feat(dnn): refactor dot gemv for both aarch64 and aarch32

GitOrigin-RevId: 2b98867e45

dnn/src/aarch64/matrix_mul/algos.cpp

@@ -14,7 +14,6 @@
 #include "src/aarch64/matrix_mul/fp32/strategy.h"
 #include "src/aarch64/matrix_mul/int16/strategy.h"
 #include "src/aarch64/matrix_mul/int8/strategy.h"
-#include "src/aarch64/matrix_mul/int8_dot/gemv.h"
 #include "src/aarch64/matrix_mul/int8_dot/strategy.h"
 #include "src/aarch64/matrix_mul/int8x8x16/strategy.h"
 #include "src/aarch64/matrix_mul/quint8/strategy.h"
@@ -441,39 +440,6 @@ MEGDNN_REG_GEMM_FUNC_FOR_IM2COL_IMPL(AlgoInt8x8x32K8x12x4DotProd,
                                      "AlgoInt8x8x32K8x12x4DotProdImpl"_hash,
                                      aarch64::matmul::gemm_s8_8x12, int8_t,
                                      int32_t);
-/* ===================== Int8x8x32 Gemv DotProd algo ===================== */
-namespace {
-void int8x8x32_gemv_dotprod_kern(const MatrixMulImpl::KernParam& kern_param) {
-    auto M = kern_param.M, N = kern_param.N, K = kern_param.K;
-    auto LDA = kern_param.LDA, LDB = kern_param.LDB, LDC = kern_param.LDC;
-    const auto Aptr = kern_param.A<dt_int8>(), Bptr = kern_param.B<dt_int8>();
-    auto Cptr = kern_param.C<dt_int32>();
-    aarch64::matmul::gemv_like_int8(Aptr, Bptr, Cptr, M, N, K, LDA, LDB, LDC);
-}
-}  // anonymous namespace
-
-bool MatrixMulImpl::AlgoInt8x8x32GemvDotProd::usable(
-        const KernSizeParam& kern_size_param) const {
-    return can_be_treated_as_int8x8x32(kern_size_param) &&
-           !kern_size_param.trA && !kern_size_param.trB &&
-           kern_size_param.N == 1 && kern_size_param.LDB == 1;
-}
-
-bool MatrixMulImpl::AlgoInt8x8x32GemvDotProd::preferred(
-        const KernSizeParam& kern_size_param) const {
-    auto N = kern_size_param.N, LDB = kern_size_param.LDB;
-    return (N == 1 && LDB == 1);
-}
-
-MatrixMulImpl::kern_t MatrixMulImpl::AlgoInt8x8x32GemvDotProd::get_kern(
-        const KernSizeParam&) const {
-    MIDOUT_BEGIN(megdnn_aarch64_matmul_kern,
-                 midout_iv("AlgoInt8x8x32GemvDotProd::get_kern"_hash)) {
-        return int8x8x32_gemv_dotprod_kern;
-    }
-    MIDOUT_END();
-    return nullptr;
-}
 
 /* =================== Int8x8x32 MK4 8X12X4 Dotprod algo =================== */
 namespace {

dnn/src/aarch64/matrix_mul/algos.h

@@ -104,21 +104,6 @@ public:
     MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
 };
 
-class MatrixMulImpl::AlgoInt8x8x32GemvDotProd final : public AlgoBase {
-public:
-    bool is_reproducible() const override { return true; }
-    const char* name() const override {
-        return "AARCH64_INT8X8X32_GEMV_DOTPROD";
-    }
-    bool usable(const KernSizeParam&) const override;
-    bool preferred(const KernSizeParam&) const override;
-    size_t get_workspace(const KernSizeParam&) const override { return 0; }
-    kern_t get_kern(const KernSizeParam&) const override;
-    void* type() const override { return sm_arm_common_algo_type; }
-    AlgoSet algoset() const override { return AlgoSet::ALGO_TYPE_GEMV; }
-    PackMode packmode() const override { return PackMode::NO_PACK; }
-};
-
 class MatrixMulImpl::AlgoInt8x8x32MK4_8x12x4DotProd final : public AlgoBase {
 public:
     bool is_reproducible() const override { return true; }
@@ -174,10 +159,6 @@ public:
     void* type() const override { return sm_arm_common_algo_type; }
     MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
 };
-
-class MatrixMulImpl::AlgoInt8x8x32Gemv final
-        : public arm_common::MatrixMulImpl::AlgoInt8x8x32Gemv {};
-
 #endif
 
