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main-performance.cpp
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main-performance.cpp
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#include <unistd.h>
#include <iostream>
#include "bloom_filter.hpp"
#include "cuckoo_filter.hpp"
#include "ltc.hpp"
#include "reservoir_sampling.hpp"
#include "mc_nn.hpp"
#include <sys/time.h>
using namespace std;
#define BLOOM_FILTER_SIZE 600
unsigned int hash_int(int* element){
return (*element)%BLOOM_FILTER_SIZE;
}
double When() {
struct timeval tp;
gettimeofday(&tp, NULL);
return ((double) tp.tv_sec + (double) tp.tv_usec * 1e-6);
}
#define CUCKOO_BUCKET_COUNT 32
#define CUCKOO_ENTRY_BY_BUCKET 6
#define CUCKOO_ENTRY_SIZE 3
struct funct_cuckoo{
static unsigned char fingerprint(int const* e){
//mod 7 == value between 0 and 6, +1 == value between 1 and 7, so the empty value (0x0) is avoided
return ((*e)%7)+1;
}
static unsigned int hash(int const* e){
return (*e)%CUCKOO_BUCKET_COUNT;
}
/*
* Make the combination of hash element and hash fingerprint does not lead to the same value
* Hash of fingerprint should probably not return a 0 or a 2^CUCKOO_ENTRY_SIZE-1 because it create same h1 and h2
*/
static unsigned int hash(unsigned char fingerprint){
return (fingerprint * 7)%CUCKOO_BUCKET_COUNT;
}
};
double randy(void){
return (double)rand() / (double)RAND_MAX;
}
void test_cuckoo(void) {
cout << "\t=== Cuckoo ===" << endl;
CuckooFilter<int, CUCKOO_BUCKET_COUNT, CUCKOO_ENTRY_BY_BUCKET, CUCKOO_ENTRY_SIZE, funct_cuckoo, randy> cf;
unsigned int const count_add = 100000000;
unsigned int const count_lookup = 100000000;
double start = When();
for(int i = 0; i < count_add; ++i){
cf.add(i);
if(i%100 == 0)
cf.clear();
}
double stop = When();
cout << "Time (Insert): " << (stop - start) << " (" << (((stop - start) / count_add) * 1e9) << " ns/item)" << endl;
cf.clear();
start = When();
for(int i = 0; i < count_lookup; ++i){
cf.lookup(i);
}
stop = When();
cout << "Time (Lookup): " << (stop - start) << " (" << (((stop - start) / count_lookup) * 1e9) << " ns/item)" << endl;
}
void test_bloom(void){
cout << "\t=== Bloom ===" << endl;
auto p = hash_int;
unsigned int const count_add = 1000000000;
unsigned int const count_lookup = 1000000000;
BloomFilter<int, BLOOM_FILTER_SIZE, 1> bf(&p);
double start = When();
for(int i = 0; i < count_add; ++i){
bf.add(i);
}
double stop = When();
cout << "Time (Insert): " << (stop - start) << " (" << (((stop - start) / count_add) * 1e9) << " ns/item)" << endl;
bf.clear();
start = When();
for(int i = 0; i < count_lookup; ++i){
bf.lookup(i);
}
stop = When();
cout << "Time (Lookup): " << (stop - start) << " (" << (((stop - start) / count_lookup) * 1e9) << " ns/item)" << endl;
}
#define LTC_SIZE 1000000
void test_ltc(void){
cout << "\t=== LTC ===" << endl;
double start, stop;
int count_smooth = 0, count_rough = 0, count_linear = 0, count_rand = 0;
int vals_smooth[LTC_SIZE];
int vals_rough[LTC_SIZE];
int* vals_rand = vals_smooth;
for(int i = 0; i < LTC_SIZE; ++i){
vals_smooth[i] = round(cos(i*0.1) * 20);
vals_rough[i] = round(cos(i) * 20);
}
start = When();
for(int j = 0; j < 1000; ++j)
{
LTC<int, int, 3> comp;
for(int i = 0; i < LTC_SIZE; ++i){
bool a = comp.add(i, i%200);
if(a)
count_linear += 1;
}
}
stop = When();
cout << "Time (linear): " << (stop - start) << " (" << (((stop - start) / (LTC_SIZE * 1000)) * 1e9) << " ns/item)" << endl;
