无法在我自己的代码中使用 CHOLMOD 和 CUDA 加速

Question

我正在尝试在 SuiteSparse 4.4.4 中使用 CHOLMOD 和 CUDA 加速。我按照用户指南编译，可以成功运行Demo文件夹下的gpu.sh，这说明GPU已经完成了部分工作。但是，当我尝试使用 CHOLMOD 运行自己的代码时，我发现 GPU 调用次数始终为 0。我确实将 Common->useGPU 设置为 1，并且环境变量 CHOLMOD_USE_GPU 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？

实际上我应该提到我只是运行一个最简单的测试用例来求解线性系统。

我尝试了几个来自 UF 稀疏矩阵集合的矩阵，但是 nvprof 显示没有分析 CUDA 应用程序。

我试过的一些矩阵:

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)

Answer 1

引用 SuiteSparse 4.4.4 附带的 CHOLMOD UserGuide.pdf 的第 7 节，第 34 页:

Only the long integer version of CHOLMOD can leverage GPU acceleration.

长整数版本的区别在于像 cholmod_l_start 而不是 cholmod_start 这样的 API 调用。

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。