 class MatrixMulImpl::AlgoInt8x8x16K8x8x8 final : public AlgoBase {

dnn/src/aarch64/matrix_mul/int8_dot/gemv.cpp

@@ -1,116 +0,0 @@
-/**
- * \file dnn/src/aarch64/matrix_mul/int8_dot/gemv.cpp
- * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
- *
- * Copyright (c) 2014-2020 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.
- */
-
-#include "src/aarch64/matrix_mul/int8_dot/gemv.h"
-#include <cstddef>
-#include "src/arm_common/simd_macro/marm_neon.h"
-#include "src/common/utils.h"
-#include "src/common/unroll_macro.h"
-
-#if __ARM_FEATURE_DOTPROD
-
-namespace {
-
-void gemv_naive_n(const int8_t* __restrict A, const int8_t* __restrict B,
-                  int32_t* __restrict C, size_t M, size_t N, size_t K,
-                  size_t Astride, size_t Bstride, size_t Cstride) {
-    megdnn_assert(N == 1 && Bstride == 1);
-    size_t m = 0;
-    for (; m + 2 <= M; m += 2) {
-        int32_t acc[4];
-        int32x4_t acc_neon = vdupq_n_s32(0);
-        size_t k = 0;
-        for (; k + 16 <= K; k += 16) {
-            int64x2_t a0 = vreinterpretq_s64_s8(vld1q_s8(A + m * Astride + k));
-            int64x2_t a1 =
-                    vreinterpretq_s64_s8(vld1q_s8(A + (m + 1) * Astride + k));
-            //! the first 8 elements is m, the last 8 elements is m + 1
-            int8x16_t a2 = vreinterpretq_s8_s64(vzip1q_s64(a0, a1));
-            int8x16_t a3 = vreinterpretq_s8_s64(vzip2q_s64(a0, a1));
-
-            int64x2_t b0 = vreinterpretq_s64_s8(vld1q_s8(B + k));
-            int8x16_t b2 = vreinterpretq_s8_s64(vzip1q_s64(b0, b0));
-            int8x16_t b3 = vreinterpretq_s8_s64(vzip2q_s64(b0, b0));
-
-            acc_neon = vdotq_s32(acc_neon, a2, b2);
-            acc_neon = vdotq_s32(acc_neon, a3, b3);
-        }
-        vst1q_s32(acc, acc_neon);
-
-        for (; k + 8 <= K; k += 8) {
-            int8x8_t a0 = vld1_s8(A + m * Astride + k);
-            int8x8_t a1 = vld1_s8(A + (m + 1) * Astride + k);
-            int8x8_t b0 = vld1_s8(B + k);
-            uint32x2_t zero = vdup_n_s32(0);
-            acc[0] += vaddv_s32(vdot_s32(zero, a0, b0));
-            zero = vdup_n_s32(0);
-            acc[3] += vaddv_s32(vdot_s32(zero, a1, b0));
-        }
-
-        for (; k < K; ++k) {
-            acc[0] += static_cast<int32_t>(A[m * Astride + k]) * B[k];
-            acc[3] += static_cast<int32_t>(A[(m + 1) * Astride + k]) * B[k];
-        }
-        C[m * Cstride] = acc[0] + acc[1];
-        C[(m + 1) * Cstride] = acc[2] + acc[3];
-    }
-
-    for (; m < M; ++m) {
-        int32_t acc[4];
-        int32x4_t acc_neon = vdupq_n_s32(0);
-        size_t k = 0;
-        for (; k + 16 <= K; k += 16) {
-            int8x16_t a0 = vld1q_s8(A + m * Astride + k);
-            int8x16_t b0 = vld1q_s8(B + k);
-            acc_neon = vdotq_s32(acc_neon, a0, b0);
-        }
-        vst1q_s32(acc, acc_neon);
-
-        for (; k + 8 <= K; k += 8) {
-            int8x8_t a0 = vld1_s8(A + m * Astride + k);
-            int8x8_t b0 = vld1_s8(B + k);
-            uint32x2_t zero = vdup_n_s32(0);
-            acc[0] += vaddv_s32(vdot_s32(zero, a0, b0));
-        }
-
-        for (; k < K; ++k) {
-            acc[0] += static_cast<int32_t>(A[m * Astride + k]) * B[k];
-        }
-        C[m * Cstride] = acc[0] + acc[1] + acc[2] + acc[3];
-    }
-}
-
-}  // namespace
-
-bool megdnn::aarch64::matmul::is_gemv_like_preferred_int8(
-        bool transposeA, bool transposeB, size_t M, size_t N, size_t K,
-        size_t /* LDA */, size_t LDB, size_t /* LDC */) {
-    if (transposeA)
-        return false;
-    if (transposeB)
-        return false;
-    MEGDNN_MARK_USED_VAR(K);
-    MEGDNN_MARK_USED_VAR(M);
-    return (N == 1 && LDB == 1);
-}
-
-void megdnn::aarch64::matmul::gemv_like_int8(const int8_t* __restrict A,
-                                             const int8_t* __restrict B,
-                                             int32_t* __restrict C, size_t M,
-                                             size_t N, size_t K, size_t Astride,
-                                             size_t Bstride, size_t Cstride) {
-    megdnn_assert(N == 1);
-    return gemv_naive_n(A, B, C, M, N, K, Astride, Bstride, Cstride);
-}
-
-#endif
-
-// vim: syntax=cpp.doxygen

