[RenderScript] Add documentation for IntrinsicBLAS, and @hide
annotations.
bug: 21039492
Change-Id: I50a6beca22c9e524a76925d8e497b2618177491d
diff --git a/api/current.txt b/api/current.txt
index 3e0a1b3..71c6b38 100644
--- a/api/current.txt
+++ b/api/current.txt
@@ -28094,18 +28094,6 @@
field public static final int UPPER = 121; // 0x79
}
- public static abstract class ScriptIntrinsicBLAS.Diag implements java.lang.annotation.Annotation {
- }
-
- public static abstract class ScriptIntrinsicBLAS.Side implements java.lang.annotation.Annotation {
- }
-
- public static abstract class ScriptIntrinsicBLAS.Transpose implements java.lang.annotation.Annotation {
- }
-
- public static abstract class ScriptIntrinsicBLAS.Uplo implements java.lang.annotation.Annotation {
- }
-
public class ScriptIntrinsicBlend extends android.renderscript.ScriptIntrinsic {
method public static android.renderscript.ScriptIntrinsicBlend create(android.renderscript.RenderScript, android.renderscript.Element);
method public void forEachAdd(android.renderscript.Allocation, android.renderscript.Allocation);
diff --git a/api/system-current.txt b/api/system-current.txt
index a61b9fb53..bc50c87 100644
--- a/api/system-current.txt
+++ b/api/system-current.txt
@@ -30132,18 +30132,6 @@
field public static final int UPPER = 121; // 0x79
}
- public static abstract class ScriptIntrinsicBLAS.Diag implements java.lang.annotation.Annotation {
- }
-
- public static abstract class ScriptIntrinsicBLAS.Side implements java.lang.annotation.Annotation {
- }
-
- public static abstract class ScriptIntrinsicBLAS.Transpose implements java.lang.annotation.Annotation {
- }
-
- public static abstract class ScriptIntrinsicBLAS.Uplo implements java.lang.annotation.Annotation {
- }
-
public class ScriptIntrinsicBlend extends android.renderscript.ScriptIntrinsic {
method public static android.renderscript.ScriptIntrinsicBlend create(android.renderscript.RenderScript, android.renderscript.Element);
method public void forEachAdd(android.renderscript.Allocation, android.renderscript.Allocation);
diff --git a/rs/java/android/renderscript/ScriptIntrinsicBLAS.java b/rs/java/android/renderscript/ScriptIntrinsicBLAS.java
index f7e81b0..aa72fba 100644
--- a/rs/java/android/renderscript/ScriptIntrinsicBLAS.java
+++ b/rs/java/android/renderscript/ScriptIntrinsicBLAS.java
@@ -22,7 +22,12 @@
/**
*
- * BLAS
+ * ScriptIntrinsicBLAS class provides high performance RenderScript APIs to BLAS.
+ *
+ * The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard
+ * building blocks for performing basic vector and matrix operations.
+ *
+ * For detailed description of BLAS, please refer to http://www.netlib.org/blas/
*
**/
public final class ScriptIntrinsicBLAS extends ScriptIntrinsic {
@@ -179,24 +184,40 @@
private static final int RsBlas_bnnm = 1000;
/**
+ * Create an intrinsic to access BLAS subroutines.
+ *
+ * @param rs The RenderScript context
+ * @return ScriptIntrinsicBLAS
*/
public static ScriptIntrinsicBLAS create(RenderScript rs) {
long id = rs.nScriptIntrinsicCreate(13, Element.U32(rs).getID(rs));
return new ScriptIntrinsicBLAS(id, rs);
}
+ /**
+ * @hide
+ */
@IntDef({NO_TRANSPOSE, TRANSPOSE, CONJ_TRANSPOSE})
@Retention(RetentionPolicy.SOURCE)
public @interface Transpose {}
+ /**
+ * @hide
+ */
@IntDef({UPPER, LOWER})
@Retention(RetentionPolicy.SOURCE)
public @interface Uplo {}
+ /**
+ * @hide
+ */
@IntDef({NON_UNIT, UNIT})
@Retention(RetentionPolicy.SOURCE)
public @interface Diag {}
+ /**
+ * @hide
+ */
@IntDef({LEFT, RIGHT})
@Retention(RetentionPolicy.SOURCE)
public @interface Side {}
@@ -280,24 +301,88 @@
throw new RSRuntimeException("Incorrect vector dimensions for GEMV");
}
}
+
+ /**
+ * SGEMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d58/sgemv_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void SGEMV(@Transpose int TransA, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY) {
validateGEMV(Element.F32(mRS), TransA, A, X, incX, Y, incY);
int M = A.getType().getY();
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DGEMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dc/da8/dgemv_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void DGEMV(@Transpose int TransA, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY) {
validateGEMV(Element.F64(mRS), TransA, A, X, incX, Y, incY);
int M = A.getType().getY();
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CGEMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/d8a/cgemv_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void CGEMV(@Transpose int TransA, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY) {
validateGEMV(Element.F32_2(mRS), TransA, A, X, incX, Y, incY);
int M = A.getType().getY();
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZGEMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d40/zgemv_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void ZGEMV(@Transpose int TransA, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY) {
validateGEMV(Element.F64_2(mRS), TransA, A, X, incX, Y, incY);
int M = A.getType().getY();
@@ -305,6 +390,30 @@
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+ /**
+ * SGBMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/d46/sgbmv_8f.html
+ *
+ * Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N),
+ * but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an
+ * example showing how to convert the original matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, m):
+ * for j in range(max(0, i-kl), min(i+ku+1, n)):
+ * b[i, j-i+kl] = a[i, j]
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param KL The number of sub-diagonals of the matrix A.
