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@marty1885
Created February 1, 2019 09:05
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//build: c++ tmperf.cpp -o tmperf -O3 -lnupic_core
//usage: ./tmperf
#include <nupic/algorithms/TemporalMemory.hpp>
#include <chrono>
#include <vector>
#include <random>
using TemporalMemory = nupic::algorithms::temporal_memory::TemporalMemory; //Yeah.... This is too redundent
const int TM_INPUT_SIZE = 64;
const float INPUT_DENSITY = 0.1f;
const size_t NUM_ITER = 40000;
const size_t ITER_REPORT = 1000;
int main()
{
//To generate random SDR efficently
std::vector<UInt> all_columns(TM_INPUT_SIZE);
for(size_t i=0;i<TM_INPUT_SIZE;i++)
all_columns[i] = i;
auto randomSDR = [&all_columns](auto& res){
static std::mt19937 rng;
std::shuffle(all_columns.begin(), all_columns.end(), rng);
std::copy(all_columns.begin(), all_columns.begin()+res.size(), res.begin());
std::sort(res.begin(), res.end());
};
std::cout << "TemporalMemory performance test. Parameters:\n"
<< "Input SDR size: " << TM_INPUT_SIZE << '\n'
<< "SDR Density: " << INPUT_DENSITY << '\n';
//The main code
std::vector<UInt> active_columns(TM_INPUT_SIZE*INPUT_DENSITY);
TemporalMemory tm({TM_INPUT_SIZE});
auto t1 = std::chrono::high_resolution_clock::now();
for(size_t i=0;i<NUM_ITER;i++) {
randomSDR(active_columns);
tm.compute(active_columns.size(), active_columns.data(), true);
if((i+1)%ITER_REPORT == 0) {
auto t2 = std::chrono::high_resolution_clock::now();
std::cout << "Iteration " << i+1 << ": time per TM execution is "
<< std::chrono::duration_cast<std::chrono::duration<double>>(t2-t1).count()/ITER_REPORT*1000 << " ms." << std::endl; //Force flush
t1 = std::chrono::high_resolution_clock::now();
}
}
}
@marty1885
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Example output:
(On I5 8250U, Linux, GCC 8.2.1)

Input SDR size: 64
SDR Density: 0.1
Iteration 1000: time per TM execution is 0.0727128 ms.
Iteration 2000: time per TM execution is 0.0772516 ms.
Iteration 3000: time per TM execution is 0.10591 ms.
Iteration 4000: time per TM execution is 0.141974 ms.
Iteration 5000: time per TM execution is 0.171026 ms.
Iteration 6000: time per TM execution is 0.213778 ms.
Iteration 7000: time per TM execution is 0.256422 ms.
Iteration 8000: time per TM execution is 0.310993 ms.
Iteration 9000: time per TM execution is 0.355887 ms.
Iteration 10000: time per TM execution is 0.424861 ms.
Iteration 11000: time per TM execution is 0.522072 ms.
Iteration 12000: time per TM execution is 0.552158 ms.
Iteration 13000: time per TM execution is 0.609994 ms.
Iteration 14000: time per TM execution is 0.679534 ms.
Iteration 15000: time per TM execution is 0.848373 ms.
Iteration 16000: time per TM execution is 1.06723 ms.
Iteration 17000: time per TM execution is 1.25357 ms.
Iteration 18000: time per TM execution is 1.45957 ms.
Iteration 19000: time per TM execution is 1.56519 ms.
Iteration 20000: time per TM execution is 1.67367 ms.
Iteration 21000: time per TM execution is 1.7592 ms.
Iteration 22000: time per TM execution is 1.84701 ms.
Iteration 23000: time per TM execution is 1.90377 ms.
Iteration 24000: time per TM execution is 2.08463 ms.
Iteration 25000: time per TM execution is 2.25694 ms.
Iteration 26000: time per TM execution is 2.44186 ms.
Iteration 27000: time per TM execution is 2.63037 ms.
Iteration 28000: time per TM execution is 2.82431 ms.
Iteration 29000: time per TM execution is 3.01219 ms.
Iteration 30000: time per TM execution is 3.64744 ms.
Iteration 31000: time per TM execution is 3.87887 ms.
Iteration 32000: time per TM execution is 4.08649 ms.
Iteration 33000: time per TM execution is 4.28914 ms.
Iteration 34000: time per TM execution is 4.60198 ms.
Iteration 35000: time per TM execution is 5.42536 ms.
Iteration 36000: time per TM execution is 5.63289 ms.
Iteration 37000: time per TM execution is 5.00891 ms.
Iteration 38000: time per TM execution is 5.20788 ms.
Iteration 39000: time per TM execution is 5.39356 ms.
Iteration 40000: time per TM execution is 5.61194 ms.

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