dnn/src/aarch64/matrix_mul/int8_dot/gemv.h

@@ -1,34 +0,0 @@
-/**
- * \file dnn/src/aarch64/matrix_mul/int8_dot/gemv.h
- * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
- *
- * Copyright (c) 2014-2020 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 <cstddef>
-#include <cstdint>
-
-#if __ARM_FEATURE_DOTPROD
-namespace megdnn {
-namespace aarch64 {
-namespace matmul {
-
-bool is_gemv_like_preferred_int8(bool transposeA, bool transposeB, size_t M,
-                                 size_t N, size_t K, size_t LDA, size_t LDB,
-                                 size_t LDC);
-
-void gemv_like_int8(const int8_t* __restrict A, const int8_t* __restrict B,
-                    int32_t* __restrict C, size_t M, size_t N, size_t K,
-                    size_t Astride, size_t Bstride, size_t Cstride);
-
-}  // namespace matmul
-}  // namespace aarch64
-}  // namespace megdnn
-#endif
-
-// vim: syntax=cpp.doxygen

dnn/src/aarch64/matrix_mul/opr_impl.cpp

@@ -28,13 +28,11 @@ class MatrixMulImpl::AlgoPack : NonCopyableObj {
 #endif
 #if __ARM_FEATURE_DOTPROD
     AlgoInt8x8x32K8x12x4DotProd int8x8x32_k8x12x4_dotprod;
-    AlgoInt8x8x32GemvDotProd int8x8x32_gemv_dotprod;
     AlgoInt8x8x32MK4_8x12x4DotProd int8x8x32_mk4_8x12x4_dotprod;
 #else
     AlgoInt8x8x32MK4_4x4x16 int8x8x32_mk4_4x4x16;
     AlgoInt8x8x32K4x4x16 int8x8x32_k4x4x16;
     AlgoInt8x8x32K8x8x8 int8x8x32_k8x8x8;
-    AlgoInt8x8x32Gemv int8x8x32_gemv;
 #endif
     AlgoInt8x8x16K8x8x8 int8x8x16_k8x8x8;
     AlgoInt8x8x16K4x4x16 int8x8x16_k4x4x16;
@@ -63,11 +61,9 @@ public:
         all_algos.emplace_back(&f16_mk8_8x8);
 #endif
 #if __ARM_FEATURE_DOTPROD
-        all_algos.emplace_back(&int8x8x32_gemv_dotprod);
         all_algos.emplace_back(&int8x8x32_k8x12x4_dotprod);
         all_algos.emplace_back(&int8x8x32_mk4_8x12x4_dotprod);
 #else
-        all_algos.emplace_back(&int8x8x32_gemv);
         all_algos.emplace_back(&int8x8x32_k4x4x16);
         all_algos.emplace_back(&int8x8x32_k8x8x8);
         all_algos.emplace_back(&int8x8x32_mk4_4x4x16);

