megenginelite-sys 1.8.2

A safe megenginelite wrapper in Rust
Documentation 
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
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177

/**
 * \file dnn/src/x86/matrix_mul/algos.h
 * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
 *
 * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
 * implied.
 */

#pragma once

#include "src/fallback/matrix_mul/gemm_common.h"
#include "src/x86/matrix_mul/opr_impl.h"

namespace megdnn {
namespace x86 {

class MatrixMulImpl::AlgoF32Blas : public AlgoBase {
public:
    const char* name() const override { return "X86_F32_BLAS"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override { return 0; }
    kern_t get_kern(const KernSizeParam&) const override;
    AlgoAttribute attribute() const override {
        return AlgoAttribute::REPRODUCIBLE | AlgoAttribute::ACCURACY_DEPEND_ON_BATCH;
    }
    PackMode packmode() const override { return PackMode::NO_PACK; }
    MEGDNN_OVERRIDE_MATMUL_DESC(8, 16, 1, 4, AlgoDataType::FLOAT32, DEFAULT)
    MEGDNN_DECL_ALGO_TYPE(X86_F32_BLAS)
};

#if MEGDNN_X86_WITH_MKL && SUPPORT_MKL_PACKED_GEMM
class MatrixMulImpl::AlgoF32MKLPackA : public AlgoBase {
public:
    AlgoAttribute attribute() const override {
        return AlgoAttribute::REPRODUCIBLE | AlgoAttribute::ACCURACY_DEPEND_ON_BATCH;
    }
    const char* name() const override { return "X86_F32_MKL_PACKA"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override { return 0; }
    kern_t get_kern(const KernSizeParam&) const override;
    PackMode packmode() const override { return PackMode::ONLY_PACKA; }
    kern_naked_t get_kern_naked(const KernSizeParam&) const override;
    void pack_A(const KernParam& kern_param, void* out, size_t index, size_t stride)
            const override;
    void pack_B(const KernParam&, void*, size_t, size_t) const override {
        megdnn_assert(0);
    };
    WorkspaceBundle get_bundle(const KernSizeParam& param) const override;
    InnerBlockSize get_inner_block_size() const override { return {8, 16, 1}; };

    MEGDNN_OVERRIDE_MATMUL_DESC(8, 16, 1, 4, AlgoDataType::FLOAT32, DEFAULT)
    MEGDNN_DECL_ALGO_TYPE(X86_F32_MKL_PACKA)
};
#endif

class MatrixMulImpl::AlgoInt8x8x32AVX2M2N4K16 : public AlgoBase {
public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X32_AVX2_2X4X16"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X32_AVX2_2X4X16)
};

class MatrixMulImpl::AlgoInt8x8x32AVX2M4N16K2 : public AlgoBase {
public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X32_AVX2_4X16X2"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X32_AVX2_4X16X2)
};

class MatrixMulImpl::AlgoInt8x8x16AVX2 : public AlgoBase {
private:
    static void gemm_s8s8s16_avx2_4x16x2(const MatrixMulImpl::KernParam& kern_param);

public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X16_AVX2"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    bool preferred(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X16_AVX2)
};

class MatrixMulImpl::AlgoInt8x8x16SSE : public AlgoBase {
private:
    static void gemm_s8s8s16_sse_4x8x2(const MatrixMulImpl::KernParam& kern_param);

public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X16_SSE"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    bool preferred(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X16_SSE)
};

class MatrixMulImpl::AlgoInt8x8x32SSEM4N8K2 : public AlgoBase {
public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X32_SSE_4X8X2"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X32_SSE_4X8X2)
};

class MatrixMulImpl::AlgoF32MK8_8x8 : public AlgoBase {
public:
    AlgoAttribute attribute() const override {
        return AlgoAttribute::REPRODUCIBLE | AlgoAttribute::USABLE_DEPEND_ON_SHAPE;
    }
    const char* name() const override { return "X86_F32MK8_8X8"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    PackMode packmode() const override { return PackMode::NO_PACK; }
    MEGDNN_OVERRIDE_MATMUL_DESC(8, 8, 8, 4, AlgoDataType::FLOAT32, MK8)
    MEGDNN_DECL_ALGO_TYPE(X86_F32_MK8_8X8)
};

class MatrixMulImpl::AlgoFloatAVX2M6N16 : public AlgoBase {
public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_F32_6x16"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_F32_6x16)
};

#if MEGDNN_X86_WITH_VNNI
class MatrixMulImpl::AlgoInt8x8x32Vnni : public AlgoBase {
public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X32_VNNI"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override;
    kern_t get_kern(const KernSizeParam&) const override;
    MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X32_VNNI)
};
#endif

#if MEGDNN_X86_WITH_MKL_DNN
class MatrixMulImpl::AlgoInt8x8x32Mkldnn : public AlgoBase {
public:
    AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
    const char* name() const override { return "X86_INT8X8X32_MKLDNN"; }
    bool usable(const KernSizeParam&) const override;
    size_t get_workspace(const KernSizeParam&) const override { return 0; }
    kern_t get_kern(const KernSizeParam&) const override;
    PackMode packmode() const override { return PackMode::NO_PACK; }
    MEGDNN_OVERRIDE_MATMUL_DESC(8, 16, 1, 2, AlgoDataType::QINT8X8X32, DEFAULT)
    MEGDNN_DECL_ALGO_TYPE(X86_INT8X8X32_MKLDNN)
};
#endif
}  // namespace x86
}  // namespace megdnn

// vim: syntax=cpp.doxygen