197 lines
6.7 KiB
C++
197 lines
6.7 KiB
C++
// MIT License
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// Copyright 2022 University of Bremen
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//
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// Permission is hereby granted, free of charge, to any person obtaining
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// a copy of this software and associated documentation files (the "Software"),
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// to deal in the Software without restriction, including without limitation
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// the rights to use, copy, modify, merge, publish, distribute, sublicense,
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// and/or sell copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following conditions:
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//
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// The above copyright notice and this permission notice shall be included
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// in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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// IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
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// DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
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// OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR
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// THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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//
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//
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// David Rotermund ( davrot@uni-bremen.de )
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//
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//
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// Release history:
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// ================
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// 1.0.0 -- 01.05.2022: first release
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//
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//
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#include "SpikeGeneration2DManyIP.h"
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#include <omp.h>
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#include <stdio.h>
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#include <string.h>
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#include <algorithm>
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#include <cassert>
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#include <iostream>
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#include <vector>
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SpikeGeneration2DManyIP::SpikeGeneration2DManyIP(){
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};
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SpikeGeneration2DManyIP::~SpikeGeneration2DManyIP(){
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};
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bool SpikeGeneration2DManyIP::spike_generation_multi_pattern(
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int64_t np_input_pointer_addr, int64_t np_input_dim_0,
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int64_t np_input_dim_1, int64_t np_input_dim_2, int64_t np_input_dim_3,
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int64_t np_random_values_pointer_addr, int64_t np_random_values_dim_0,
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int64_t np_random_values_dim_1, int64_t np_random_values_dim_2,
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int64_t np_random_values_dim_3, int64_t np_output_pointer_addr,
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int64_t np_output_dim_0, int64_t np_output_dim_1, int64_t np_output_dim_2,
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int64_t np_output_dim_3, int64_t number_of_cpu_processes) {
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int64_t number_of_pattern = np_input_dim_0;
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int64_t pattern_id;
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omp_set_num_threads(number_of_cpu_processes);
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#pragma omp parallel for
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for (pattern_id = 0; pattern_id < number_of_pattern; pattern_id++) {
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spike_generation(
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np_input_pointer_addr, np_input_dim_0, np_input_dim_1, np_input_dim_2,
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np_input_dim_3, np_random_values_pointer_addr, np_random_values_dim_0,
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np_random_values_dim_1, np_random_values_dim_2, np_random_values_dim_3,
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np_output_pointer_addr, np_output_dim_0, np_output_dim_1,
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np_output_dim_2, np_output_dim_3, pattern_id);
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}
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return true;
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};
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bool SpikeGeneration2DManyIP::spike_generation(
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int64_t np_input_pointer_addr, int64_t np_input_dim_0,
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int64_t np_input_dim_1, int64_t np_input_dim_2, int64_t np_input_dim_3,
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int64_t np_random_values_pointer_addr, int64_t np_random_values_dim_0,
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int64_t np_random_values_dim_1, int64_t np_random_values_dim_2,
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int64_t np_random_values_dim_3, int64_t np_output_pointer_addr,
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int64_t np_output_dim_0, int64_t np_output_dim_1, int64_t np_output_dim_2,
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int64_t np_output_dim_3, int64_t id_pattern) {
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float *np_input_pointer = (float *)np_input_pointer_addr;
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float *np_random_values_pointer = (float *)np_random_values_pointer_addr;
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int64_t *np_output_pointer = (int64_t *)np_output_pointer_addr;
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assert((id_pattern >= 0));
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assert((id_pattern < np_input_dim_0));
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// Input
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assert((np_input_pointer != nullptr));
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assert((np_input_dim_0 > 0));
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assert((np_input_dim_1 > 0));
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assert((np_input_dim_2 > 0));
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assert((np_input_dim_3 > 0));
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int64_t np_input_dim_c0 = np_input_dim_1 * np_input_dim_2 * np_input_dim_3;
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int64_t np_input_dim_c1 = np_input_dim_2 * np_input_dim_3;
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int64_t np_input_dim_c2 = np_input_dim_3;
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// Random
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assert((np_random_values_pointer != nullptr));
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assert((np_random_values_dim_0 > 0));
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assert((np_random_values_dim_1 > 0));
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assert((np_random_values_dim_2 > 0));
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assert((np_random_values_dim_3 > 0));
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int64_t np_random_values_dim_c0 =
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np_random_values_dim_1 * np_random_values_dim_2 * np_random_values_dim_3;
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int64_t np_random_values_dim_c1 =
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np_random_values_dim_2 * np_random_values_dim_3;
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int64_t np_random_values_dim_c2 = np_random_values_dim_3;
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// Output
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assert((np_output_pointer != nullptr));
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assert((np_output_dim_0 > 0));
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assert((np_output_dim_1 > 0));
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assert((np_output_dim_2 > 0));
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assert((np_output_dim_3 > 0));
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int64_t np_output_dim_c0 =
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np_output_dim_1 * np_output_dim_2 * np_output_dim_3;
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int64_t np_output_dim_c1 = np_output_dim_2 * np_output_dim_3;
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int64_t np_output_dim_c2 = np_output_dim_3;
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// -------------------------------
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int64_t h_dim = np_input_dim_1;
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int64_t spike_dim = np_output_dim_1;
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std::vector<float> temp_p;
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temp_p.resize(h_dim);
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float *temp_p_ptr = temp_p.data();
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std::vector<int64_t> temp_out;
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temp_out.resize(spike_dim);
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int64_t *temp_out_ptr = temp_out.data();
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std::vector<float> temp_rand;
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temp_rand.resize(spike_dim);
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float *temp_rand_ptr = temp_rand.data();
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int64_t counter;
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int64_t counter_x = 0;
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int64_t counter_y = 0;
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float *p_ptr = nullptr;
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int64_t *out_ptr = nullptr;
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float *rand_ptr = nullptr;
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std::vector<float>::iterator position_iterator;
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for (counter_x = 0; counter_x < np_output_dim_2; counter_x++) {
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for (counter_y = 0; counter_y < np_output_dim_3; counter_y++) {
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p_ptr = np_input_pointer + id_pattern * np_input_dim_c0 +
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counter_x * np_input_dim_c2 + counter_y;
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// + counter * np_input_dim_c1
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out_ptr = np_output_pointer + id_pattern * np_output_dim_c0 +
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counter_x * np_output_dim_c2 + counter_y;
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// + counter * np_output_dim_c1
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rand_ptr = np_random_values_pointer +
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id_pattern * np_random_values_dim_c0 +
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counter_x * np_random_values_dim_c2 + counter_y;
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// + counter * np_random_values_dim_c1
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#pragma omp simd
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for (counter = 0; counter < h_dim; counter++) {
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temp_p_ptr[counter] = p_ptr[counter * np_input_dim_c1];
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}
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#pragma omp simd
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for (counter = 0; counter < spike_dim; counter++) {
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temp_rand_ptr[counter] = rand_ptr[counter * np_random_values_dim_c1];
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}
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// ----------------------------
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for (counter = 0; counter < spike_dim; counter++) {
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position_iterator = std::lower_bound(temp_p.begin(), temp_p.end(),
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temp_rand_ptr[counter]);
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temp_out_ptr[counter] = position_iterator - temp_p.begin();
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}
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// ----------------------------
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#pragma omp simd
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for (counter = 0; counter < spike_dim; counter++) {
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out_ptr[counter * np_output_dim_c1] = temp_out_ptr[counter];
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}
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}
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}
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return true;
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};
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