68 lines
2.0 KiB
C++
68 lines
2.0 KiB
C++
#pragma once
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#include <mmintrin.h>
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#include <xmmintrin.h>
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#include <emmintrin.h>
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#include <xmmintrin.h>
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#include <pmmintrin.h>
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#include "./StreamingBasisFunction.h"
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#include "../../sse_mathfun.h"
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namespace NeuralNetwork {
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namespace BasisFunction {
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class Linear: public StreamingBasisFunction {
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public:
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Linear() {}
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inline virtual float computeStreaming(const std::vector<float>& weights, const std::vector<float>& input) override {
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size_t inputSize=input.size();
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size_t alignedPrev=inputSize-inputSize%4;
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const float* weightsData=weights.data();
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const float* inputData=input.data();
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vec4f partialSolution;
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partialSolution.sse =_mm_setzero_ps();
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//TODO prefetch ??
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for(register size_t k=0;k<alignedPrev;k+=4) {
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partialSolution.sse=_mm_add_ps(partialSolution.sse,_mm_mul_ps(_mm_load_ps(weightsData+k),_mm_load_ps(inputData+k)));
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}
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for(register size_t k=alignedPrev;k<inputSize;k++) {
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partialSolution.sse=_mm_add_ps(partialSolution.sse,_mm_mul_ps(_mm_load_ss(weightsData+k),_mm_load_ss(inputData+k)));
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}
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#ifdef USE_SSE2 //pre-SSE3 solution
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partialSolution.sse= _mm_add_ps(_mm_movehl_ps(partialSolution.sse, partialSolution.sse), partialSolution.sse);
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partialSolution.sse=_mm_add_ss(partialSolution.sse, _mm_shuffle_ps(partialSolution.sse,partialSolution.sse, 1));
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#else
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partialSolution.sse = _mm_hadd_ps(partialSolution.sse, partialSolution.sse);
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partialSolution.sse = _mm_hadd_ps(partialSolution.sse, partialSolution.sse);
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#endif
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return partialSolution.f[0];
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}
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inline virtual float compute(const std::vector<float>& weights, const std::vector<float>& input) override {
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register float tmp = 0;
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size_t inputSize=input.size();
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for(size_t k=0;k<inputSize;k++) {
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tmp+=input[k]*weights[k];
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}
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return tmp;
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}
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virtual BasisFunction* clone() const override {
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return new Linear();
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}
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virtual std::string stringify() const override {
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return "{ \"class\": \"NeuralNetwork::BasisFunction::Linear\" }";
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}
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};
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}
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} |