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reuse AVX2-optimized kernels for AVX1 CPUs (like IvyBridge)

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This commit is contained in:
Vadim Pisarevsky
2017-07-06 21:36:59 +03:00
parent f670a99270
commit ed9564106c
6 changed files with 447 additions and 306 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+16 -1
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@@ -285,11 +285,12 @@ public:
const std::vector<float>* reluslope_;
const ActivationLayer* activ_;
bool is1x1_;
bool useAVX;
bool useAVX2;
ParallelConv()
: input_(0), weights_(0), output_(0), ngroups_(0), nstripes_(0),
biasvec_(0), reluslope_(0), activ_(0), is1x1_(false), useAVX2(false)
biasvec_(0), reluslope_(0), activ_(0), is1x1_(false), useAVX(false), useAVX2(false)
{}
static void run( const Mat& input, Mat& output, const Mat& weights,
@@ -322,6 +323,7 @@ public:
int inpCnAll = input.size[1], width = input.size[3], height = input.size[2];
int inpCn = inpCnAll / ngroups;
p.is1x1_ = kernel == Size(0,0) && pad == Size(0, 0);
p.useAVX = checkHardwareSupport(CPU_AVX);
p.useAVX2 = checkHardwareSupport(CPU_AVX2);
int ncn = std::min(inpCn, (int)BLK_SIZE_CN);
@@ -507,6 +509,12 @@ public:
fastConv_avx2(wptr, wstep, biasptr, rowbuf0, data_out0 + ofs0,
outShape, bsz, vsz, vsz_a, relu, cn0 == 0);
else
#endif
#if CV_TRY_AVX
if(useAVX)
fastConv_avx(wptr, wstep, biasptr, rowbuf0, data_out0 + ofs0,
outShape, bsz, vsz, vsz_a, relu, cn0 == 0);
else
#endif
for( int i = 0; i < outCn; i += 2 )
{
@@ -795,6 +803,7 @@ public:
b_ = &b;
c_ = &c;
nstripes_ = nstripes;
useAVX = checkHardwareSupport(CPU_AVX);
useAVX2 = checkHardwareSupport(CPU_AVX2);
}
@@ -817,6 +826,11 @@ public:
if( useAVX2 )
fastGEMM_avx2( aptr, astep, bptr, bstep, cptr, cstep, mmax, kmax, nmax );
else
#endif
#if CV_TRY_AVX
if( useAVX )
fastGEMM_avx( aptr, astep, bptr, bstep, cptr, cstep, mmax, kmax, nmax );
else
#endif
for( m = 0; m < mmax; m += 2 )
{
@@ -910,6 +924,7 @@ public:
const Mat *a_, *b_;
Mat* c_;
int nstripes_;
bool useAVX;
bool useAVX2;
};