不能使用CHOLMOD与CUDA加速在我自己的代码

Question

我试图在SuiteSparse 4.4.4中使用CUDA加速的CHOLMOD。我根据用户指南编译了它，我可以在Demo文件夹下成功运行gpu.sh，这表明GPU正在做部分工作。然而，当我尝试使用CHOLMOD运行我自己的代码时，我发现GPU调用的数量总是0。我将Common->useGPU设置为1，环境变量CHOLMOD_USE_GPU也设置为1。我的Makefile如下所示。库路径正确。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解决一个线性系统。

我从UF稀疏矩阵集合中尝试了几个矩阵，但nvprof显示没有CUDA应用程序被分析。

我尝试过的一些矩阵:

bmw7st_1: http://www.cise.ufl.edu/research/sparse/matrices/li_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 msn", 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) ;
}

Makefile:

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

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

只有长整数版本的CHOLMOD可以使用GPU加速。

长整数版本由api调用cholmod_l_start而不是cholmod_start来区分。

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 msn", 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GPU正在使用