gemm.cpp 4.83 KB
Newer Older
Chao Liu's avatar
Chao Liu committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
#include <cstring>

#include "ck/utility/common_header.hpp"
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
#include "ck/tensor_description/cluster_descriptor.hpp"
#include "ck/tensor/tensor_view.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/host_utility/device_prop.hpp"

#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/fill.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"

#include "reference_gemm.hpp"
#include "gemm.hpp"

// elementwise lambda
struct AElementFunction
{
    template <typename X>
    __host__ __device__ auto operator()(const X& x) const
    {
        return x;
    }
};

struct BElementFunction
{
    template <typename X>
    __host__ __device__ auto operator()(const X& x) const
    {
        return x;
    }
};

struct CElementFunction
{
    template <typename X>
    __host__ __device__ auto operator()(const X& x) const
    {
        return x;
    }
};

int main(int argc, char* argv[])
{
    using ADataType   = ck::half_t;
    using BDataType   = ck::half_t;
    using AccDataType = float;
    using CDataType   = ck::half_t;

    ck::index_t M = 3328;
    ck::index_t N = 4096;
    ck::index_t K = 4096;

    if(argc == 4)
    {
        M = std::stoi(argv[1]);
        N = std::stoi(argv[2]);
        K = std::stoi(argv[3]);
    }

    std::array<ck::index_t, 2> a_lengths{M, K};
    std::array<ck::index_t, 2> a_strides{K, 1};

    std::array<ck::index_t, 2> b_lengths{N, K};
    std::array<ck::index_t, 2> b_strides{K, 1};

    std::array<ck::index_t, 2> c_lengths{M, N};
    std::array<ck::index_t, 2> c_strides{N, 1};

    // host verify
    Tensor<ADataType> a_host(a_lengths, a_strides);
    Tensor<BDataType> b_host(b_lengths, b_strides);
    Tensor<CDataType> c_host_ref(c_lengths, c_strides);
    Tensor<CDataType> c_host_dev(c_lengths, c_strides);

    ck::utils::FillUniformDistributionIntegerValue<ADataType>{-5.f, 5.f}(a_host);
    ck::utils::FillUniformDistributionIntegerValue<BDataType>{-5.f, 5.f}(b_host);

    // reference gemm
    reference_gemm<ADataType, ADataType, CDataType, float>(a_host, b_host, c_host_ref);

    DeviceMem a_buf(sizeof(ADataType) * a_host.GetElementSpaceSize());
    DeviceMem b_buf(sizeof(BDataType) * b_host.GetElementSpaceSize());
    DeviceMem c_buf(sizeof(CDataType) * c_host_dev.GetElementSpaceSize());

    a_buf.ToDevice(a_host.mData.data());
    b_buf.ToDevice(b_host.mData.data());

    constexpr ck::index_t kGemmMPerBlock = 256;
    constexpr ck::index_t kGemmNPerBlock = 128;
    constexpr ck::index_t kGemmKPerBlock = 32;

    constexpr ck::index_t kBlockSize = 256;
    ck::index_t kGridSize            = (M / kGemmMPerBlock) * (N / kGemmNPerBlock);

    std::cout << "grid size " << kGridSize << std::endl;

    const auto gemm_kernel = Gemm<ADataType,
                                  BDataType,
                                  AccDataType,
                                  CDataType,
                                  ck::tensor_layout::gemm::RowMajor,
                                  ck::tensor_layout::gemm::ColumnMajor,
                                  ck::tensor_layout::gemm::RowMajor,
                                  AElementFunction,
                                  BElementFunction,
                                  CElementFunction,
                                  kBlockSize,
                                  kGemmMPerBlock,
                                  kGemmNPerBlock,
                                  kGemmKPerBlock>{};

    float ave_time = launch(ProgramServer{},
                            gemm_kernel,
                            kGridSize,
                            kBlockSize,
                            static_cast<ADataType*>(a_buf.GetDeviceBuffer()),
                            static_cast<BDataType*>(b_buf.GetDeviceBuffer()),
                            static_cast<CDataType*>(c_buf.GetDeviceBuffer()),
                            M,
                            N,
                            K,
                            K,
                            K,
                            N,
                            AElementFunction{},
                            BElementFunction{},
                            CElementFunction{});

    c_buf.FromDevice(c_host_dev.mData.data());

    std::size_t flop = std::size_t(2) * M * N * K;
    std::size_t num_btype =
        sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(CDataType) * M * N;

    float tflops = static_cast<float>(flop) / 1.E9 / ave_time;

    float gb_per_sec = num_btype / 1.E6 / ave_time;

    std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
              << std::endl;

    return !ck::utils::check_err(c_host_dev, c_host_ref);
}