dnn/src/aarch64/matrix_mul/opr_impl.h

@@ -34,14 +34,12 @@ private:
 #if __ARM_FEATURE_DOTPROD
     class AlgoInt8x8x32K8x12x4DotProd;  // Aarch64 Int8x8x32 Kernel
                                         // 8x12x4 DotProduct
-    class AlgoInt8x8x32GemvDotProd;     // Aarch64 Int8x8x32 Gemv DotProduct
     class AlgoInt8x8x32MK4_8x12x4DotProd; // Aarch64 nchw44 Int8x8x32 Kernel
                                           // 8x12x4 DotProduct
 #else
     class AlgoInt8x8x32MK4_4x4x16;  // Aarch64 nchw44 Int8x8x32 Kernel 4x4x16
     class AlgoInt8x8x32K4x4x16;  // Aarch64 Int8x8x32 Kernel 4x4x16
     class AlgoInt8x8x32K8x8x8;   // Aarch64 Int8x8x32 Kernel 8x8x8
-    class AlgoInt8x8x32Gemv;     // Aarch64 Int8x8x32 Gemv
 #endif
     class AlgoInt8x8x16K8x8x8;   // Aarch64 Int8x8x16 Kernel 8x8x8
     class AlgoInt8x8x16K4x4x16;  // Aarch64 Int8x8x16 Kernel 4x4x16

dnn/src/arm_common/matrix_mul/algos.cpp

@@ -72,7 +72,6 @@ MatrixMulImpl::kern_t MatrixMulImpl::AlgoInt8x8x16::get_kern(
     return exec_int_8x8x16;
 }
 
-#if !__ARM_FEATURE_DOTPROD
 /* ===================== Int8x8x32 Gemv algo ===================== */
 namespace {
 void int8x8x32_gemv_kern(const MatrixMulImpl::KernParam& kern_param) {
@@ -102,7 +101,6 @@ MatrixMulImpl::kern_t MatrixMulImpl::AlgoInt8x8x32Gemv::get_kern(
         const KernSizeParam&) const {
     return int8x8x32_gemv_kern;
 }
-#endif
 
 /* ===================== F32 Gemv algo ===================== */
 namespace {
@@ -112,7 +110,6 @@ void f32_gemv_kern(const MatrixMulImpl::KernParam& kern_param) {
     const auto Aptr = kern_param.A<dt_float32>(),
                Bptr = kern_param.B<dt_float32>();
     auto Cptr = kern_param.C<dt_float32>();
-
     arm_common::sgemm_sgemv_like(Aptr, Bptr, Cptr, M, N, K, LDA, LDB, LDC);
 }
 }  // anonymous namespace

dnn/src/arm_common/matrix_mul/algos.h

@@ -27,11 +27,7 @@ public:
     PackMode packmode() const override { return PackMode::NO_PACK; }
 };
 
-#if !__ARM_FEATURE_DOTPROD
 class MatrixMulImpl::AlgoInt8x8x32Gemv : public AlgoBase {
-protected:
-    ~AlgoInt8x8x32Gemv() = default;
-
 public:
     bool is_reproducible() const override { return true; }
     const char* name() const override { return "ARM_COMMON_INT8X8X32_GEMV"; }
@@ -43,7 +39,6 @@ public:
     AlgoSet algoset() const override { return AlgoSet::ALGO_TYPE_GEMV; }
     PackMode packmode() const override { return PackMode::NO_PACK; }
 };
-#endif
 
 class MatrixMulImpl::AlgoF32Gemv : public AlgoBase {
 protected:

dnn/src/arm_common/matrix_mul/int8/gemv.cpp

@@ -9,8 +9,6 @@
  * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  */
 
-#if !__ARM_FEATURE_DOTPROD
-
 #include <cstddef>
 #include "src/arm_common/matrix_mul/int8/gemv.h"
 #include "src/arm_common/simd_macro/marm_neon.h"
@@ -23,6 +21,8 @@ MIDOUT_DECL(megdnn_arm_common_int8_gemv)
 using namespace megdnn;
 using namespace arm_common;
 
