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/**
* This code is released under the
* Apache License Version 2.0 http://www.apache.org/licenses/.
*
* (c) Daniel Lemire, http://lemire.me/en/
*/
#include <algorithm>
#include <vector>
#include <set>
#ifdef _MSC_VER
#include <winsock2.h>
#else
#include <sys/time.h>
#endif
#include "ewah.h"
using namespace std;
/**
* Mersenne twister - random number generator.
* Generate uniform distribution of 32 bit integers with the MT19937 algorithm.
* source: http://bannister.us/weblog/?s=Mersenne
*/
class ZRandom {
private:
enum {
N = 624, M = 397
};
unsigned int MT[N + 1];
unsigned int* map[N];
int nValues;
public:
ZRandom(unsigned int iSeed = 20070102);
void seed(unsigned iSeed);
unsigned int getValue();
unsigned int getValue(const uint32_t MaxValue);
double getDouble();
bool test(const double p);
};
ZRandom::ZRandom(unsigned iSeed) :
nValues(0) {
seed(iSeed);
}
void ZRandom::seed(unsigned iSeed) {
nValues = 0;
// Seed the array used in random number generation.
MT[0] = iSeed;
for (int i = 1; i < N; ++i) {
MT[i] = 1 + (69069 * MT[i - 1]);
}
// Compute map once to avoid % in inner loop.
for (int i = 0; i < N; ++i) {
map[i] = MT + ((i + M) % N);
}
}
inline bool ZRandom::test(const double p) {
return getDouble() <= p;
}
inline double ZRandom::getDouble() {
return double(getValue()) * (1.0 / 4294967296.0);
}
unsigned int ZRandom::getValue(const uint32_t MaxValue) {
unsigned int used = MaxValue;
used |= used >> 1;
used |= used >> 2;
used |= used >> 4;
used |= used >> 8;
used |= used >> 16;
// Draw numbers until one is found in [0,n]
unsigned int i;
do
i = getValue() & used; // toss unused bits to shorten search
while (i > MaxValue);
return i;
}
unsigned int ZRandom::getValue() {
if (0 == nValues) {
MT[N] = MT[0];
for (int i = 0; i < N; ++i) {
register unsigned y = (0x80000000 & MT[i]) | (0x7FFFFFFF
& MT[i + 1]);
register unsigned v = *(map[i]) ^ (y >> 1);
if (1 & y)
v ^= 2567483615;
MT[i] = v;
}
nValues = N;
}
unsigned int y = MT[N - nValues--];
y ^= y >> 11;
y ^= (y << 7) & 2636928640U;
y ^= (y << 15) & 4022730752U;
y ^= y >> 18;
return y;
}
class UniformDataGenerator {
public:
UniformDataGenerator(unsigned int seed = static_cast<unsigned int>(time(NULL))) :
rand(seed) {
}
vector<uint32_t> generateDenseUniform(uint32_t N, uint32_t Max) {
return generateUniform(N, Max);
}
vector<uint32_t> generateSparseUniform(uint32_t N, uint32_t Max) {
return generateUniform(N, Max);
}
vector<uint32_t> generateUniform(uint32_t N, uint32_t Max) {
vector<uint32_t> ans;
if (N > Max)
throw runtime_error("not possible");
if (N == Max) {
for (uint32_t k = 0; k < Max; ++k)
ans.push_back(k);
assert(ans.back() < Max);
return ans;
}
if (N > Max / 2) {
set<uint32_t> s;
while (s.size() < N)
s.insert(rand.getValue(Max - 1));
ans.assign(s.begin(), s.end());
return ans;
}
while (ans.size() < N) {
while (ans.size() < N) {
ans.push_back(rand.getValue(Max - 1));
}
sort(ans.begin(), ans.end());
vector<uint32_t>::iterator it = unique(ans.begin(), ans.end());
ans.resize(static_cast<uint32_t>(it - ans.begin()));
}
return ans;
}
ZRandom rand;
};
class ClusteredDataGenerator {
public:
UniformDataGenerator unidg;
ClusteredDataGenerator(
unsigned int seed = static_cast<unsigned int> (time(NULL))) :
unidg(seed) {
}
vector<uint32_t> generateDenseClustered(uint32_t N, uint32_t Max) {
return generateClustered(N, Max);
}
vector<uint32_t> generateSparseClustered(uint32_t N, uint32_t Max) {
return generateClustered(N, Max);
}