+ * @param KU The number of super-diagonals of the matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains the band matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void SGBMV(@Transpose int TransA, int KL, int KU, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY) {
// GBMV has the same validation requirements as GEMV + KL and KU >= 0
validateGEMV(Element.F32(mRS), TransA, A, X, incX, Y, incY);
@@ -315,6 +424,31 @@
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sgbmv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, KL, KU);
}
+
+ /**
+ * DGBMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d2/d3f/dgbmv_8f.html
+ *
+ * Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N),
+ * but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an
+ * example showing how to convert the original matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, m):
+ * for j in range(max(0, i-kl), min(i+ku+1, n)):
+ * b[i, j-i+kl] = a[i, j]
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param KL The number of sub-diagonals of the matrix A.
+ * @param KU The number of super-diagonals of the matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains the band matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void DGBMV(@Transpose int TransA, int KL, int KU, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY) {
// GBMV has the same validation requirements as GEMV + KL and KU >= 0
validateGEMV(Element.F64(mRS), TransA, A, X, incX, Y, incY);
@@ -325,6 +459,31 @@
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dgbmv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, KL, KU);
}
+
+ /**
+ * CGBMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/d75/cgbmv_8f.html
+ *
+ * Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N),
+ * but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an
+ * example showing how to convert the original matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, m):
+ * for j in range(max(0, i-kl), min(i+ku+1, n)):
+ * b[i, j-i+kl] = a[i, j]
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param KL The number of sub-diagonals of the matrix A.
+ * @param KU The number of super-diagonals of the matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains the band matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void CGBMV(@Transpose int TransA, int KL, int KU, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY) {
// GBMV has the same validation requirements as GEMV + KL and KU >= 0
validateGEMV(Element.F32_2(mRS), TransA, A, X, incX, Y, incY);
@@ -335,6 +494,31 @@
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cgbmv, TransA, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, KL, KU);
}
+
+ /**
+ * ZGBMV performs one of the matrix-vector operations
+ * y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d9/d46/zgbmv_8f.html
+ *
+ * Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N),
+ * but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an
+ * example showing how to convert the original matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, m):
+ * for j in range(max(0, i-kl), min(i+ku+1, n)):
+ * b[i, j-i+kl] = a[i, j]
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param KL The number of sub-diagonals of the matrix A.
+ * @param KU The number of super-diagonals of the matrix A.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains the band matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void ZGBMV(@Transpose int TransA, int KL, int KU, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY) {
// GBMV has the same validation requirements as GEMV + KL and KU >= 0
validateGEMV(Element.F64_2(mRS), TransA, A, X, incX, Y, incY);
@@ -403,27 +587,103 @@
return N;
}
+ /**
+ * STRMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/d45/strmv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void STRMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
validateTRMV(Element.F32(mRS), Uplo, TransA, Diag, A, X, incX);
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_strmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DTRMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dc/d7e/dtrmv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void DTRMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
validateTRMV(Element.F64(mRS), Uplo, TransA, Diag, A, X, incX);
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtrmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * CTRMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x or x := A**H*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/df/d78/ctrmv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void CTRMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
validateTRMV(Element.F32_2(mRS), Uplo, TransA, Diag, A, X, incX);
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctrmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * ZTRMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x or x := A**H*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/dd1/ztrmv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void ZTRMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
validateTRMV(Element.F64_2(mRS), Uplo, TransA, Diag, A, X, incX);
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_ztrmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+ /**
+ * STBMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/d7d/stbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void STBMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBMV has the same requirements as TRMV + K >= 0
if (K < 0) {
@@ -433,6 +693,28 @@
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_stbmv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DTBMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/df/d29/dtbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void DTBMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBMV has the same requirements as TRMV + K >= 0
if (K < 0) {
@@ -442,6 +724,28 @@
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtbmv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * CTBMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x or x := A**H*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/dcd/ctbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void CTBMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBMV has the same requirements as TRMV + K >= 0
if (K < 0) {
@@ -451,6 +755,28 @@
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctbmv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * ZTBMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x or x := A**H*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/d39/ztbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void ZTBMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBMV has the same requirements as TRMV + K >= 0
if (K < 0) {
@@ -460,22 +786,124 @@
int N = A.getType().getY();
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_ztbmv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * STPMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/db1/stpmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void STPMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
int N = validateTPMV(Element.F32(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_stpmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DTPMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dc/dcd/dtpmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void DTPMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
int N = validateTPMV(Element.F64(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtpmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * CTPMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x or x := A**H*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/dbb/ctpmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void CTPMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
int N = validateTPMV(Element.F32_2(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctpmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * ZTPMV performs one of the matrix-vector operations
+ * x := A*x or x := A**T*x or x := A**H*x
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d2/d9e/ztpmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void ZTPMV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
int N = validateTPMV(Element.F64_2(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_ztpmv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * STRSV solves one of the systems of equations
+ * A*x = b or A**T*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/d2a/strsv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void STRSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
// TRSV is the same as TRMV
validateTRMV(Element.F32(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -483,6 +911,20 @@
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_strsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DTRSV solves one of the systems of equations
+ * A*x = b or A**T*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/d96/dtrsv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void DTRSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
// TRSV is the same as TRMV
validateTRMV(Element.F64(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -490,6 +932,20 @@
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtrsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * CTRSV solves one of the systems of equations
+ * A*x = b or A**T*x = b or A**H*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/dc8/ctrsv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void CTRSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