+#if !__ARM_FEATURE_DOTPROD
+
 namespace {
 
 void gemv_naive_n(const int8_t* __restrict A, const int8_t* __restrict B,
@@ -95,8 +95,82 @@ void gemv_naive_n(const int8_t* __restrict A, const int8_t* __restrict B,
         C[m * Cstride] = acc0;
     }
 }
+}  // namespace
+#endif
+
+#if __ARM_FEATURE_DOTPROD
+namespace {
+
+void gemv_naive_n(const int8_t* __restrict A, const int8_t* __restrict B,
+                  int32_t* __restrict C, size_t M, size_t N, size_t K,
+                  size_t Astride, size_t Bstride, size_t Cstride) {
+    megdnn_assert(N == 1 && Bstride == 1);
+    size_t m = 0;
+    for (; m + 2 <= M; m += 2) {
+        int32_t acc[4];
+        int32x4_t acc_neon = vdupq_n_s32(0);
+        size_t k = 0;
+        for (; k + 16 <= K; k += 16) {
+            int64x2_t a0 = vreinterpretq_s64_s8(vld1q_s8(A + m * Astride + k));
+            int64x2_t a1 =
+                    vreinterpretq_s64_s8(vld1q_s8(A + (m + 1) * Astride + k));
+            //! the first 8 elements is m, the last 8 elements is m + 1
+            int8x16_t a2 = vreinterpretq_s8_s64(vzip1q_s64(a0, a1));
+            int8x16_t a3 = vreinterpretq_s8_s64(vzip2q_s64(a0, a1));
+
+            int64x2_t b0 = vreinterpretq_s64_s8(vld1q_s8(B + k));
+            int8x16_t b2 = vreinterpretq_s8_s64(vzip1q_s64(b0, b0));
+            int8x16_t b3 = vreinterpretq_s8_s64(vzip2q_s64(b0, b0));
+
+            acc_neon = vdotq_s32(acc_neon, a2, b2);
+            acc_neon = vdotq_s32(acc_neon, a3, b3);
+        }
+        vst1q_s32(acc, acc_neon);
+
+        for (; k + 8 <= K; k += 8) {
+            int8x8_t a0 = vld1_s8(A + m * Astride + k);
+            int8x8_t a1 = vld1_s8(A + (m + 1) * Astride + k);
+            int8x8_t b0 = vld1_s8(B + k);
+            uint32x2_t zero = vdup_n_s32(0);
+            acc[0] += vaddv_s32(vdot_s32(zero, a0, b0));
+            zero = vdup_n_s32(0);
+            acc[3] += vaddv_s32(vdot_s32(zero, a1, b0));
+        }
+
+        for (; k < K; ++k) {
+            acc[0] += static_cast<int32_t>(A[m * Astride + k]) * B[k];
+            acc[3] += static_cast<int32_t>(A[(m + 1) * Astride + k]) * B[k];
+        }
+        C[m * Cstride] = acc[0] + acc[1];
+        C[(m + 1) * Cstride] = acc[2] + acc[3];
+    }
+
+    for (; m < M; ++m) {
+        int32_t acc[4];
+        int32x4_t acc_neon = vdupq_n_s32(0);
+        size_t k = 0;
+        for (; k + 16 <= K; k += 16) {
+            int8x16_t a0 = vld1q_s8(A + m * Astride + k);
+            int8x16_t b0 = vld1q_s8(B + k);
+            acc_neon = vdotq_s32(acc_neon, a0, b0);
+        }
+        vst1q_s32(acc, acc_neon);
 
