Basic benchmark polynomial evaluation using Horner's Method

benchmark-poly.py

"""Simple re-arrangement can yield significant performance improvements in
naive, low-order polynomial evaluation. The interested reader may wish to read
about "Horner's method."

(C) 2018 Nabla Zero Labs
MIT License
"""
import time

def p0(a, x):
    """First strategy: naively calculate the polynomial.
    Three additions, three multiplications, one pow(2), one pow(3)."""
    for xi in x:
        y = a[0] + a[1] * xi + a[2] * xi**2 + a[3] * xi**3
    return y

def p1(a, x):
    """Second strategy: save multiplications at the cost of memory.
    Three additions, five multiplications, two extra variables"""
    for xi in x:
        xi2 = xi * xi
        xi3 = xi2 * xi
        y = a[0] + a[1] * xi + a[2] * xi2 + a[3] * xi3
    return y

def p2(a, x):
    """Third strategy: save multiplication with no cost.
    Three additions, three multiplications.
    """
    for xi in x:
        y = a[0] + xi * (a[1] + xi * ( a[2] + a[3] * xi))
    return y

def cpu(fun, *args):
    a, x = args
    tbeg = time.perf_counter()
    y = fun(a, x)
    tend = time.perf_counter()
    elap = tend - tbeg
    thro = len(x) / elap
    print(f"{fun.__name__}: {elap:.6f} sec ({thro:.0f} eval/sec)",
          f"last value: {y:23.16e}", sep=" ")

if __name__ == "__main__":
    import random

    a = [random.uniform(-10, 10) for _ in range(4)]
    x = [random.uniform(-1, 1) for _ in range(1000000)]

    for _ in range(10):
        cpu(p0, a, x)
        cpu(p1, a, x)
        cpu(p2, a, x)

#include <chrono>
#include <iomanip>
#include <iostream>
#include <limits>
#include <random>
#include <vector>

template < typename T >
T p0( const T a[ 4 ], const std::vector< T >& x ) {
  using std::pow;
  T y = 0;
  for ( auto&& xi : x ) {
    y += a[ 0 ] + a[ 1 ] * xi + a[ 2 ] * pow( xi, 2 ) + a[ 3 ] * pow( xi, 3 );
  }
  return y;
}

template < typename T >
T p1( const T a[ 4 ], const std::vector< T >& x ) {
  T y = 0;
  for ( auto&& xi : x ) {
    auto xi2 = xi * xi;
    auto xi3 = xi2 * xi;

    y += a[ 0 ] + a[ 1 ] * xi + a[ 2 ] * xi2 + a[ 3 ] * xi3;
  }
  return y;
}

template < typename T >
T p2( const T a[ 4 ], const std::vector< T >& x ) {
  T y = 0;
  for ( auto&& xi : x ) {
    y += a[ 0 ] + xi * ( a[ 1 ] + xi * ( a[ 2 ] + a[ 3 ] * xi ) );
  }
  return y;
}

template < typename T >
T p3( const T a[ 4 ], const std::vector< T >& x ) {
  T y = 0;
  for ( auto&& xi : x ) {
    y += std::fma(
        std::fma( std::fma( a[ 3 ], xi, a[ 2 ] ), xi, a[ 1 ] ), xi, a[ 0 ] );
  }
  return y;
}

template < typename F, typename T >
void cpu( F&& fun, const T a[ 4 ], const std::vector< T >& x ) {
  using namespace std::chrono;
  auto tbeg = system_clock::now();
  auto y    = fun( a, x );
  auto tend = system_clock::now();
  auto elap = nanoseconds( tend - tbeg ).count();
  auto thro = double( x.size() ) / elap;

  std::cout << std::setprecision( std::numeric_limits< T >::max_digits10 )
            << std::scientific;
  std::cout << std::setw( 12 ) << elap << " nanosec (" << std::setw( 12 )
            << thro << " eval / nanosec) last: " << y << "\n";
}

template < typename T >
void run() {
  std::mt19937 gen( 0 );

  std::uniform_real_distribution< T > dis( -1, 1 );