// TRSV is the same as TRMV
validateTRMV(Element.F32_2(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -497,6 +953,20 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctrsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * ZTRSV solves one of the systems of equations
+ * A*x = b or A**T*x = b or A**H*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d1/d2f/ztrsv_8f.html
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void ZTRSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation A, Allocation X, int incX) {
// TRSV is the same as TRMV
validateTRMV(Element.F64_2(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -504,6 +974,28 @@
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_ztrsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * STBSV solves one of the systems of equations
+ * A*x = b or A**T*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/d1f/stbsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void STBSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBSV is the same as TRMV + K >= 0
validateTRMV(Element.F32(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -513,6 +1005,28 @@
}
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_stbsv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DTBSV solves one of the systems of equations
+ * A*x = b or A**T*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/dcf/dtbsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void DTBSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBSV is the same as TRMV + K >= 0
validateTRMV(Element.F64(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -522,6 +1036,28 @@
}
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtbsv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, A.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * CTBSV solves one of the systems of equations
+ * A*x = b or A**T*x = b or A**H*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d9/d5f/ctbsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void CTBSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBSV is the same as TRMV + K >= 0
validateTRMV(Element.F32_2(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -531,6 +1067,28 @@
}
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctbsv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * ZTBSV solves one of the systems of equations
+ * A*x = b or A**T*x = b or A**H*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/d5a/ztbsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param K The number of off-diagonals of the matrix A
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void ZTBSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, int K, Allocation A, Allocation X, int incX) {
// TBSV is the same as TRMV + K >= 0
validateTRMV(Element.F64_2(mRS), Uplo, TransA, Diag, A, X, incX);
@@ -540,21 +1098,109 @@
}
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_ztbsv, TransA, 0, 0, Uplo, Diag, 0, N, K, 0, 0, A.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * STPSV solves one of the systems of equations
+ * A*x = b or A**T*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/d7c/stpsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void STPSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
// TPSV is same as TPMV
int N = validateTPMV(Element.F32(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_stpsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DTPSV solves one of the systems of equations
+ * A*x = b or A**T*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d9/d84/dtpsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void DTPSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
// TPSV is same as TPMV
int N = validateTPMV(Element.F64(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtpsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * CTPSV solves one of the systems of equations
+ * A*x = b or A**T*x = b or A**H*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/d56/ctpsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void CTPSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
// TPSV is same as TPMV
int N = validateTPMV(Element.F32_2(mRS), Uplo, TransA, Diag, Ap, X, incX);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctpsv, TransA, 0, 0, Uplo, Diag, 0, N, 0, 0, 0, Ap.getID(mRS), X.getID(mRS), 0, 0, 0, incX, 0, 0, 0);
}
+
+ /**
+ * ZTPSV solves one of the systems of equations
+ * A*x = b or A**T*x = b or A**H*x = b
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/da/d57/ztpsv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the matrix is an upper or lower triangular matrix.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param Ap The input allocation contains packed matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ */
public void ZTPSV(@Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Allocation Ap, Allocation X, int incX) {
// TPSV is same as TPMV
int N = validateTPMV(Element.F64_2(mRS), Uplo, TransA, Diag, Ap, X, incX);
@@ -768,10 +1414,49 @@
return N;
}
+ /**
+ * SSYMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d2/d94/ssymv_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void SSYMV(@Uplo int Uplo, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY) {
int N = validateSYMV(Element.F32(mRS), Uplo, A, X, Y, incX, incY);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssymv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * SSBMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/da1/ssbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the band matrix A is being supplied.
+ * @param K The number of off-diagonals of the matrix A
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void SSBMV(@Uplo int Uplo, int K, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY) {
// SBMV is the same as SYMV + K >= 0
if (K < 0) {
@@ -780,36 +1465,186 @@
int N = validateSYMV(Element.F32(mRS), Uplo, A, X, Y, incX, incY);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssbmv, 0, 0, 0, Uplo, 0, 0, N, K, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * SSPMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/d68/sspmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form.
+ * @param alpha The scalar alpha.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void SSPMV(@Uplo int Uplo, float alpha, Allocation Ap, Allocation X, int incX, float beta, Allocation Y, int incY) {
int N = validateSPMV(Element.F32(mRS), Uplo, Ap, X, incX, Y, incY);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sspmv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, Ap.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * SGER performs the rank 1 operation
+ * A := alpha*x*y**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d5c/sger_8f.html
+ *
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ */
public void SGER(float alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
int M = A.getType().getY();
int N = A.getType().getX();
validateGER(Element.F32(mRS), X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sger, 0, 0, 0, 0, 0, M, N, 0, alpha, X.getID(mRS), Y.getID(mRS), 0.f, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * SSYR performs the rank 1 operation
+ * A := alpha*x*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/dac/ssyr_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ */
public void SSYR(@Uplo int Uplo, float alpha, Allocation X, int incX, Allocation A) {
int N = validateSYR(Element.F32(mRS), Uplo, X, incX, A);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssyr, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), A.getID(mRS), 0.f, 0, incX, 0, 0, 0);
}
+
+ /**
+ * SSPR performs the rank 1 operation
+ * A := alpha*x*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d2/d9b/sspr_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ */
public void SSPR(@Uplo int Uplo, float alpha, Allocation X, int incX, Allocation Ap) {
int N = validateSPR(Element.F32(mRS), Uplo, X, incX, Ap);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sspr, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), Ap.getID(mRS), 0.f, 0, incX, 0, 0, 0);
}
+
+ /**
+ * SSYR2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**T + alpha*y*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d99/ssyr2_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ */
public void SSYR2(@Uplo int Uplo, float alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
int N = validateSYR2(Element.F32(mRS), Uplo, X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssyr2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), Y.getID(mRS), 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * SSPR2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**T + alpha*y*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d3e/sspr2_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ */
public void SSPR2(@Uplo int Uplo, float alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap) {
int N = validateSPR2(Element.F32(mRS), Uplo, X, incX, Y, incY, Ap);
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sspr2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), Y.getID(mRS), 0, Ap.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DSYMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/dbe/dsymv_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void DSYMV(@Uplo int Uplo, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY) {
int N = validateSYMV(Element.F64(mRS), Uplo, A, X, Y, incX, incY);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsymv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DSBMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/d1e/dsbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the band matrix A is being supplied.
