x86 avx512 optimization (#3691)

* convolution sgemm pack16to1

* convolution sgemm pack4to16

* eltwise avx512

src/layer/x86/convolution_1x1_pack16to1.h

@@ -0,0 +1,65 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void conv1x1s1_sgemm_pack16to1_avx512(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int h = bottom_blob.h;
+    const int size = w * h;
+
+    Mat bottom_im2col = bottom_blob;
+    bottom_im2col.w = size;
+    bottom_im2col.h = 1;
+
+    im2col_sgemm_pack16to1_avx512(bottom_im2col, top_blob, kernel, _bias, opt);
+}
+
+static void conv1x1s2_sgemm_pack16to1_avx512(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int channels = bottom_blob.c;
+    size_t elemsize = bottom_blob.elemsize;
+    int elempack = bottom_blob.elempack;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+
+    const int tailstep = (w - 2 * outw + w) * 16;
+
+    Mat bottom_blob_shrinked;
+    bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = 0; p < channels; p++)
+    {
+        const float* r0 = bottom_blob.channel(p);
+        float* outptr = bottom_blob_shrinked.channel(p);
+
+        for (int i = 0; i < outh; i++)
+        {
+            for (int j = 0; j < outw; j++)
+            {
+                __m512 _v = _mm512_load_ps(r0);
+                _mm512_store_ps(outptr, _v);
+
+                r0 += 32;
+                outptr += 16;
+            }
+
+            r0 += tailstep;
+        }
+    }
+
+    conv1x1s1_sgemm_pack16to1_avx512(bottom_blob_shrinked, top_blob, kernel, _bias, opt);
+}

src/layer/x86/convolution_1x1_pack4to16.h

@@ -0,0 +1,66 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void conv1x1s1_sgemm_pack4to16_avx512(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int h = bottom_blob.h;
+    const int size = w * h;
+
+    Mat bottom_im2col = bottom_blob;
+    bottom_im2col.w = size;
+    bottom_im2col.h = 1;
+
+    im2col_sgemm_pack4to16_avx512(bottom_im2col, top_blob, kernel, _bias, opt);
+}
+
+static void conv1x1s2_sgemm_pack4to16_avx512(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int channels = bottom_blob.c;
+    size_t elemsize = bottom_blob.elemsize;
+    int elempack = bottom_blob.elempack;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+
+    const int tailstep = (w - 2 * outw + w) * 4;
+
+    Mat bottom_blob_shrinked;
+    bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = 0; p < channels; p++)
+    {
+        const float* r0 = bottom_blob.channel(p);
+        float* outptr = bottom_blob_shrinked.channel(p);
+
+        for (int i = 0; i < outh; i++)
+        {
+            int j = 0;
+            for (; j < outw; j++)
+            {
+                __m128 _v = _mm_load_ps(r0);
+                _mm_store_ps(outptr, _v);
+
+                r0 += 8;
+                outptr += 4;
+            }
+
+            r0 += tailstep;
+        }
+    }
+
+    conv1x1s1_sgemm_pack4to16_avx512(bottom_blob_shrinked, top_blob, kernel, _bias, opt);
+}