| 1 | tim | 2075 | #include <cassert> | 
| 2 |  |  | #include <fstream> | 
| 3 |  |  | #include <algorithm> | 
| 4 |  |  | #include "utils/simError.h" | 
| 5 |  |  | #include "math/ParallelRandNumGen.hpp" | 
| 6 |  |  |  | 
| 7 |  |  | void RandNumGenTestCase::testUniform(){ | 
| 8 |  |  | MTRand randNumGen(823645754); | 
| 9 |  |  |  | 
| 10 |  |  | const int N = 16; | 
| 11 |  |  | std::vector<unsigned long int> histogram(N, 0); | 
| 12 |  |  | const int num = 1000000; | 
| 13 |  |  | for (int i = 0; i <num; ++i) { | 
| 14 |  |  | ++histogram[randNumGen.randInt(N -1 )]; // rantInt returns an integer in [0, N-1] | 
| 15 |  |  | } | 
| 16 |  |  |  | 
| 17 |  |  | std::ofstream uniform("uniform.dat") | 
| 18 |  |  | int avg = num / N; | 
| 19 |  |  | double tolerance = 0.01*avg; | 
| 20 |  |  | for (int i = 0; i < num; ++i) { | 
| 21 |  |  | assert((histogram[i] - avg) /avg <= tolerance); | 
| 22 |  |  | uniform << i << "\t" << histogram[i] << std::endl; | 
| 23 |  |  | } | 
| 24 |  |  | } | 
| 25 |  |  |  | 
| 26 |  |  | void RandNumGenTestCase::testGaussian(){ | 
| 27 |  |  | MTRand randNumGen(823645754); | 
| 28 |  |  | double mean = 100.0; | 
| 29 |  |  | double variance = 1.0; | 
| 30 |  |  | const int num = 1000000; | 
| 31 |  |  | double interval = 0.1; | 
| 32 |  |  | const int size = 2000; | 
| 33 |  |  | vector<unsigned long int> histogram(size , 0); | 
| 34 |  |  | vector<double> normalizedHistogram(size); | 
| 35 |  |  | for (int i = 0; i < num; ++i) { | 
| 36 |  |  | int index = static_cast<int>(randNumGen.randNorm(mean, variance) / interval); | 
| 37 |  |  | ++histogram[index]; | 
| 38 |  |  | } | 
| 39 |  |  |  | 
| 40 |  |  | std::transform(histogram.begin(), histogram.end(), normalizedHistogram.begin(), std::bind2nd(std::divides<double>(), num)); | 
| 41 |  |  | std::ofstream gaussian("gaussian.dat"); | 
| 42 |  |  | for (int i = 0; i < num; ++i) { | 
| 43 |  |  | gaussian << i << "\t" << normalizedHistogram[i] << std::endl; | 
| 44 |  |  | } | 
| 45 |  |  | } | 
| 46 |  |  |  | 
| 47 |  |  | void RandNumGenTestCase::testParallelRandNumGen(){ | 
| 48 |  |  | const int seed = 324271632; | 
| 49 |  |  | const int nloops = 1000000; | 
| 50 |  |  | MPI_Status istatus; | 
| 51 |  |  | ParallelRandNumGen mpiRandNumGen(seed); | 
| 52 |  |  | const int masterNode = 0; | 
| 53 |  |  | if (worldRank = masterNode) { | 
| 54 |  |  |  | 
| 55 |  |  | MTRand singleRandNumGen(seed); | 
| 56 |  |  |  | 
| 57 |  |  | int nProcessors; | 
| 58 |  |  | MPI_Comm_size(MPI_COMM_WORLD, &nProcessors); | 
| 59 |  |  | std::vector<unsigned long int> mpiRandNums(nProcessors); | 
| 60 |  |  | std::vector<unsigned long int> singleRandNums(nProcessors); | 
| 61 |  |  |  | 
| 62 |  |  | for (int i = 0; i < nloops; ++i) { | 
| 63 |  |  | mpiRandNums[masterNode] = mpiRandNumGen.randInt(); | 
| 64 |  |  |  | 
| 65 |  |  | for (int j = 0; j < nProcessors; ++j) { | 
| 66 |  |  | if (j != masterNode) { | 
| 67 |  |  | MPI_Recv(&mpiRandNums[j], 1, MPI_UNSIGNED_LONG, j, i, MPI_COMM_WORLD, &istatus); | 
| 68 |  |  | } | 
| 69 |  |  |  | 
| 70 |  |  | singleRandNums[j] = mpiRandNumGen.randInt(); | 
| 71 |  |  | } | 
| 72 |  |  |  | 
| 73 |  |  | assert(mpiRandNums, singleRandNums); | 
| 74 |  |  | } | 
| 75 |  |  |  | 
| 76 |  |  |  | 
| 77 |  |  |  | 
| 78 |  |  | } else { | 
| 79 |  |  |  | 
| 80 |  |  | unsigned long int randNum; | 
| 81 |  |  | for (int i = 0; i < nloops; ++i) { | 
| 82 |  |  | randNum = mpiRandNumGen.randInt(); | 
| 83 |  |  | MPI_Send(&randNum, 1, MPI_INT, masterNode, i, MPI_COMM_WORLD); | 
| 84 |  |  | } | 
| 85 |  |  |  | 
| 86 |  |  | } | 
| 87 |  |  |  | 
| 88 |  |  | } | 
| 89 |  |  |  | 
| 90 |  |  |  | 
| 91 |  |  | int main(int argc, char* argv[]) { | 
| 92 |  |  |  | 
| 93 |  |  | MPI_Init(argc, argv); | 
| 94 |  |  |  | 
| 95 |  |  | if (worldRank == 0 ) { | 
| 96 |  |  | testUniform(); | 
| 97 |  |  | testGaussian(); | 
| 98 |  |  | } | 
| 99 |  |  |  | 
| 100 |  |  | testParallelRandNumGen(); | 
| 101 |  |  |  | 
| 102 |  |  | MPI_Finalize(); | 
| 103 |  |  | } |