+ * @param K The number of off-diagonals of the matrix A
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void DSBMV(@Uplo int Uplo, int K, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY) {
// SBMV is the same as SYMV + K >= 0
if (K < 0) {
@@ -818,28 +1653,138 @@
int N = validateSYMV(Element.F64(mRS), Uplo, A, X, Y, incX, incY);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsbmv, 0, 0, 0, Uplo, 0, 0, N, K, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DSPMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/d85/dspmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form.
+ * @param alpha The scalar alpha.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void DSPMV(@Uplo int Uplo, double alpha, Allocation Ap, Allocation X, int incX, double beta, Allocation Y, int incY) {
int N = validateSPMV(Element.F64(mRS), Uplo, Ap, X, incX, Y, incY);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dspmv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, Ap.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DGER performs the rank 1 operation
+ * A := alpha*x*y**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dc/da8/dger_8f.html
+ *
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ */
public void DGER(double alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
int M = A.getType().getY();
int N = A.getType().getX();
validateGER(Element.F64(mRS), X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dger, 0, 0, 0, 0, 0, M, N, 0, alpha, X.getID(mRS), Y.getID(mRS), 0.f, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DSYR performs the rank 1 operation
+ * A := alpha*x*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/d60/dsyr_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ */
public void DSYR(@Uplo int Uplo, double alpha, Allocation X, int incX, Allocation A) {
int N = validateSYR(Element.F64(mRS), Uplo, X, incX, A);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsyr, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), A.getID(mRS), 0.f, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DSPR performs the rank 1 operation
+ * A := alpha*x*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dd/dba/dspr_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ */
public void DSPR(@Uplo int Uplo, double alpha, Allocation X, int incX, Allocation Ap) {
int N = validateSPR(Element.F64(mRS), Uplo, X, incX, Ap);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dspr, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), Ap.getID(mRS), 0.f, 0, incX, 0, 0, 0);
}
+
+ /**
+ * DSYR2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**T + alpha*y*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/d41/dsyr2_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ */
public void DSYR2(@Uplo int Uplo, double alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
int N = validateSYR2(Element.F64(mRS), Uplo, X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsyr2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), Y.getID(mRS), 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * DSPR2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**T + alpha*y*x**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dd/d9e/dspr2_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ */
public void DSPR2(@Uplo int Uplo, double alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap) {
int N = validateSPR2(Element.F64(mRS), Uplo, X, incX, Y, incY, Ap);
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dspr2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, X.getID(mRS), Y.getID(mRS), 0, Ap.getID(mRS), incX, incY, 0, 0);
@@ -876,11 +1821,50 @@
}
+ /**
+ * CHEMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d7/d51/chemv_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void CHEMV(@Uplo int Uplo, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY) {
// HEMV is the same as SYR2 validation-wise
int N = validateSYR2(Element.F32_2(mRS), Uplo, X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_chemv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CHBMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/dc2/chbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the band matrix A is being supplied.
+ * @param K The number of off-diagonals of the matrix A
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void CHBMV(@Uplo int Uplo, int K, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY) {
// HBMV is the same as SYR2 validation-wise
int N = validateSYR2(Element.F32_2(mRS), Uplo, X, incX, Y, incY, A);
@@ -889,17 +1873,69 @@
}
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_chbmv, 0, 0, 0, Uplo, 0, 0, N, K, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CHPMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d2/d06/chpmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form.
+ * @param alpha The scalar alpha.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void CHPMV(@Uplo int Uplo, Float2 alpha, Allocation Ap, Allocation X, int incX, Float2 beta, Allocation Y, int incY) {
// HPMV is the same as SPR2
int N = validateSPR2(Element.F32_2(mRS), Uplo, X, incX, Y, incY, Ap);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_chpmv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, Ap.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CGERU performs the rank 1 operation
+ * A := alpha*x*y**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d5f/cgeru_8f.html
+ *
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ */
public void CGERU(Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
validateGERU(Element.F32_2(mRS), X, incX, Y, incY, A);
int M = A.getType().getY();
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cgeru, 0, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CGERC performs the rank 1 operation
+ * A := alpha*x*y**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dd/d84/cgerc_8f.html
+ *
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ */
public void CGERC(Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
// same as GERU
validateGERU(Element.F32_2(mRS), X, incX, Y, incY, A);
@@ -907,31 +1943,143 @@
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cgerc, 0, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CHER performs the rank 1 operation
+ * A := alpha*x*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/d6d/cher_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ */
public void CHER(@Uplo int Uplo, float alpha, Allocation X, int incX, Allocation A) {
// same as SYR
int N = validateSYR(Element.F32_2(mRS), Uplo, X, incX, A);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cher, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, 0, X.getID(mRS), 0, 0, 0, A.getID(mRS), incX, 0, 0, 0);
}
+
+ /**
+ * CHPR performs the rank 1 operation
+ * A := alpha*x*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/dcd/chpr_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ */
public void CHPR(@Uplo int Uplo, float alpha, Allocation X, int incX, Allocation Ap) {
// equivalent to SPR for validation
int N = validateSPR(Element.F32_2(mRS), Uplo, X, incX, Ap);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_chpr, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, 0, X.getID(mRS), 0, 0, 0, Ap.getID(mRS), incX, 0, 0, 0);
}
+
+ /**
+ * CHER2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**H + alpha*y*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d87/cher2_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ */
public void CHER2(@Uplo int Uplo, Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
// same as SYR2
int N = validateSYR2(Element.F32_2(mRS), Uplo, X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cher2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * CHPR2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**H + alpha*y*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/d44/chpr2_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F32_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F32_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ */
public void CHPR2(@Uplo int Uplo, Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap) {
// same as SPR2
int N = validateSPR2(Element.F32_2(mRS), Uplo, X, incX, Y, incY, Ap);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_chpr2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, Ap.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZHEMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/ddd/zhemv_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void ZHEMV(@Uplo int Uplo, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY) {
// HEMV is the same as SYR2 validation-wise
int N = validateSYR2(Element.F64_2(mRS), Uplo, X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zhemv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZHBMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/d1a/zhbmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N),
+ * but only the region N*(K+1) will be referenced. The following subroutine can is an
+ * example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'.
