OlivierLi

#include <map>
#include <vector>
#include <chrono>
#include <iostream>
#include <algorithm>
#include <map>
#include <cassert>

bool comp( const std::pair<size_t, size_t>& lhs, const std::pair<size_t, size_t>& rhs ) {return lhs.first < rhs.first; }

OlivierLi

cmake_minimum_required(VERSION 2.8)
project(skip_map)

SET(CMAKE_CXX_COMPILER clang++)
SET(CLANG_COMPILE_FLAGS "-Wall -Wextra -Wfatal-errors --std=c++14 -g")
SET(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} ${CLANG_COMPILE_FLAGS}" )

#Find all cpp files recursively
file(GLOB_RECURSE SRC "src" "*.cpp")

OlivierLi

void test_sse( int *output, const int *input )
{
	//SSE -> AVX transition
	//_mm256_zeroall();

	//Load the integers into an xmm register
	__m256i loaded_ints = _mm256_loadu_si256( ( const __m256i* )input );

	//Convert the integers to float values
	__m256 values_reg = _mm256_cvtepi32_ps( loaded_ints );

OlivierLi

#include "stdafx.h"

#include <iostream>
#include <chrono>
#include <immintrin.h>
#include <memory>

static inline bool isAligned( const void *pointer, size_t byte_count )
{
	return (uintptr_t) pointer % byte_count == 0;

OlivierLi

#include "stdafx.h"

#include <iostream>
#include <chrono>
#include <xmmintrin.h>
#include <cstring>

void test_sse( unsigned char *output, int *input )
{
	//Create alligned arrays on the stack and the pointers needed to access them

OlivierLi

// test3.cpp : Defines the entry point for the console application.
//

#include <cassert>
#include <chrono>
#include <iostream>
#include <random>
#include <vector>
#include <cstdint>
#include <algorithm>

OlivierLi

#include <functional>
#include <vector>
#include <future>
#include <iostream>

class MyType
{
public:
	int value = 0;
	int compute()

OlivierLi

#include <iostream>
#include <vector>
#include <sstream>
#include <deque>
#include <fstream>
#include <algorithm>
#include <set>
#include <bits/unique_ptr.h>
#include <bits/stl_map.h>

OlivierLi

----------------------------------------------------------
Training predictor neural_network_predictor
Result: success
Validating predictor neural_network_predictor
Mean Squared Error: 0.803143 Mean Percent Error: 12.9514%
----------------------------------------------------------
Training predictor knn_predictor
Result: success
Validating predictor knn_predictor
Mean Squared Error: 0.485454 Mean Percent Error: 9.83764%

OlivierLi

{
    "particles_count" : 64000,
    "particle_mass" : 0.0025,
    "simulation_time" : 1,
    "target_fps" : 60,
    "simulation_scale" : 0.01,
    "write_all_frames" : false,
    "constant_acceleration" : {
    	"x" : 0, "y" : -9.8, "z" : 0
    }