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我正在尝试CHOLMOD在. 我按照用户指南编译，可以在文件夹下成功运行，说明GPU在做部分工作。但是，当我尝试使用 运行自己的代码时，发现 GPU 调用的次数始终为 0。我确实设置为 1，环境变量也设置为 1。我的 Makefile 如下所示。库路径是正确的。对我有什么建议吗？CUDASuiteSparse 4.4.4gpu.shDemoCHOLMODCommon->useGPUCHOLMOD_USE_GPU

实际上我应该提到我只是在运行一个最简单的测试用例来解决线性系统。

我尝试了 UF Sparse Matrix Collection 中的几个矩阵，但nvprof显示没有CUDA分析任何应用程序。

我尝试过的一些矩阵：

bmw7st_1：http ://www.cise.ufl.edu/research/sparse/matrices/GHS_psdef/bmw7st_1.html

nd6k： http ://www.cise.ufl.edu/research/sparse/matrices/ND/nd6k.html

nd24k： http ://www.cise.ufl.edu/research/sparse/matrices/ND/nd24k.html

代码：

#include <stdio.h>
#include <time.h>
#include <unistd.h>
#include <assert.h>
#include <sys/time.h>
#include "cholmod.h"

int main (void)
{
    struct timeval t1, t2;
    double elapsedTime;

    const char* matFile = "../bmw7st_1.mtx";
    FILE* fp = fopen(matFile, "r");
    assert(fp != NULL);

    cholmod_sparse *A ;
    cholmod_dense *x, *b;
    cholmod_factor *L ;

    cholmod_common* c = (cholmod_common*)malloc(sizeof(cholmod_common));
    cholmod_start (c) ; /* start CHOLMOD */
    c->useGPU = 1;
    c->supernodal = CHOLMOD_SUPERNODAL;

    A = cholmod_read_sparse (fp, c) ; /* read in a matrix */
    cholmod_print_sparse (A, "A", c) ; /* print the matrix */
    fclose(fp);

    if (A == NULL || A->stype == 0) /* A must be symmetric */
    {
        cholmod_free_sparse (&A, c) ;
        cholmod_finish (c) ;
        return (0) ;
    }

    b = cholmod_ones (A->nrow, 1, A->xtype, c) ; /* b = ones(n,1) */

    gettimeofday(&t1, NULL);
    L = cholmod_analyze (A, c) ; /* analyze */
    cholmod_factorize (A, L, c) ; /* factorize */
    x = cholmod_solve (CHOLMOD_A, L, b, c) ; /* solve Ax=b */
    gettimeofday(&t2, NULL);
    elapsedTime = (t2.tv_sec - t1.tv_sec) * 1000.0;
    elapsedTime += (t2.tv_usec - t1.tv_usec) / 1000.0;
    printf("Time: %.4f ms\n", elapsedTime);

    cholmod_free_factor (&L, c) ; /* free matrices */
    cholmod_free_sparse (&A, c) ;
    cholmod_free_dense (&x, c) ;
    cholmod_free_dense (&b, c) ;
    cholmod_finish (c) ; /* finish CHOLMOD */
    return (0) ;
}

生成文件：

CC = gcc

CFLAGS = -g -Wall -O2 \
-lrt -lgfortran \
-gdwarf-2

LIBS = $(CHOLMOD)/Lib/libcholmod.a \
$(AMD)/Lib/libamd.a \
$(COLAMD)/Lib/libcolamd.a \
$(LAPACK)/liblapack.a \
$(OPENBLAS)/lib/libopenblas.so \
$(XERBLA)/libcerbla.a \
$(METIS)/libmetis.a \
$(CAMD)/Lib/libcamd.a \
$(CCOLAMD)/Lib/libccolamd.a \
$(SUITESPARSE)/SuiteSparse_config/libsuitesparseconfig.a \
$(CUDART_LIB) \
$(CUBLAS_LIB)

HEADER_DIR = $(CHOLMOD)/Include
CONFIG_HEADER_DIR = $(SUITESPARSE)/SuiteSparse_config

OBJ_DIR = .

BIN_DIR = .