+ * for i in range(0, n):
+ * for j in range(i, min(i+k+1, n)):
+ * b[i, j-i] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the band matrix A is being supplied.
+ * @param K The number of off-diagonals of the matrix A
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void ZHBMV(@Uplo int Uplo, int K, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY) {
// HBMV is the same as SYR2 validation-wise
int N = validateSYR2(Element.F64_2(mRS), Uplo, X, incX, Y, incY, A);
@@ -940,17 +2088,69 @@
}
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zhbmv, 0, 0, 0, Uplo, 0, 0, N, K, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZHPMV performs the matrix-vector operation
+ * y := alpha*A*x + beta*y
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/d60/zhpmv_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form.
+ * @param alpha The scalar alpha.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param beta The scalar beta.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ */
public void ZHPMV(@Uplo int Uplo, Double2 alpha, Allocation Ap, Allocation X, int incX, Double2 beta, Allocation Y, int incY) {
// HPMV is the same as SPR2
int N = validateSPR2(Element.F64_2(mRS), Uplo, X, incX, Y, incY, Ap);
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zhpmv, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, Ap.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZGERU performs the rank 1 operation
+ * A := alpha*x*y**T + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d7/d12/zgeru_8f.html
+ *
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ */
public void ZGERU(Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
validateGERU(Element.F64_2(mRS), X, incX, Y, incY, A);
int M = A.getType().getY();
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zgeru, 0, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZGERC performs the rank 1 operation
+ * A := alpha*x*y**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/dad/zgerc_8f.html
+ *
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ */
public void ZGERC(Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
// same as GERU
validateGERU(Element.F64_2(mRS), X, incX, Y, incY, A);
@@ -958,21 +2158,93 @@
int N = A.getType().getX();
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zgerc, 0, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZHER performs the rank 1 operation
+ * A := alpha*x*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/d0e/zher_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ */
public void ZHER(@Uplo int Uplo, double alpha, Allocation X, int incX, Allocation A) {
// same as SYR
int N = validateSYR(Element.F64_2(mRS), Uplo, X, incX, A);
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zher, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, 0, X.getID(mRS), 0, 0, 0, A.getID(mRS), incX, 0, 0, 0);
}
+
+ /**
+ * ZHPR performs the rank 1 operation
+ * A := alpha*x*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/de1/zhpr_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ */
public void ZHPR(@Uplo int Uplo, double alpha, Allocation X, int incX, Allocation Ap) {
// equivalent to SPR for validation
int N = validateSPR(Element.F64_2(mRS), Uplo, X, incX, Ap);
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zhpr, 0, 0, 0, Uplo, 0, 0, N, 0, alpha, 0, X.getID(mRS), 0, 0, 0, Ap.getID(mRS), incX, 0, 0, 0);
}
+
+ /**
+ * ZHER2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**H + alpha*y*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/da/d8a/zher2_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ */
public void ZHER2(@Uplo int Uplo, Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A) {
// same as SYR2
int N = validateSYR2(Element.F64_2(mRS), Uplo, X, incX, Y, incY, A);
mRS.nScriptIntrinsicBLAS_Z(getID(mRS), RsBlas_zher2, 0, 0, 0, Uplo, 0, 0, N, 0, alpha.x, alpha.y, X.getID(mRS), Y.getID(mRS), 0, 0, A.getID(mRS), incX, incY, 0, 0);
}
+
+ /**
+ * ZHPR2 performs the symmetric rank 2 operation
+ * A := alpha*x*y**H + alpha*y*x**H + A
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d5/d52/zhpr2_8f.html
+ *
+ * Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2,
+ * The following subroutine can is an example showing how to convert a UPPER trianglar matrix
+ * 'a' to packed matrix 'b'.
+ * k = 0
+ * for i in range(0, n):
+ * for j in range(i, n):
+ * b[k++] = a[i, j]
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part is to be supplied in the packed form.
+ * @param alpha The scalar alpha.
+ * @param X The input allocation contains vector x, supported elements type {@link Element#F64_2}.
+ * @param incX The increment for the elements of vector x, must be larger than zero.
+ * @param Y The input allocation contains vector y, supported elements type {@link Element#F64_2}.
+ * @param incY The increment for the elements of vector y, must be larger than zero.
+ * @param Ap The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ */
public void ZHPR2(@Uplo int Uplo, Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap) {
// same as SPR2
int N = validateSPR2(Element.F64_2(mRS), Uplo, X, incX, Y, incY, Ap);
@@ -1051,6 +2323,20 @@
}
+ /**
+ * SGEMM performs one of the matrix-matrix operations
+ * C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/de2/sgemm_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param TransB The type of transpose applied to matrix B.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32}.
+ */
public void SGEMM(@Transpose int TransA, @Transpose int TransB, float alpha, Allocation A,
Allocation B, float beta, Allocation C) {
validateTranspose(TransA);
@@ -1073,6 +2359,21 @@
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_sgemm, TransA, TransB, 0, 0, 0, M, N, K, alpha, A.getID(mRS), B.getID(mRS),
beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * DGEMM performs one of the matrix-matrix operations
+ * C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d7/d2b/dgemm_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param TransB The type of transpose applied to matrix B.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64}.
