Intel MKL函数之 cblas_sgemm、cblas_sgemm_batch

cblas_sgemm

        int m = 40;
        int k = 20;
        int n = 40;
        std::vector<float> a(m*k, 1.0);
        std::vector<float> b(k*n, 1.0);
        std::vector<float> c(m*n, 0.0);

        float alpha = 1.0;
        float beta = 0.0;
        cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
                    m, n, k, alpha,
                    a.data(), k,
                    b.data(), n, beta,
                    c.data(), n);

        std::cout << "a.size(): " << a.size() << std::endl;
        for (int i = 0; i < a.size(); ++i) {
            std::cout << a[i] << " ";
            if ((i + 1) % k == 0)
                std::cout << std::endl;
        }

        std::cout << "b.size(): " << b.size() << std::endl;
        for (int i = 0; i < b.size(); ++i) {
            std::cout << b[i] << " ";
            if ((i + 1) % n == 0)
                std::cout << std::endl;
        }

        std::cout << "c.size(): " << c.size() << std::endl;
        for (int i = 0; i < c.size(); ++i) {
            std::cout << c[i] << " ";
            if ((i + 1) % n == 0)
                std::cout << std::endl;
        }
        std::cout << std::endl;

output:

a.size(): 800 ( 40 * 20 )
1 1 ... 1 1
...
1 1 ... 1 1
b.size(): 800 ( 20 * 40 )
1 1 ... 1 1
...
1 1 ... 1 1
c_array.size(): 1600 (40 * 40)
20 20 ... 20 20
...
20 20 ... 20 20

cblas_sgemm_batch

        int raw_rows = 20;
        int raw_cols = 40;
        std::vector<float> a(raw_rows * raw_cols, 1.0);
        std::vector<float> b(raw_rows * raw_cols, 1.0);
        std::vector<float> c(1600, 0.0);

        #define GRP_COUNT 1
        MKL_INT    m[GRP_COUNT] = {20};
        MKL_INT    k[GRP_COUNT] = {10};
        MKL_INT    n[GRP_COUNT] = {20};

        MKL_INT    lda[GRP_COUNT] = {40};
        MKL_INT    ldb[GRP_COUNT] = {40};
        MKL_INT    ldc[GRP_COUNT] = {80};

        CBLAS_TRANSPOSE    transA[GRP_COUNT] = { CblasNoTrans };
        CBLAS_TRANSPOSE    transB[GRP_COUNT] = { CblasTrans };

        float    alpha[GRP_COUNT] = {1.0};
        float    beta[GRP_COUNT] = {0.0};

        const MKL_INT    size_per_grp[GRP_COUNT] = {4};

        const float *a_array[4], *b_array[4];
        float *c_array[4];
        for (int i = 0; i < 4; ++i) {
            a_array[i] = a.data() + i * 10;
            b_array[i] = b.data() + i * 10;
            c_array[i] = c.data() + i * 20;
        }

        cblas_sgemm_batch (CblasRowMajor, transA, transB,
                m, n, k, alpha,
                a_array, lda,
                b_array, ldb, beta,
                c_array, ldc,
                GRP_COUNT, size_per_grp);

        std::cout << "a.size(): " << a.size() << std::endl;
        for (int i = 0; i < a.size(); ++i) {
            std::cout << a[i] << " ";
            if ((i + 1) % 40 == 0)
                std::cout << std::endl;
        }

        std::cout << "b.size(): " << b.size() << std::endl;
        for (int i = 0; i < b.size(); ++i) {
            std::cout << b[i] << " ";
            if ((i + 1) % 40 == 0)
                std::cout << std::endl;
        }

        std::cout << "c_array.size(): " << 20 * 20 * 4 << std::endl;
        for (int i = 0; i < 1600; ++i) {
            std::cout << c[i] << " ";
            if ((i + 1) % 80 == 0)
                std::cout << std::endl;
        }
        std::cout << std::endl;

output:

a.size(): 800 ( 20 * 40 )
1 1 ... 1 1
...
1 1 ... 1 1
b.size(): 800 ( 20 * 40 )
1 1 ... 1 1
...
1 1 ... 1 1
c_array.size(): 1600 (40 * 40)
10 10 ... 10 10
...
10 10 ... 10 10

        int raw_rows = 20;
        int raw_cols = 40;
        std::vector<float> a(raw_rows * raw_cols, 1.0);
        std::vector<float> b(raw_rows * raw_cols, 1.0);
        std::vector<float> c(400, 0.0);

        #define GRP_COUNT 1
        MKL_INT    m[GRP_COUNT] = {5};
        MKL_INT    k[GRP_COUNT] = {10};
        MKL_INT    n[GRP_COUNT] = {5};

        MKL_INT    lda[GRP_COUNT] = {40};
        MKL_INT    ldb[GRP_COUNT] = {40};
        MKL_INT    ldc[GRP_COUNT] = {20};

        CBLAS_TRANSPOSE    transA[GRP_COUNT] = { CblasNoTrans };
        CBLAS_TRANSPOSE    transB[GRP_COUNT] = { CblasTrans };

        float    alpha[GRP_COUNT] = {1.0};
        float    beta[GRP_COUNT] = {0.0};

        const MKL_INT    size_per_grp[GRP_COUNT] = {16};

        const float *a_array[16], *b_array[16];
        float *c_array[16];
        for (int i = 0; i < 4; ++i) {
            for (int j = 0; j < 4; ++j) {
                a_array[i*4+j] = a.data() + i * 5 * 40 + j * 10;
                b_array[i*4+j] = b.data() + i * 5 * 40 + j * 10;
                c_array[i*4+j] = c.data() + i * 5 * 20 + j * 5;
            }
        }

        cblas_sgemm_batch (CblasRowMajor, transA, transB,
                m, n, k, alpha,
                a_array, lda,
                b_array, ldb, beta,
                c_array, ldc,
                GRP_COUNT, size_per_grp);

        std::cout << "a.size(): " << a.size() << std::endl;
        for (int i = 0; i < a.size(); ++i) {
            std::cout << a[i] << " ";
            if ((i + 1) % 40 == 0)
                std::cout << std::endl;
        }

        std::cout << "b.size(): " << b.size() << std::endl;
        for (int i = 0; i < b.size(); ++i) {
            std::cout << b[i] << " ";
            if ((i + 1) % 40 == 0)
                std::cout << std::endl;
        }

        std::cout << "c_array.size(): " << 5 *5 * 16 << std::endl;
        for (int i = 0; i < 400; ++i) {
            std::cout << c[i] << " ";
            if ((i + 1) % 20 == 0)
                std::cout << std::endl;
        }
        std::cout << std::endl;

output:

a.size(): 800 ( 20 * 40 )
1 1 ... 1 1
...
1 1 ... 1 1
b.size(): 800 ( 20 * 40 )
1 1 ... 1 1
...
1 1 ... 1 1
c_array.size(): 400 (20 * 20)
10 10 ... 10 10
...
10 10 ... 10 10