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https://github.com/NVIDIA/cuda-samples.git
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96 lines
3.8 KiB
C++
96 lines
3.8 KiB
C++
/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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///////////////////////////////////////////////////////////////////////////////
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// CPU Fast Walsh Transform
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///////////////////////////////////////////////////////////////////////////////
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extern "C" void fwtCPU(float *h_Output, float *h_Input, int log2N) {
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const int N = 1 << log2N;
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for (int pos = 0; pos < N; pos++) h_Output[pos] = h_Input[pos];
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// Cycle through stages with different butterfly strides
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for (int stride = N / 2; stride >= 1; stride >>= 1) {
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// Cycle through subvectors of (2 * stride) elements
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for (int base = 0; base < N; base += 2 * stride)
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// Butterfly index within subvector of (2 * stride) size
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for (int j = 0; j < stride; j++) {
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int i0 = base + j + 0;
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int i1 = base + j + stride;
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float T1 = h_Output[i0];
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float T2 = h_Output[i1];
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h_Output[i0] = T1 + T2;
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h_Output[i1] = T1 - T2;
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}
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}
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}
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///////////////////////////////////////////////////////////////////////////////
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// Straightforward Walsh Transform: used to test both CPU and GPU FWT
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// Slow. Uses doubles because of straightforward accumulation
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///////////////////////////////////////////////////////////////////////////////
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extern "C" void slowWTcpu(float *h_Output, float *h_Input, int log2N) {
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const int N = 1 << log2N;
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for (int i = 0; i < N; i++) {
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double sum = 0;
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for (int j = 0; j < N; j++) {
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// Walsh-Hadamard quotient
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double q = 1.0;
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for (int t = i & j; t != 0; t >>= 1)
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if (t & 1) q = -q;
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sum += q * h_Input[j];
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}
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h_Output[i] = (float)sum;
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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// Reference CPU dyadic convolution.
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// Extremely slow because of non-linear memory access patterns (cache thrashing)
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////////////////////////////////////////////////////////////////////////////////
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extern "C" void dyadicConvolutionCPU(float *h_Result, float *h_Data,
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float *h_Kernel, int log2dataN,
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int log2kernelN) {
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const int dataN = 1 << log2dataN;
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const int kernelN = 1 << log2kernelN;
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for (int i = 0; i < dataN; i++) {
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double sum = 0;
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for (int j = 0; j < kernelN; j++) sum += h_Data[i ^ j] * h_Kernel[j];
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h_Result[i] = (float)sum;
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}
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}
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