+ */
public void DGEMM(@Transpose int TransA, @Transpose int TransB, double alpha, Allocation A,
Allocation B, double beta, Allocation C) {
validateTranspose(TransA);
@@ -1094,6 +2395,21 @@
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dgemm, TransA, TransB, 0, 0, 0, M, N, K, alpha, A.getID(mRS), B.getID(mRS),
beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * CGEMM performs one of the matrix-matrix operations
+ * C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T or op(X) = X**H
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/d5b/cgemm_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param TransB The type of transpose applied to matrix B.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CGEMM(@Transpose int TransA, @Transpose int TransB, Float2 alpha, Allocation A,
Allocation B, Float2 beta, Allocation C) {
validateTranspose(TransA);
@@ -1116,6 +2432,20 @@
beta.x, beta.y, C.getID(mRS), 0, 0, 0, 0);
}
+ /**
+ * ZGEMM performs one of the matrix-matrix operations
+ * C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T or op(X) = X**H
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d7/d76/zgemm_8f.html
+ *
+ * @param TransA The type of transpose applied to matrix A.
+ * @param TransB The type of transpose applied to matrix B.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2
+ */
public void ZGEMM(@Transpose int TransA, @Transpose int TransB, Double2 alpha, Allocation A,
Allocation B, Double2 beta, Allocation C) {
validateTranspose(TransA);
@@ -1138,6 +2468,20 @@
beta.x, beta.y, C.getID(mRS), 0, 0, 0, 0);
}
+ /**
+ * SSYMM performs one of the matrix-matrix operations
+ * C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d7/d42/ssymm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32}.
+ */
public void SSYMM(@Side int Side, @Uplo int Uplo, float alpha, Allocation A,
Allocation B, float beta, Allocation C) {
validateSide(Side);
@@ -1150,6 +2494,21 @@
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssymm, 0, 0, Side, Uplo, 0, C.getType().getY(), C.getType().getX(), 0, alpha, A.getID(mRS), B.getID(mRS),
beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * DSYMM performs one of the matrix-matrix operations
+ * C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/db0/dsymm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64}.
+ */
public void DSYMM(@Side int Side, @Uplo int Uplo, double alpha, Allocation A,
Allocation B, double beta, Allocation C) {
validateSide(Side);
@@ -1161,6 +2520,21 @@
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsymm, 0, 0, Side, Uplo, 0, C.getType().getY(), C.getType().getX(), 0, alpha, A.getID(mRS), B.getID(mRS),
beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * CSYMM performs one of the matrix-matrix operations
+ * C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/db/d59/csymm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CSYMM(@Side int Side, @Uplo int Uplo, Float2 alpha, Allocation A,
Allocation B, Float2 beta, Allocation C) {
validateSide(Side);
@@ -1172,6 +2546,21 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_csymm, 0, 0, Side, Uplo, 0, C.getType().getY(), C.getType().getX(), 0, alpha.x, alpha.y, A.getID(mRS), B.getID(mRS),
beta.x, beta.y, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * ZSYMM performs one of the matrix-matrix operations
+ * C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/df/d51/zsymm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2}.
+ */
public void ZSYMM(@Side int Side, @Uplo int Uplo, Double2 alpha, Allocation A,
Allocation B, Double2 beta, Allocation C) {
validateSide(Side);
@@ -1184,6 +2573,19 @@
beta.x, beta.y, C.getID(mRS), 0, 0, 0, 0);
}
+ /**
+ * SSYRK performs one of the symmetric rank k operations
+ * C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d0/d40/ssyrk_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32}.
+ */
public void SSYRK(@Uplo int Uplo, @Transpose int Trans, float alpha, Allocation A, float beta, Allocation C) {
validateTranspose(Trans);
validateUplo(Uplo);
@@ -1198,6 +2600,19 @@
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssyrk, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), K, alpha, A.getID(mRS), 0, beta, C.getID(mRS), 0, 0, 0, 0);
}
+ /**
+ * DSYRK performs one of the symmetric rank k operations
+ * C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dc/d05/dsyrk_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64}.
+ */
public void DSYRK(@Uplo int Uplo, @Transpose int Trans, double alpha, Allocation A, double beta, Allocation C) {
validateTranspose(Trans);
validateUplo(Uplo);
@@ -1210,6 +2625,20 @@
}
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsyrk, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), K, alpha, A.getID(mRS), 0, beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * CSYRK performs one of the symmetric rank k operations
+ * C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/d6a/csyrk_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CSYRK(@Uplo int Uplo, @Transpose int Trans, Float2 alpha, Allocation A, Float2 beta, Allocation C) {
validateTranspose(Trans);
validateUplo(Uplo);
@@ -1223,6 +2652,20 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_csyrk, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), K, alpha.x, alpha.y, A.getID(mRS), 0, beta.x, beta.y,
C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * ZSYRK performs one of the symmetric rank k operations
+ * C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/d54/zsyrk_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2}.
+ */
public void ZSYRK(@Uplo int Uplo, @Transpose int Trans, Double2 alpha, Allocation A, Double2 beta, Allocation C) {
validateTranspose(Trans);
validateUplo(Uplo);
@@ -1262,6 +2705,21 @@
throw new RSRuntimeException("Invalid A and B in SYR2K");
}
}
+
+ /**
+ * SSYR2K performs one of the symmetric rank 2k operations
+ * C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/df/d3d/ssyr2k_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32}.
+ */
public void SSYR2K(@Uplo int Uplo, @Transpose int Trans, float alpha, Allocation A, Allocation B, float beta, Allocation C) {
validateUplo(Uplo);
validateSYR2K(Element.F32(mRS), Trans, A, B, C);
@@ -1273,6 +2731,21 @@
}
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_ssyr2k, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), K, alpha, A.getID(mRS), B.getID(mRS), beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * DSYR2K performs one of the symmetric rank 2k operations
+ * C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d1/dec/dsyr2k_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64}.