  T a[] = {dis( gen ), dis( gen ), dis( gen ), dis( gen )};

  std::vector< T > x;
  for ( int k = 0; k < 1000000; ++k ) {
    x.emplace_back( dis( gen ) );
  }

  std::cout << "new run\n";
  for ( int k = 0; k < 5; ++k ) {
    cpu( p0< T >, a, x );
    cpu( p1< T >, a, x );
    cpu( p2< T >, a, x );
    cpu( p3< T >, a, x );
    std::cout << "-------------------------------------------------------------"
                 "------------------\n";
  }
}

int main() {
  run< float >();
  run< double >();
  run< long double >();
}

Result:

new run
    25824000 nanosec (3.872366791e-02 eval / nanosec) last: 2.412012031e+05
     1398000 nanosec (7.153075823e-01 eval / nanosec) last: 2.412012031e+05
     1064000 nanosec (9.398496241e-01 eval / nanosec) last: 2.412012031e+05
      795000 nanosec (1.257861635e+00 eval / nanosec) last: 2.412012031e+05
-------------------------------------------------------------------------------
    25858000 nanosec (3.867275118e-02 eval / nanosec) last: 2.412012031e+05
     1262000 nanosec (7.923930269e-01 eval / nanosec) last: 2.412012031e+05
      990000 nanosec (1.010101010e+00 eval / nanosec) last: 2.412012031e+05
      729000 nanosec (1.371742112e+00 eval / nanosec) last: 2.412012031e+05
-------------------------------------------------------------------------------
    25654000 nanosec (3.898027598e-02 eval / nanosec) last: 2.412012031e+05
     1072000 nanosec (9.328358209e-01 eval / nanosec) last: 2.412012031e+05
     1019000 nanosec (9.813542689e-01 eval / nanosec) last: 2.412012031e+05
      775000 nanosec (1.290322581e+00 eval / nanosec) last: 2.412012031e+05
-------------------------------------------------------------------------------
    25649000 nanosec (3.898787477e-02 eval / nanosec) last: 2.412012031e+05
     1107000 nanosec (9.033423668e-01 eval / nanosec) last: 2.412012031e+05
      965000 nanosec (1.036269430e+00 eval / nanosec) last: 2.412012031e+05
      717000 nanosec (1.394700139e+00 eval / nanosec) last: 2.412012031e+05
-------------------------------------------------------------------------------
    26686000 nanosec (3.747283220e-02 eval / nanosec) last: 2.412012031e+05
     1296000 nanosec (7.716049383e-01 eval / nanosec) last: 2.412012031e+05
      986000 nanosec (1.014198783e+00 eval / nanosec) last: 2.412012031e+05
      731000 nanosec (1.367989056e+00 eval / nanosec) last: 2.412012031e+05
-------------------------------------------------------------------------------
new run
    24278000 nanosec (4.11895543290221600e-02 eval / nanosec) last: 4.24933177245050552e+05
     1523000 nanosec (6.56598818122127392e-01 eval / nanosec) last: 4.24933177245050552e+05
     1244000 nanosec (8.03858520900321505e-01 eval / nanosec) last: 4.24933177245050552e+05
      918000 nanosec (1.08932461873638342e+00 eval / nanosec) last: 4.24933177245050552e+05
-------------------------------------------------------------------------------
    24012000 nanosec (4.16458437447942698e-02 eval / nanosec) last: 4.24933177245050552e+05
     1142000 nanosec (8.75656742556917722e-01 eval / nanosec) last: 4.24933177245050552e+05
     1090000 nanosec (9.17431192660550510e-01 eval / nanosec) last: 4.24933177245050552e+05
      865000 nanosec (1.15606936416184980e+00 eval / nanosec) last: 4.24933177245050552e+05
-------------------------------------------------------------------------------
    24334000 nanosec (4.10947645269992626e-02 eval / nanosec) last: 4.24933177245050552e+05
     1091000 nanosec (9.16590284142988043e-01 eval / nanosec) last: 4.24933177245050552e+05