start = When();
for(int j = 0; j < 1000; ++j)
{
LTC<int, int, 3> comp;
for(int i = 0; i < LTC_SIZE; ++i){
bool a = comp.add(i, vals_smooth[i]);
if(a)
count_smooth += 1;
}
}
stop = When();
cout << "Time (smooth): " << (stop - start) << " (" << (((stop - start) / (LTC_SIZE * 1000)) * 1e9) << " ns/item)" << endl;
start = When();
for(int j = 0; j < 1000; ++j)
{
LTC<int, int, 3> comp;
for(int i = 0; i < LTC_SIZE; ++i){
bool a = comp.add(i, vals_rough[i]);
if(a)
count_rough += 1;
}
}
stop = When();
cout << "Time (rough): " << (stop - start) << " (" << (((stop - start) / (LTC_SIZE * 1000)) * 1e9) << " ns/item)" << endl;
for(int i = 0; i < LTC_SIZE; ++i)
vals_rand[i] = rand()%100000;
start = When();
for(int j = 0; j < 1000; ++j)
{
LTC<int, int, 3> comp;
for(int i = 0; i < LTC_SIZE; ++i){
bool a = comp.add(i, vals_rand[i]);
if(a)
count_rand += 1;
}
}
stop = When();
cout << "Time (random): " << (stop - start) << " (" << (((stop - start) / (LTC_SIZE * 1000)) * 1e9) << " ns/item)" << endl;
cout << "Linear: " << ((count_linear)/1e6) << "M" << endl;
cout << "Smooth: " << ((count_smooth)/1e6) << "M" << endl;
cout << "Rough: " << ((count_rough)/1e6) << "M" << endl;
cout << "Rand: " << ((count_rand)/1e6) << "M" << endl;
}
void test_reservoir_sampling(void){
cout << "\t=== Reservoir Sampling ===" << endl;
ReservoirSampling<int, 100, randy> rs;
unsigned int sum_pre_count = 0;
int pre_count[100] = {0}, count_loop = 1000000;
pre_count[20] = 1000;
pre_count[25] = 500;
pre_count[50] = 400;
pre_count[75] = 250;
for(int i = 0; i < 100; ++i)
sum_pre_count += pre_count[i];
int count[100] = {0};
double start, stop;
start = When();
for(int k = 0; k < count_loop; ++k)
for(int i = 0; i < 100; ++i)
for(int j = 0; j < pre_count[i]; ++j)
rs.add(i);
stop = When();
cout << "Time: " << (stop - start) << " (" << (((stop - start) / (count_loop * sum_pre_count)) * 1e9 ) << " ns/item)" << endl;
for(int i = 0; i < 100; ++i){
int idx = rs[i];
if(idx >= 0 && idx < 100)
count[idx] += 1;
}
for(int i = 0; i < 100; ++i)
if(count[i] < 0)
cout << i << ": " << count[i] << endl;
}
#define MCNN_FEATURE_COUNT 4
//void test_mc_nn(void){
//cout << "\t=== MCNN ===" << endl;
//int dataset_size = 20;
//MCNN<double, features_count, 10, 10> classifier;
//double* dataset = (int*)calloc(features_count * dataset_size, sizeof(double));
//int* labels = malloc(dataset_size * sizeof(int));
//double* dataset2 = (int*)calloc(features_count * dataset_size, sizeof(double));
//int* labels2 = malloc(dataset_size * sizeof(int));
//for(int i = 0; i < dataset_size; ++i){
//labels[i] = rand()%7;
////TODO give some random value
//for(int j = 0; j < features_count; ++j)
//dataset[i][j] = 0;
//labels2[i] = rand()%7;
////TODO give some random value
//for(int j = 0; j < features_count; ++j)
//dataset2[i][j] = 0;
//}
//int const turn_count = 10;
//for(int i = 0; i < turn_count; ++i){
//for(int idx = 0; idx < dataset_size; ++idx)
//classifier.train(dataset[idx], labels[idx]);
//for(int idx = 0; idx < dataset_size; ++idx)
//classifier.train(dataset2[idx], labels2[idx]);
//}
//classifier.print();
//for(int idx = 8; idx < 13; ++idx){
//auto predict = classifier.predict(dataset[idx]);
//cout << "Prediction for " << idx << ": " << predict << endl;
//classifier.train(dataset[idx], labels[idx]);
//classifier.print();
//}
//}
int main(int argc, char** argv){
test_ltc();
test_reservoir_sampling();
test_bloom();
test_cuckoo();
return 0;
}