template<class iterator>
void fillUniform(iterator begin, iterator end, uint32_t Min, uint32_t Max) {
vector<uint32_t> v = unidg.generateUniform(
static_cast<uint32_t> (end - begin), Max - Min);
for (uint32_t k = 0; k < v.size(); ++k)
begin[k] = Min + v[k];
}
template<class iterator>
void fillClustered(iterator begin, iterator end, uint32_t Min, uint32_t Max) {
const uint32_t N = static_cast<uint32_t> (end - begin);
const uint32_t range = Max - Min;
if ((range == N) or (N <= 10)) {
fillUniform(begin, end, Min, Max);
return;
}
const uint32_t cut = N / 2 + unidg.rand.getValue(range - N - 1);
const double p = unidg.rand.getDouble();
if (p < 0.25) {
fillUniform(begin, begin + N / 2, Min, Min + cut);
fillClustered(begin + N / 2, end, Min + cut, Max);
} else if (p < 0.5) {
fillClustered(begin, begin + N / 2, Min, Min + cut);
fillUniform(begin + N / 2, end, Min + cut, Max);
} else {
fillClustered(begin, begin + N / 2, Min, Min + cut);
fillClustered(begin + N / 2, end, Min + cut, Max);
}
}
vector<uint32_t> generateClustered(uint32_t N, uint32_t Max) {
vector<uint32_t> ans(N);
fillClustered(ans.begin(), ans.end(), 0, Max);
return ans;
}
};
/**
* author: Preston Bannister
*/
class WallClockTimer {
public:
struct timeval t1, t2;
WallClockTimer() :
t1(), t2() {
gettimeofday(&t1, 0);
t2 = t1;
}
void reset() {
gettimeofday(&t1, 0);
t2 = t1;
}
int elapsed() {
return (static_cast<int> (t2.tv_sec - t1.tv_sec) * 1000)
+ static_cast<int> (t2.tv_usec - t1. tv_usec) / 1000;
}
int split() {
gettimeofday(&t2, 0);
return elapsed();
}
};
template<class uword>
void test(vector<vector<uint32_t> > & data, int repeat) {
WallClockTimer timer;
long bogus = 0;
// building
timer.reset();
vector<EWAHBoolArray<uword> > ewah(data.size());
size_t size = 0;
for (int r = 0; r < repeat; ++r) {
size = 0;
for (size_t k = 0; k < data.size(); ++k) {
ewah[k].reset();
for (uint32_t x = 0; x < data.at(k).size(); ++x) {
ewah[k].set(data.at(k).at(x));
}
size += ewah[k].sizeInBytes();
}
}
cout << size << "\t";
cout << timer.split() << "\t";
timer.reset();
for (int r = 0; r < repeat; ++r)
for (size_t k = 0; k < data.size(); ++k) {
vector < size_t > vals = ewah[k].toArray();
bogus += vals.size();
assert(vals.size() == data[k].size());
}
cout << timer.split() << "\t";
timer.reset();
for (int r = 0; r < repeat; ++r)
for (size_t k = 0; k < data.size(); ++k) {
EWAHBoolArray<uword> ewahor(ewah[0]);
for (size_t j = 1; j < k; ++j) {
EWAHBoolArray<uword> container;
ewahor.logicalor(ewah[j], container);
ewahor.swap(container);
}
bogus += ewahor.sizeInBits();
}
cout << timer.split() << "\t";
timer.reset();
for (int r = 0; r < repeat; ++r)
for (size_t k = 0; k < data.size(); ++k) {
EWAHBoolArray<uword> ewahand(ewah[0]);
for (size_t j = 1; j < k; ++j) {
EWAHBoolArray<uword> container;
ewahand.logicaland(ewah[j], container);
ewahand.swap(container);
}
bogus += ewahand.sizeInBits();
}
cout << timer.split() << "\t" << bogus << endl;
}
void test(size_t N, int nbr, int repeat) {
for (int sparsity = 1; sparsity < 31 - nbr; sparsity += 1) {
ClusteredDataGenerator cdg;
cout << "# sparsity=" << sparsity << "\t";
vector < vector<uint32_t> > data(N);
uint32_t Max = (1 << (nbr + sparsity));
cout << "# generating data..." << endl;
for (size_t k = 0; k < N; ++k) {
data[k] = cdg.generateClustered(1 << nbr, Max);
}
cout << "# generating data...ok" << endl;
cout << "#64 bits" << endl;
test<uint64_t> (data, repeat);
cout << "#32 bits" << endl;
test<uint32_t> (data, repeat);
}
}
int main(void) {
test(10, 18, 1);
}