     1043000 nanosec (9.58772770853307810e-01 eval / nanosec) last: 4.24933177245050552e+05
      874000 nanosec (1.14416475972540055e+00 eval / nanosec) last: 4.24933177245050552e+05
-------------------------------------------------------------------------------
    23830000 nanosec (4.19639110365086013e-02 eval / nanosec) last: 4.24933177245050552e+05
     1436000 nanosec (6.96378830083565492e-01 eval / nanosec) last: 4.24933177245050552e+05
     1280000 nanosec (7.81250000000000000e-01 eval / nanosec) last: 4.24933177245050552e+05
      902000 nanosec (1.10864745011086474e+00 eval / nanosec) last: 4.24933177245050552e+05
-------------------------------------------------------------------------------
    24681000 nanosec (4.05169968801912389e-02 eval / nanosec) last: 4.24933177245050552e+05
     1237000 nanosec (8.08407437348423574e-01 eval / nanosec) last: 4.24933177245050552e+05
     1123000 nanosec (8.90471950133570833e-01 eval / nanosec) last: 4.24933177245050552e+05
      860000 nanosec (1.16279069767441867e+00 eval / nanosec) last: 4.24933177245050552e+05
-------------------------------------------------------------------------------
new run
    53355000 nanosec (1.874238590572580021032e-02 eval / nanosec) last: 4.249331772450602300921e+05
     2667000 nanosec (3.749531308586426803231e-01 eval / nanosec) last: 4.249331772450602300921e+05
     1965000 nanosec (5.089058524173027953097e-01 eval / nanosec) last: 4.249331772450602300921e+05
   106937000 nanosec (9.351300298306480102140e-03 eval / nanosec) last: 4.249331772450602300921e+05
-------------------------------------------------------------------------------
    53469000 nanosec (1.870242570461388975644e-02 eval / nanosec) last: 4.249331772450602300921e+05
     2969000 nanosec (3.368137420006736548750e-01 eval / nanosec) last: 4.249331772450602300921e+05
     2194000 nanosec (4.557885141294439335091e-01 eval / nanosec) last: 4.249331772450602300921e+05
   106082000 nanosec (9.426669934578911155820e-03 eval / nanosec) last: 4.249331772450602300921e+05
-------------------------------------------------------------------------------
    53432000 nanosec (1.871537655337625338792e-02 eval / nanosec) last: 4.249331772450602300921e+05
     2746000 nanosec (3.641660597232337925888e-01 eval / nanosec) last: 4.249331772450602300921e+05
     2366000 nanosec (4.226542688081149634627e-01 eval / nanosec) last: 4.249331772450602300921e+05
   107089000 nanosec (9.338027248363510793294e-03 eval / nanosec) last: 4.249331772450602300921e+05
-------------------------------------------------------------------------------
    53097000 nanosec (1.883345575079571274091e-02 eval / nanosec) last: 4.249331772450602300921e+05
     2692000 nanosec (3.714710252600297302195e-01 eval / nanosec) last: 4.249331772450602300921e+05
     2104000 nanosec (4.752851711026616077227e-01 eval / nanosec) last: 4.249331772450602300921e+05
   107119000 nanosec (9.335412018409433229649e-03 eval / nanosec) last: 4.249331772450602300921e+05
-------------------------------------------------------------------------------
    53603000 nanosec (1.865567225714978571993e-02 eval / nanosec) last: 4.249331772450602300921e+05
     2692000 nanosec (3.714710252600297302195e-01 eval / nanosec) last: 4.249331772450602300921e+05
     1982000 nanosec (5.045408678102926147702e-01 eval / nanosec) last: 4.249331772450602300921e+05
   106767000 nanosec (9.366189927599351955356e-03 eval / nanosec) last: 4.249331772450602300921e+05
-------------------------------------------------------------------------------