Complex Calculate use avx2 are slower 3 times than normal #880

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1. serge-sans-paille commented on Jan 10, 2023

   

   serge-sans-paille

   on Jan 10, 2023

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   Sorry, I cannot reproduce your timings. Here is the test program I've been using

   #include <iostream>
   #include <xsimd/xsimd.hpp>
   #include <vector>
   
   int main(int argc, char** argv)
   {
     unsigned n = std::atoi(argv[1]);
     unsigned p = std::atoi(argv[2]);
     std::vector<double> x(n);
     std::vector<double> y(n);
     std::vector<double> out(n);
     for(unsigned i = 0; i < n; ++i) {
       x[i] = .00002 * i;
       y[i] = .00003 * i;
     }
     for(unsigned j = 0; j < p; ++j) {
   #ifdef USE_XSIMD
       for(unsigned i = 0; i < n; i += xsimd::batch<double, xsimd::avx2>::size) {
         auto vout = xsimd::load_unaligned(&out[i]);
         auto vx = xsimd::load_unaligned(&x[i]);
         auto vy = xsimd::load_unaligned(&y[i]);
         vout += xsimd::sqrt((xsimd::cos(vx) + xsimd::sin(vy)) / 2.);
         vout.store_unaligned(&out[i]);
       }
   #else
       for(unsigned i = 0; i < n; ++i) {
         out[i] += std::sqrt((xsimd::cos(x[i]) + std::sin(y[i])) / 2);
       }
   #endif
     }
     std::cout << out[n / p] << "\n";
     return 0;
   }
   

   compiled with g++ test.cpp -O2 -mavx2 -o r -UUSE_XSIMD -DNDEBUG -Iinclude && time ./r 1000000 100 or g++ test.cpp -O2 -mavx2 -o r -DUSE_XSIMD -DNDEBUG -Iinclude && time ./r 1000000 100

   I get a consistent x2.5 speedup with xsimd on... same for -O3 and with clang.
2. YggSky commented on Jan 11, 2023

   

   YggSky

   on Jan 11, 2023

   Last edited by YggSky

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   Sorry, I cannot reproduce your timings. Here is the test program I've been using

   #include <iostream>
   #include <xsimd/xsimd.hpp>
   #include <vector>
   
   int main(int argc, char** argv)
   {
     unsigned n = std::atoi(argv[1]);
     unsigned p = std::atoi(argv[2]);
     std::vector<double> x(n);
     std::vector<double> y(n);
     std::vector<double> out(n);
     for(unsigned i = 0; i < n; ++i) {
       x[i] = .00002 * i;
       y[i] = .00003 * i;
     }
     for(unsigned j = 0; j < p; ++j) {
   #ifdef USE_XSIMD
       for(unsigned i = 0; i < n; i += xsimd::batch<double, xsimd::avx2>::size) {
         auto vout = xsimd::load_unaligned(&out[i]);
         auto vx = xsimd::load_unaligned(&x[i]);
         auto vy = xsimd::load_unaligned(&y[i]);
         vout += xsimd::sqrt((xsimd::cos(vx) + xsimd::sin(vy)) / 2.);
         vout.store_unaligned(&out[i]);
       }
   #else
       for(unsigned i = 0; i < n; ++i) {
         out[i] += std::sqrt((xsimd::cos(x[i]) + std::sin(y[i])) / 2);
       }
   #endif
     }
     std::cout << out[n / p] << "\n";
     return 0;
   }
   

   compiled with g++ test.cpp -O2 -mavx2 -o r -UUSE_XSIMD -DNDEBUG -Iinclude && time ./r 1000000 100 or g++ test.cpp -O2 -mavx2 -o r -DUSE_XSIMD -DNDEBUG -Iinclude && time ./r 1000000 100

   I get a consistent x2.5 speedup with xsimd on... same for -O3 and with clang.

   I use your code ,get the same result,even if i change the n=1e8,p=1. but when I change the data with my input

   for(unsigned i = 0; i < n; ++i) {
       //x[i] = .00002 * i;
     // y[i] = .00003 * i;
   	x[i] = i;
   	y[i] = std::sin(i);
     }
   

   the time is Very different. the n=1e8,p=1. (12s with 4s). with n=1e6,p=1e2 time 1.1s(whit xsimd avx2) to 2.4s(normal) . I think maybe 2 reason. 1.the data input ,2 the data size could affect the time cost.
3. amyspark commented on Jan 13, 2023

   

   amyspark

   on Jan 13, 2023

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   Here's a godbolt with the alternatives: https://godbolt.org/z/TosvEr9fz Both show the 2.5x speedup.
4. YggSky commented on Jan 15, 2023

   

   YggSky

   on Jan 15, 2023

   Last edited by YggSky

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   Here's a godbolt with the alternatives: https://godbolt.org/z/TosvEr9fz Both show the 2.5x speedup.

   the code you use n=1e6，p=1e2 . with this parameter ,time ture speedup,I get the same with you. but when n=1e8,p=1,time will different,as i description above. when i change your code

    //unsigned n = std::atoi("1000000");
   //    unsigned p = std::atoi("100");
   
   unsigned n = std::atoi("100000000");
   unsigned p = std::atoi("1");
   

   unfortunately,can't execute. with n = std::atoi("1000000") p = std::atoi("100") certainly the time with yours. so if you make the n size enough,you will find time xmind will cost more, i debug find the internal ximd::sin or simd::cos time-consuming. if the data size small .such n=1e6 the function will not,but if you use n=1e8 and use std::sqrt((std::cos(x[i]) + std::sin(y[i])) / 2),not use std::sqrt((xmind::cos(x[i]) + xmind::sin(y[i])) / 2) time more

   that great impact ximd::cos or ximd::sin, if the data size is small ,such you use n=1e6,not big different,but n=1e8,the result big different.)