+ */
public void DSYR2K(@Uplo int Uplo, @Transpose int Trans, double alpha, Allocation A, Allocation B, double beta, Allocation C) {
validateUplo(Uplo);
validateSYR2K(Element.F64(mRS), Trans, A, B, C);
@@ -1284,6 +2757,21 @@
}
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dsyr2k, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), K, alpha, A.getID(mRS), B.getID(mRS), beta, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * CSYR2K performs one of the symmetric rank 2k operations
+ * C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/d7e/csyr2k_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CSYR2K(@Uplo int Uplo, @Transpose int Trans, Float2 alpha, Allocation A, Allocation B, Float2 beta, Allocation C) {
validateUplo(Uplo);
validateSYR2K(Element.F32_2(mRS), Trans, A, B, C);
@@ -1295,6 +2783,21 @@
}
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_csyr2k, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), K, alpha.x, alpha.y, A.getID(mRS), B.getID(mRS), beta.x, beta.y, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * ZSYR2K performs one of the symmetric rank 2k operations
+ * C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/df/d20/zsyr2k_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2}.
+ */
public void ZSYR2K(@Uplo int Uplo, @Transpose int Trans, Double2 alpha, Allocation A, Allocation B, Double2 beta, Allocation C) {
validateUplo(Uplo);
validateSYR2K(Element.F64_2(mRS), Trans, A, B, C);
@@ -1334,6 +2837,22 @@
}
}
}
+
+ /**
+ * STRMM performs one of the matrix-matrix operations
+ * B := alpha*op(A)*B or B := alpha*B*op(A)
+ * op(A) is one of op(A) = A or op(A) = A**T
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/df/d01/strmm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32}.
+ */
public void STRMM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, float alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1341,6 +2860,22 @@
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_strmm, TransA, 0, Side, Uplo, Diag, B.getType().getY(), B.getType().getX(), 0,
alpha, A.getID(mRS), B.getID(mRS), 0.f, 0, 0, 0, 0, 0);
}
+
+ /**
+ * DTRMM performs one of the matrix-matrix operations
+ * B := alpha*op(A)*B or B := alpha*B*op(A)
+ * op(A) is one of op(A) = A or op(A) = A**T
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/dd/d19/dtrmm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64}.
+ */
public void DTRMM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, double alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1348,6 +2883,22 @@
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtrmm, TransA, 0, Side, Uplo, Diag, B.getType().getY(), B.getType().getX(), 0,
alpha, A.getID(mRS), B.getID(mRS), 0, 0, 0, 0, 0, 0);
}
+
+ /**
+ * CTRMM performs one of the matrix-matrix operations
+ * B := alpha*op(A)*B or B := alpha*B*op(A)
+ * op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d4/d9b/ctrmm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ */
public void CTRMM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Float2 alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1355,6 +2906,22 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctrmm, TransA, 0, Side, Uplo, Diag, B.getType().getY(), B.getType().getX(), 0,
alpha.x, alpha.y, A.getID(mRS), B.getID(mRS), 0, 0, 0, 0, 0, 0, 0);
}
+
+ /**
+ * ZTRMM performs one of the matrix-matrix operations
+ * B := alpha*op(A)*B or B := alpha*B*op(A)
+ * op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/de1/ztrmm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2}.
+ */
public void ZTRMM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Double2 alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1392,6 +2959,22 @@
}
}
}
+
+ /**
+ * STRSM solves one of the matrix equations
+ * op(A)*X := alpha*B or X*op(A) := alpha*B
+ * op(A) is one of op(A) = A or op(A) = A**T
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d2/d8b/strsm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32}.
+ */
public void STRSM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, float alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1399,6 +2982,22 @@
mRS.nScriptIntrinsicBLAS_Single(getID(mRS), RsBlas_strsm, TransA, 0, Side, Uplo, Diag, B.getType().getY(), B.getType().getX(), 0,
alpha, A.getID(mRS), B.getID(mRS), 0, 0, 0, 0, 0, 0);
}
+
+ /**
+ * DTRSM solves one of the matrix equations
+ * op(A)*X := alpha*B or X*op(A) := alpha*B
+ * op(A) is one of op(A) = A or op(A) = A**T
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/da7/dtrsm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64}.
+ */
public void DTRSM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, double alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1406,6 +3005,22 @@
mRS.nScriptIntrinsicBLAS_Double(getID(mRS), RsBlas_dtrsm, TransA, 0, Side, Uplo, Diag, B.getType().getY(), B.getType().getX(), 0,
alpha, A.getID(mRS), B.getID(mRS), 0, 0, 0, 0, 0, 0);
}
+
+ /**
+ * CTRSM solves one of the matrix equations
+ * op(A)*X := alpha*B or X*op(A) := alpha*B
+ * op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/de/d30/ctrsm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ */
public void CTRSM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Float2 alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1413,6 +3028,22 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_ctrsm, TransA, 0, Side, Uplo, Diag, B.getType().getY(), B.getType().getX(), 0,
alpha.x, alpha.y, A.getID(mRS), B.getID(mRS), 0, 0, 0, 0, 0, 0, 0);
}
+
+ /**
+ * ZTRSM solves one of the matrix equations
+ * op(A)*X := alpha*B or X*op(A) := alpha*B
+ * op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d1/d39/ztrsm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether matrix A is upper or lower triangular.
+ * @param TransA The type of transpose applied to matrix A.
+ * @param Diag Specifies whether or not A is unit triangular.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2}.