+        for (; k + 8 <= K; k += 8) {
+            int8x8_t a0 = vld1_s8(A + m * Astride + k);
+            int8x8_t b0 = vld1_s8(B + k);
+            uint32x2_t zero = vdup_n_s32(0);
+            acc[0] += vaddv_s32(vdot_s32(zero, a0, b0));
+        }
+
+        for (; k < K; ++k) {
+            acc[0] += static_cast<int32_t>(A[m * Astride + k]) * B[k];
+        }
+        C[m * Cstride] = acc[0] + acc[1] + acc[2] + acc[3];
+    }
+}
 }  // namespace
+#endif
 
 bool matmul::is_gemv_like_preferred_int8(bool transposeA, bool transposeB,
                                          size_t M, size_t N, size_t K,
@@ -124,6 +198,5 @@ void matmul::gemv_like_int8(const int8_t* __restrict A,
     } MIDOUT_END();
 }
 
-#endif
 
 // vim: syntax=cpp.doxygen

dnn/src/arm_common/matrix_mul/int8/gemv.h

@@ -13,7 +13,6 @@
 #include <cstddef>
 #include <cstdint>
 
-#if !__ARM_FEATURE_DOTPROD
 namespace megdnn {
 namespace arm_common {
 namespace matmul {
@@ -28,6 +27,6 @@ void gemv_like_int8(const int8_t* __restrict A, const int8_t* __restrict B,
 }  // namespace matmul
 }  // namespace arm_common
 }  // namespace megdnn
-#endif
+
 
 // vim: syntax=cpp.doxygen

dnn/src/arm_common/matrix_mul/opr_impl.cpp

@@ -27,13 +27,14 @@ class MatrixMulImpl::AlgoPack : NonCopyableObj {
 #if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 	AlgoF16Gemv f16gemv;
 #endif
-
+    AlgoInt8x8x32Gemv int8x8x32_gemv; 
 public:
     AlgoPack() {
         all_algos.emplace_back(&int8x8x16);
 #if  __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
         all_algos.emplace_back(&f16gemv);
 #endif
+        all_algos.emplace_back(&int8x8x32_gemv);
  }
     SmallVector<AlgoBase*> all_algos;
 };

dnn/src/arm_common/matrix_mul/opr_impl.h

@@ -25,9 +25,7 @@ public:
 
 protected:
     static void* const sm_arm_common_algo_type;
-#if !__ARM_FEATURE_DOTPROD
     class AlgoInt8x8x32Gemv;  // Arm_common Int 8x8x32 Gemv
-#endif
     class AlgoF32Gemv;        // Arm_common F32 Gemv
 #if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
     class AlgoF16Gemv;

dnn/src/arm_common/simd_macro/marm_neon.h

@@ -388,6 +388,19 @@ __ai int64x2_t vmovl_high_s32(int32x4_t __p0) {
 __ai uint64x2_t vmovl_high_u32(uint32x4_t __p0) {
     return vmovl_u32(vget_high_u32(__p0));
 }
+
+__ai int64x2_t vzip1q_s64(int64x2_t& a, int64x2_t& b) {
+    return vcombine_s64(vget_low_s64(a), vget_low_s64(b));
+}
+
+__ai int64x2_t vzip2q_s64(int64x2_t& a, int64x2_t& b) {
+    return vcombine_s64(vget_high_s64(a), vget_high_s64(b));
+}
+
+__ai int32_t vaddv_s32(int32x2_t a) {
+    return vget_lane_s32(a, 0) + vget_lane_s32(a, 1);
+}
+
 #endif  // MEGDNN_ARMV7
 
 //! pack vmovl_low_xx() on armv7 and armv8

dnn/src/armv7/matrix_mul/algos.h

@@ -134,11 +134,6 @@ public:
     MEGDNN_REG_GEMM_FUNC_FOR_IM2COL();
 };
 
