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cmake(opt): AVX512_SKX

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This commit is contained in:
Alexander Alekhin
2017-12-29 05:06:52 +00:00
parent fc1d85bf59
commit 7d67d60fb1
10 changed files with 88 additions and 18 deletions
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modules/core/include/opencv2/core/cv_cpu_dispatch.h
+7
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@@ -86,6 +86,10 @@
# include <immintrin.h>
# define CV_AVX_512F 1
#endif
#ifdef CV_CPU_COMPILE_AVX512_SKX
# include <immintrin.h>
# define CV_AVX512_SKX 1
#endif
#ifdef CV_CPU_COMPILE_FMA3
# define CV_FMA3 1
#endif
@@ -222,6 +226,9 @@ struct VZeroUpperGuard {
#ifndef CV_AVX_512VL
# define CV_AVX_512VL 0
#endif
#ifndef CV_AVX512_SKX
# define CV_AVX512_SKX 0
#endif
#ifndef CV_NEON
# define CV_NEON 0
modules/core/include/opencv2/core/cv_cpu_helper.h
+15
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@@ -180,6 +180,21 @@
#endif
#define __CV_CPU_DISPATCH_CHAIN_AVX_512F(fn, args, mode, ...) CV_CPU_CALL_AVX_512F(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_SKX
# define CV_TRY_AVX512_SKX 1
# define CV_CPU_HAS_SUPPORT_AVX512_SKX 1
# define CV_CPU_CALL_AVX512_SKX(fn, args) return (opt_AVX512_SKX::fn args)
#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_SKX
# define CV_TRY_AVX512_SKX 1
# define CV_CPU_HAS_SUPPORT_AVX512_SKX (cv::checkHardwareSupport(CV_CPU_AVX512_SKX))
# define CV_CPU_CALL_AVX512_SKX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_SKX) return (opt_AVX512_SKX::fn args)
#else
# define CV_TRY_AVX512_SKX 0
# define CV_CPU_HAS_SUPPORT_AVX512_SKX 0
# define CV_CPU_CALL_AVX512_SKX(fn, args)
#endif
#define __CV_CPU_DISPATCH_CHAIN_AVX512_SKX(fn, args, mode, ...) CV_CPU_CALL_AVX512_SKX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON
# define CV_TRY_NEON 1
# define CV_CPU_HAS_SUPPORT_NEON 1
modules/core/include/opencv2/core/cvdef.h
+13 -4
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@@ -146,7 +146,8 @@ namespace cv { namespace debug_build_guard { } using namespace debug_build_guard
#define CV_CPU_AVX_512CD 15
#define CV_CPU_AVX_512DQ 16
#define CV_CPU_AVX_512ER 17
#define CV_CPU_AVX_512IFMA512 18
#define CV_CPU_AVX_512IFMA512 18 // deprecated
#define CV_CPU_AVX_512IFMA 18
#define CV_CPU_AVX_512PF 19
#define CV_CPU_AVX_512VBMI 20
#define CV_CPU_AVX_512VL 21
@@ -155,8 +156,11 @@ namespace cv { namespace debug_build_guard { } using namespace debug_build_guard
#define CV_CPU_VSX 200
// CPU features groups
#define CV_CPU_AVX512_SKX 256
// when adding to this list remember to update the following enum
#define CV_HARDWARE_MAX_FEATURE 255
#define CV_HARDWARE_MAX_FEATURE 512
/** @brief Available CPU features.
*/
@@ -179,14 +183,19 @@ enum CpuFeatures {
CPU_AVX_512CD = 15,
CPU_AVX_512DQ = 16,
CPU_AVX_512ER = 17,
CPU_AVX_512IFMA512 = 18,
CPU_AVX_512IFMA512 = 18, // deprecated
CPU_AVX_512IFMA = 18,
CPU_AVX_512PF = 19,
CPU_AVX_512VBMI = 20,
CPU_AVX_512VL = 21,
CPU_NEON = 100,
CPU_VSX = 200
CPU_VSX = 200,
CPU_AVX512_SKX = 256, //!< Skylake-X with AVX-512F/CD/BW/DQ/VL
CPU_MAX_FEATURE = 512 // see CV_HARDWARE_MAX_FEATURE
};
modules/core/src/system.cpp
+8 -1
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@@ -301,7 +301,7 @@ struct HWFeatures
g_hwFeatureNames[CPU_AVX_512CD] = "AVX512CD";
g_hwFeatureNames[CPU_AVX_512DQ] = "AVX512DQ";
g_hwFeatureNames[CPU_AVX_512ER] = "AVX512ER";
g_hwFeatureNames[CPU_AVX_512IFMA512] = "AVX512IFMA";
g_hwFeatureNames[CPU_AVX_512IFMA] = "AVX512IFMA";
g_hwFeatureNames[CPU_AVX_512PF] = "AVX512PF";
g_hwFeatureNames[CPU_AVX_512VBMI] = "AVX512VBMI";
g_hwFeatureNames[CPU_AVX_512VL] = "AVX512VL";