+ */
public void ZTRSM(@Side int Side, @Uplo int Uplo, @Transpose int TransA, @Diag int Diag, Double2 alpha, Allocation A, Allocation B) {
validateUplo(Uplo);
validateDiag(Diag);
@@ -1444,12 +3075,42 @@
throw new RSRuntimeException("Called HEMM with mismatched B and C");
}
}
+
+ /**
+ * CHEMM performs one of the matrix-matrix operations
+ * C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d3/d66/chemm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CHEMM(@Side int Side, @Uplo int Uplo, Float2 alpha, Allocation A, Allocation B, Float2 beta, Allocation C) {
validateUplo(Uplo);
validateHEMM(Element.F32_2(mRS), Side, A, B, C);
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_chemm, 0, 0, Side, Uplo, 0, C.getType().getY(), C.getType().getX(), 0,
alpha.x, alpha.y, A.getID(mRS), B.getID(mRS), beta.x, beta.y, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * ZHEMM performs one of the matrix-matrix operations
+ * C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d6/d3e/zhemm_8f.html
+ *
+ * @param Side Specifies whether the symmetric matrix A appears on the left or right.
+ * @param Uplo Specifies whether the upper or lower triangular part is to be referenced.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2}.
+ */
public void ZHEMM(@Side int Side, @Uplo int Uplo, Double2 alpha, Allocation A, Allocation B, Double2 beta, Allocation C) {
validateUplo(Uplo);
validateHEMM(Element.F64_2(mRS), Side, A, B, C);
@@ -1477,6 +3138,20 @@
}
}
}
+
+ /**
+ * CHERK performs one of the hermitian rank k operations
+ * C := alpha*A*A**H + beta*C or C := alpha*A**H*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d8/d52/cherk_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CHERK(@Uplo int Uplo, @Transpose int Trans, float alpha, Allocation A, float beta, Allocation C) {
validateUplo(Uplo);
validateHERK(Element.F32_2(mRS), Trans, A, C);
@@ -1489,6 +3164,20 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cherk, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), k,
alpha, 0, A.getID(mRS), 0, beta, 0, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * ZHERK performs one of the hermitian rank k operations
+ * C := alpha*A*A**H + beta*C or C := alpha*A**H*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d1/db1/zherk_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2}.
+ */
public void ZHERK(@Uplo int Uplo, @Transpose int Trans, double alpha, Allocation A, double beta, Allocation C) {
validateUplo(Uplo);
validateHERK(Element.F64_2(mRS), Trans, A, C);
@@ -1526,6 +3215,21 @@
throw new RSRuntimeException("Called HER2K with invalid A and B matrices");
}
}
+
+ /**
+ * CHER2K performs one of the hermitian rank 2k operations
+ * C := alpha*A*B**H + conjg( alpha )*B*A**H + beta*C or C := alpha*A**H*B + conjg( alpha )*B**H*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d1/d82/cher2k_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F32_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F32_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F32_2}.
+ */
public void CHER2K(@Uplo int Uplo, @Transpose int Trans, Float2 alpha, Allocation A, Allocation B, float beta, Allocation C) {
validateUplo(Uplo);
validateHER2K(Element.F32_2(mRS), Trans, A, B, C);
@@ -1538,6 +3242,21 @@
mRS.nScriptIntrinsicBLAS_Complex(getID(mRS), RsBlas_cher2k, Trans, 0, 0, Uplo, 0, 0, C.getType().getX(), k, alpha.x, alpha.y,
A.getID(mRS), B.getID(mRS), beta, 0, C.getID(mRS), 0, 0, 0, 0);
}
+
+ /**
+ * ZHER2K performs one of the hermitian rank 2k operations
+ * C := alpha*A*B**H + conjg( alpha )*B*A**H + beta*C or C := alpha*A**H*B + conjg( alpha )*B**H*A + beta*C
+ *
+ * Details: http://www.netlib.org/lapack/explore-html/d7/dfa/zher2k_8f.html
+ *
+ * @param Uplo Specifies whether the upper or lower triangular part of C is to be referenced.
+ * @param Trans The type of transpose applied to the operation.
+ * @param alpha The scalar alpha.
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#F64_2}.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#F64_2}.
+ * @param beta The scalar beta.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#F64_2}.
+ */
public void ZHER2K(@Uplo int Uplo, @Transpose int Trans, Double2 alpha, Allocation A, Allocation B, double beta, Allocation C) {
validateUplo(Uplo);
validateHER2K(Element.F64_2(mRS), Trans, A, B, C);
@@ -1553,9 +3272,19 @@
/**
- *
- * 8-bit GEMM-like operation for neural networks
- *
+ * 8-bit GEMM-like operation for neural networks: C = B.transposed() * A
+ * Calculations are done in 1.10.21 fixed-point format for the final output,
+ * just before there's a shift down to drop the fractional parts. The output
+ * values are gated to 0 to 255 to fit in a byte, but the 10-bit format
+ * gives some headroom to avoid wrapping around on small overflows.
+ *
+ * @param A The input allocation contains matrix A, supported elements type {@link Element#U8}.
+ * @param a_offset The offset for all values in matrix A, e.g A[i,j] = A[i,j] - a_offset.
+ * @param B The input allocation contains matrix B, supported elements type {@link Element#U8}.
+ * @param b_offset The offset for all values in matrix B, e.g B[i,j] = B[i,j] - b_offset.
+ * @param C The input allocation contains matrix C, supported elements type {@link Element#U8}.
+ * @param c_offset The offset for all values in matrix C.
+ * @param c_mult The multiplier for all values in matrix C, e.g C[i,j] = (C[i,j] + c_offset) * c_mult.
**/
public void BNNM(Allocation A, int a_offset, Allocation B, int b_offset, Allocation C, int c_offset, int c_mult) {
validateL3(Element.U8(mRS), NO_TRANSPOSE, TRANSPOSE, 0, A, B, C);