INCLUDES = -I$(HEADER_DIR) \
-I$(CONFIG_HEADER_DIR)

SRCS = $(shell ls *.c)

OBJS = $(SRCS:.c=.o)

OBJS_BUILD = $(shell ls $(OBJ_DIR)/*.o)

APP = prog

RM = rm -f

all: $(APP)

$(APP): $(OBJS)
        $(CC) $(CFLAGS) -o $(BIN_DIR)/$(APP) $(OBJS_BUILD) $(LIBS)

%.o: %.c $(HEADER_DIR)/*.h $(CONFIG_HEADER_DIR)/*.h
        $(CC) $(CFLAGS) $(INCLUDES) -c $< -o $(OBJ_DIR)/$@

clean:
        $(RM) $(OBJS_BUILD) $(APP)
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1 回答 1

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参考 SuiteSparse 4.4.4 附带的 CHOLMOD UserGuide.pdf 的第 7 节 p34：

只有 CHOLMOD 的长整数版本可以利用 GPU 加速。

长整数版本通过 api 调用来区分，cholmod_l_start而不是cholmod_start.

对您的程序进行以下修改：

#include <stdio.h>
#include <time.h>
#include <unistd.h>
#include <assert.h>
#include <sys/time.h>
#include "cholmod.h"

int main (void)
{
    struct timeval t1, t2;
    double elapsedTime;

    const char* matFile = "../Matrix/nd6k/nd6k.mtx";
    FILE* fp = fopen(matFile, "r");
    assert(fp != NULL);

    cholmod_sparse *A ;
    cholmod_dense *x, *b;
    cholmod_factor *L ;

    cholmod_common* c = (cholmod_common*)malloc(sizeof(cholmod_common));
    cholmod_l_start (c) ; /* start CHOLMOD */
    c->useGPU = 1;
    c->supernodal = CHOLMOD_SUPERNODAL;

    A = cholmod_l_read_sparse (fp, c) ; /* read in a matrix */
    cholmod_l_print_sparse (A, "A", c) ; /* print the matrix */
    fclose(fp);

    if (A == NULL || A->stype == 0) /* A must be symmetric */
    {
        cholmod_l_free_sparse (&A, c) ;
        cholmod_l_finish (c) ;
        return (0) ;
    }

    b = cholmod_l_ones (A->nrow, 1, A->xtype, c) ; /* b = ones(n,1) */

    gettimeofday(&t1, NULL);
    L = cholmod_l_analyze (A, c) ; /* analyze */
    cholmod_l_factorize (A, L, c) ; /* factorize */
    x = cholmod_l_solve (CHOLMOD_A, L, b, c) ; /* solve Ax=b */
    gettimeofday(&t2, NULL);
    elapsedTime = (t2.tv_sec - t1.tv_sec) * 1000.0;
    elapsedTime += (t2.tv_usec - t1.tv_usec) / 1000.0;
    printf("Time: %.4f ms\n", elapsedTime);
    cholmod_l_gpu_stats(c);
    cholmod_l_free_factor (&L, c) ; /* free matrices */
    cholmod_l_free_sparse (&A, c) ;
    cholmod_l_free_dense (&x, c) ;
    cholmod_l_free_dense (&b, c) ;
    cholmod_l_finish (c) ; /* finish CHOLMOD */
    return (0) ;
}

我得到这样的输出：

$ ./prog
CHOLMOD sparse:  A:  18000-by-18000, nz 3457658, upper.  OK
Time: 14570.3950 ms

CHOLMOD GPU/CPU statistics:
SYRK  CPU calls          888 time   1.0637e-01
      GPU calls          213 time   8.9194e-02
GEMM  CPU calls          711 time   1.1511e-01
      GPU calls          213 time   1.9351e-03
POTRF CPU calls          217 time   3.2180e-02
      GPU calls            5 time   1.5788e-01
TRSM  CPU calls          217 time   6.0409e-01
      GPU calls            4 time   5.6943e-02
time in the BLAS: CPU   8.5774e-01 GPU   3.0595e-01 total:   1.1637e+00
assembly time   0.0000e+00    0.0000e+00
$

表示正在使用 GPU。

于 2015-08-14T22:25:52.070 回答