-#if !__ARM_FEATURE_DOTPROD
-class MatrixMulImpl::AlgoInt8x8x32Gemv final
-        : public arm_common::MatrixMulImpl::AlgoInt8x8x32Gemv {};
-#endif
-
 class MatrixMulImpl::AlgoQuint8K4x8x8 final : public AlgoBase {
 public:
     bool is_reproducible() const override { return true; }

dnn/src/armv7/matrix_mul/opr_impl.cpp

@@ -35,9 +35,6 @@ class MatrixMulImpl::AlgoPack : NonCopyableObj {
     AlgoInt8x8x32MK4_4x2x16 int8x8x32_mk4_4x2x16;
     AlgoInt8x8x32K4x2x16 int8x8x32_k4x2x16;
     AlgoInt8x8x32K4x8x8 int8x8x32_k4x8x8;
-#if !__ARM_FEATURE_DOTPROD
-    AlgoInt8x8x32Gemv int8x8x32_gemv;
-#endif
     AlgoQuint8K4x8x8 quint8_k4x8x8;
     AlgoInt8x8x16K4x2x16 int8x8x16_k4x2x16;
     AlgoInt8x8x16K4x8x8 int8x8x16_k4x8x8;
@@ -61,9 +58,6 @@ public:
         all_algos.emplace_back(&int8_k6x8x4);
         all_algos.emplace_back(&quint8_k4x8x4);
 #endif
-#if !__ARM_FEATURE_DOTPROD
-        all_algos.emplace_back(&int8x8x32_gemv);
-#endif
         all_algos.emplace_back(&int8x8x32_mk4_4x2x16);
         all_algos.emplace_back(&int8x8x32_k4x2x16);
         all_algos.emplace_back(&int8x8x32_k4x8x8);

dnn/src/armv7/matrix_mul/opr_impl.h

@@ -27,9 +27,6 @@ private:
     class AlgoInt8x8x32K4x8x8;   // Armv7 Int8x8x32 Kernel 4x8x8
     class AlgoInt8x8x32K4x2x16;  // Armv7 Int8x8x32 Kernel 4x2x16
     class AlgoInt8x8x32MK4_4x2x16;  // Armv7 Int8x8x32 Kernel MK4 4x2x16
-#if !__ARM_FEATURE_DOTPROD
-    class AlgoInt8x8x32Gemv;     // Armv7 Int8x8x32 Gemv
-#endif
     class AlgoQuint8K4x8x8;      // Armv7 Quint8 Kernel 4x8x8
     class AlgoInt8x8x16K4x2x16;  // Armv7 Int8x8x16 Kernel 4x2x16
     class AlgoInt8x8x16K4x8x8;  // Armv7 Int8x8x16 Kernel 4x8x8

dnn/test/arm_common/matrix_mul.cpp

@@ -133,6 +133,36 @@ TEST_F(ARM_COMMON, MATRIX_MUL_FP16_TEST) {
 }
 #endif
 
+TEST_F(ARM_COMMON, QINT8x8x32_GEMV) {
+    Checker<MatrixMul> checker(handle());
+    using Param = MatrixMul::Param;
+
+    checker.set_before_exec_callback(
+            AlgoChecker<MatrixMul>("ARM_COMMON_INT8X8X32_GEMV"));
+
+    std::unique_ptr<RNG> rng = std::make_unique<UniformIntRNG>(-127, 127);
+    checker.set_rng(0, rng.get()).set_rng(1, rng.get());
+
+    auto run = [&](size_t M, size_t K, size_t N) {
+        Param param;
+        param.transposeA = false;
+        param.transposeB = false;
+        TensorShape A, B;
+        A = TensorShape{M, K};
+        B = TensorShape{K, N};
+        checker.set_param(param)
+                .set_dtype(0, dtype::QuantizedS8(2.5f))
+                .set_dtype(1, dtype::QuantizedS8(2.5f))
+                .set_dtype(2, dtype::QuantizedS32(6.25f))
+                .execs({A, B, {}});
+    };
+    
+    // N = 1
+    for (size_t M : {1, 10, 16, 33, 64})
+        for (size_t K : {7, 512, 1024})
+            for (size_t N : {1})
+                run(M, K, N);
+}
 
 #if MEGDNN_WITH_BENCHMARK