@@ -309,6 +309,8 @@ struct HWFeatures
g_hwFeatureNames[CPU_NEON] = "NEON";
g_hwFeatureNames[CPU_VSX] = "VSX";
g_hwFeatureNames[CPU_AVX512_SKX] = "AVX512-SKX";
}
void initialize(void)
@@ -456,6 +458,11 @@ struct HWFeatures
have[CV_CPU_AVX_512VBMI] = false;
have[CV_CPU_AVX_512VL] = false;
}
if (have[CV_CPU_AVX_512F])
{
have[CV_CPU_AVX512_SKX] = have[CV_CPU_AVX_512F] & have[CV_CPU_AVX_512CD] & have[CV_CPU_AVX_512BW] & have[CV_CPU_AVX_512DQ] & have[CV_CPU_AVX_512VL];
}
}
#else
CV_UNUSED(cpuid_data);
modules/dnn/CMakeLists.txt
+1 -1
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@@ -13,7 +13,7 @@ endif()
set(the_description "Deep neural network module. It allows to load models from different frameworks and to make forward pass")
ocv_add_dispatched_file("layers/layers_common" AVX AVX2 AVX_512F)
ocv_add_dispatched_file("layers/layers_common" AVX AVX2 AVX512_SKX)
ocv_add_module(dnn opencv_core opencv_imgproc WRAP python matlab java js)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wno-shadow -Wno-parentheses -Wmaybe-uninitialized -Wsign-promo
modules/dnn/src/layers/convolution_layer.cpp
+6 -6
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@@ -384,7 +384,7 @@ public:
p.is1x1_ = kernel == Size(0,0) && pad == Size(0, 0);
p.useAVX = checkHardwareSupport(CPU_AVX);
p.useAVX2 = checkHardwareSupport(CPU_AVX2);
p.useAVX512 = CV_CPU_HAS_SUPPORT_AVX_512F;
p.useAVX512 = CV_CPU_HAS_SUPPORT_AVX512_SKX;
int ncn = std::min(inpCn, (int)BLK_SIZE_CN);
p.ofstab_.resize(kernel.width*kernel.height*ncn);
@@ -564,10 +564,10 @@ public:
// now compute dot product of the weights
// and im2row-transformed part of the tensor
int bsz = ofs1 - ofs0;
#if CV_TRY_AVX_512F
#if CV_TRY_AVX512_SKX
/* AVX512 convolution requires an alignment of 16, and ROI is only there for larger vector sizes */
if(useAVX512)
opt_AVX_512F::fastConv(wptr, wstep, biasptr, rowbuf0, data_out0 + ofs0,
opt_AVX512_SKX::fastConv(wptr, wstep, biasptr, rowbuf0, data_out0 + ofs0,
outShape, bsz, vsz, vsz_a, relu, cn0 == 0);
else
#endif
@@ -1102,7 +1102,7 @@ public:
nstripes_ = nstripes;
useAVX = checkHardwareSupport(CPU_AVX);
useAVX2 = checkHardwareSupport(CPU_AVX2);
useAVX512 = CV_CPU_HAS_SUPPORT_AVX_512F;
useAVX512 = CV_CPU_HAS_SUPPORT_AVX512_SKX;
}
void operator()(const Range& range_) const
@@ -1120,9 +1120,9 @@ public:
size_t bstep = b_->step1();
size_t cstep = c_->step1();
#if CV_TRY_AVX_512F
#if CV_TRY_AVX512_SKX
if( useAVX512 )
opt_AVX_512F::fastGEMM( aptr, astep, bptr, bstep, cptr, cstep, mmax, kmax, nmax );
opt_AVX512_SKX::fastGEMM( aptr, astep, bptr, bstep, cptr, cstep, mmax, kmax, nmax );
else
#endif
#if CV_TRY_AVX2
modules/dnn/src/layers/fully_connected_layer.cpp
+3 -3
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@@ -161,7 +161,7 @@ public:
p.activ = activ;
p.useAVX = checkHardwareSupport(CPU_AVX);
p.useAVX2 = checkHardwareSupport(CPU_AVX2);
p.useAVX512 = CV_CPU_HAS_SUPPORT_AVX_512F;
p.useAVX512 = CV_CPU_HAS_SUPPORT_AVX512_SKX;
parallel_for_(Range(0, nstripes), p, nstripes);
}
@@ -196,9 +196,9 @@ public:
memcpy(sptr, sptr_, vecsize*sizeof(sptr[0]));
#if CV_TRY_AVX_512F
#if CV_TRY_AVX512_SKX
if( useAVX512 )
opt_AVX_512F::fastGEMM1T( sptr, wptr, wstep, biasptr, dptr, nw, vecsize);
opt_AVX512_SKX::fastGEMM1T( sptr, wptr, wstep, biasptr, dptr, nw, vecsize);
else
#endif
#if CV_TRY_AVX2
modules/dnn/src/layers/layers_common.simd.hpp
+1 -1
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@@ -301,7 +301,7 @@ void fastGEMM( const float* aptr, size_t astep, const float* bptr,
{
int n = 0;
#if CV_AVX_512F
#if CV_AVX512_SKX // AVX512VL is necessary to avoid register spilling
for( ; n <= nb - 32; n += 32 )
{
for( int m = 0; m < ma; m += 4 )