1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
|
// Copyright 2009-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
#include "parallel_filter.h"
#include "../sys/regression.h"
#include <map>
namespace embree
{
struct parallel_filter_regression_test : public RegressionTest
{
parallel_filter_regression_test(const char* name) : RegressionTest(name) {
registerRegressionTest(this);
}
bool run ()
{
bool passed = true;
auto pred = [&]( uint32_t v ) { return (v & 0x3) == 0; };
for (size_t N=10; N<1000000; N=size_t(2.1*N))
{
size_t N0 = rand() % N;
/* initialize array with random numbers */
std::vector<uint32_t> src(N);
std::map<uint32_t,int> m;
for (size_t i=0; i<N; i++) src[i] = rand();
/* count elements up */
for (size_t i=N0; i<N; i++)
if (pred(src[i]))
m[src[i]] = 0;
for (size_t i=N0; i<N; i++)
if (pred(src[i]))
m[src[i]]++;
/* filter array */
//size_t M = sequential_filter(src.data(),N0,N,pred);
size_t M = parallel_filter(src.data(),N0,N,size_t(1024),pred);
/* check if filtered data is correct */
for (size_t i=N0; i<M; i++) {
passed &= pred(src[i]);
m[src[i]]--;
}
for (size_t i=N0; i<M; i++)
passed &= (m[src[i]] == 0);
}
return passed;
}
};
parallel_filter_regression_test parallel_filter_regression("parallel_filter_regression");
}
|