📄 sspr.cu
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/* * Copyright 1993-2008 NVIDIA Corporation. All rights reserved. * * NOTICE TO USER: * * This source code is subject to NVIDIA ownership rights under U.S. and * international Copyright laws. * * This software and the information contained herein is being provided * under the terms and conditions of a Source Code License Agreement. * * NVIDIA MAKES NO REPRESENTATION ABOUT THE SUITABILITY OF THIS SOURCE * CODE FOR ANY PURPOSE. IT IS PROVIDED "AS IS" WITHOUT EXPRESS OR * IMPLIED WARRANTY OF ANY KIND. NVIDIA DISCLAIMS ALL WARRANTIES WITH * REGARD TO THIS SOURCE CODE, INCLUDING ALL IMPLIED WARRANTIES OF * MERCHANTABILITY, NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE. * IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL, * OR CONSEQUENTIAL DAMAGES, OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS * OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE * OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE * OR PERFORMANCE OF THIS SOURCE CODE. * * U.S. Government End Users. This source code is a "commercial item" as * that term is defined at 48 C.F.R. 2.101 (OCT 1995), consisting of * "commercial computer software" and "commercial computer software * documentation" as such terms are used in 48 C.F.R. 12.212 (SEPT 1995) * and is provided to the U.S. Government only as a commercial end item. * Consistent with 48 C.F.R.12.212 and 48 C.F.R. 227.7202-1 through * 227.7202-4 (JUNE 1995), all U.S. Government End Users acquire the * source code with only those rights set forth herein. *//* This file contains the implementation of the BLAS-2 function sspr */#include <stdlib.h>#include <assert.h>#include <string.h>#include <stdio.h>#include <limits.h>#include <ctype.h>#include <math.h>#include "cublas.h" /* CUBLAS public header file */#include "cublasP.h" /* CUBLAS private header file */__global__ void sspr_up_main (struct cublasSsprParams parms);__global__ void sspr_lo_main (struct cublasSsprParams parms);/* * void * cublasSspr (char uplo, int n, float alpha, const float *x, int incx, * float *AP) * * performs the symmetric rank 1 operation * * A = alpha * x * transpose(x) + A, * * where alpha is a single precision scalar and x is an n element single * precision vector. A is a symmetric n x n matrix consisting of single * precision elements that is supplied in packed form. * * Input * ----- * uplo specifies whether the matrix data is stored in the upper or the lower * triangular part of array AP. If uplo == 'U' or 'u', then the upper * triangular part of A is supplied in AP. If uplo == 'L' or 'l', then * the lower triangular part of A is supplied in AP. * n specifies the number of rows and columns of the matrix A. It must be * at least zero. * alpha single precision scalar multiplier applied to x * transpose(x). * x single precision array of length at least (1 + (n - 1) * abs(incx)). * incx storage spacing between elements of x. incx must not be zero. * AP single precision array with at least ((n * (n + 1)) / 2) elements. If * uplo == 'U' or 'u', the array AP contains the upper triangular part * of the symmetric matrix A, packed sequentially, column by column; * that is, if i <= j, then A[i,j] is stored is AP[i+(j*(j+1)/2)]. If * uplo == 'L' or 'L', the array AP contains the lower triangular part * of the symmetric matrix A, packed sequentially, column by column; * that is, if i >= j, then A[i,j] is stored in AP[i+((2*n-j+1)*j)/2]. * * Output * ------ * A updated according to A = alpha * x * transpose(x) + A * * Reference: http://www.netlib.org/blas/sspr.f * * Error status for this function can be retrieved via cublasGetError(). * * Error Status * ------------ * CUBLAS_STATUS_NOT_INITIALIZED if CUBLAS library has not been initialized * CUBLAS_STATUS_INVALID_VALUE if n < 0, or incx == 0 * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU */__host__ void CUBLASAPI cublasSspr (char uplo, int n, float alpha, const float *x, int incx, float *AP){ struct cublasContext *ctx = CUBLAS_GET_CTX(); struct cublasSsprParams params; cudaError_t cudaStat; int up; int info = 0; dim3 ctaDims(CUBLAS_SSPR_GRIDW, CUBLAS_SSPR_GRIDH); if (!cublasInitialized (ctx)) { cublasSetError (ctx, CUBLAS_STATUS_NOT_INITIALIZED); return; } up = toupper(uplo) == 'U'; info = 0; if ((!up) && (toupper (uplo) != 'L')) { info = 1; } else if (n < 0) { info = 2; } else if (incx == 0) { info = 5; } if (info) { cublasXerbla ("SSPR ", info); cublasSetError (ctx, CUBLAS_STATUS_INVALID_VALUE); return; } /* early out if nothing to do */ if ((n == 0) || (alpha == 0.0f)) { return; } memset (¶ms, 0, sizeof(params)); params.up = up; params.n = n; params.alpha = alpha; params.AP = AP; params.x = x; params.incx = incx; cudaStat = cudaGetLastError(); /* clear error status */ if (params.up) { sspr_up_main<<<ctaDims,CUBLAS_SSPR_THREAD_COUNT>>>(params); } else { sspr_lo_main<<<ctaDims,CUBLAS_SSPR_THREAD_COUNT>>>(params); } cudaStat = cudaGetLastError(); /* check for launch error */ if (cudaStat != cudaSuccess) { cublasSetError (ctx, CUBLAS_STATUS_EXECUTION_FAILED); }}/* column-major ordering */#undef IDXX#define IDXX(i) (startx + ((i) * parms.incx))#define BLK_LOG (5)#define BLK (1 << BLK_LOG)#define ELEMS_PER_THREAD ((BLK*BLK)/CUBLAS_SSPR_THREAD_COUNT)#define IIINC (BLK)#define JJINC (BLK)#define IINC (IIINC*CUBLAS_SSPR_GRIDH)#define JINC (JJINC*CUBLAS_SSPR_GRIDW)#define A_NBR_COLS (CUBLAS_SSPR_THREAD_COUNT/IIINC)#if (BLK & (BLK - 1))#error tile dimension must be a power of two#endif#if (CUBLAS_SSPR_THREAD_COUNT < BLK)#error thread count must be greater than or equal to tile dimension#endif#if ((BLK*BLK)%CUBLAS_SSPR_THREAD_COUNT)#error number of tile elements must be integral multiple of thread count#endif#if (CUBLAS_SSPR_THREAD_COUNT%IIINC)#error thread count must be integral multple of tile dimension#endif__shared__ float xi[IINC];__shared__ float xj[IINC];__global__ void sspr_up_main (struct cublasSsprParams parms) {#undef LOWER#define LOWER 0#include "sspr.h"}__global__ void sspr_lo_main (struct cublasSsprParams parms){#undef LOWER#define LOWER 1#include "sspr.h"}
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