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Here is last (hopefully) instalment in this thread; it only concerns faster, compared to the PDL CPAN tutorial, "Game of Life" implementation. But maybe some features used are too advanced for a tutorial. Improvement comes from:

  • To achieve wrap around, the ugly glueing in parent node is replaced with dicing along each axis. Very convenient function.
  • Horrible expression to compute next generation (requires 8 operations on whole arrays) is replaced with shorter version (just 4).
use strict; use warnings; use feature 'say'; use Time::HiRes 'time'; use PDL; use PDL::NiceSlice; use Test::PDL 'eq_pdl'; use constant { WIDTH => 20, HEIGHT => 20, STEPS => 1000, }; my $x = zeroes long, WIDTH, HEIGHT; # Put in a simple glider. $x(1:3,1:3) .= pdl ( [1,1,1], [0,0,1], [0,1,0] ); my $backup = $x-> copy; printf "Game of Life!\nMatrix: %s, %d generations\n", $x-> info, STEPS; # Tutorial my $t = time; for ( 1 .. STEPS ) { my $t_ = time; # Calculate the number of neighbours per cell. my $n = $x->range(ndcoords($x)-1,3,"periodic")->reorder(2,3,0,1); $n = $n->sumover->sumover - $x; # Calculate the next generation. $x = ((($n == 2) + ($n == 3))* $x) + (($n == 3) * !$x); } printf "Tutorial: %0.3f s\n", time - $t; # Faster my $m = $backup-> copy; $t = time; my $wrap_w = pdl [ reverse WIDTH - 1, ( 0 .. WIDTH - 1 ), 0 ]; my $wrap_h = pdl [ reverse HEIGHT - 1, ( 0 .. HEIGHT - 1 ), 0 ]; for ( 1 .. STEPS ) { my $n = $m -> dice_axis( 0, $wrap_w ) -> lags( 0, 1, WIDTH ) -> sumover -> dice_axis( 1, $wrap_h ) -> lags( 1, 1, HEIGHT ) -> xchg( 0, 1 ) -> sumover; $n -= $m; $m = ( $n == 3 ) | $m & ( $n == 2 ) } printf "Faster: %0.3f s\n", time - $t; die unless eq_pdl( $x, $m ); __END__ Game of Life! Matrix: PDL: Long D [20,20], 1000 generations Tutorial: 0.341 s Faster: 0.111 s Matrix: PDL: Long D [200,200], 100 generations Tutorial: 0.845 s Faster: 0.086 s Matrix: PDL: Long D [1000,1000], 20 generations Tutorial: 4.422 s Faster: 0.443 s Matrix: PDL: Long D [2000,2000], 10 generations Tutorial: 8.878 s Faster: 0.872 s

In reply to Re^3: Fast sliding submatrix sums with PDL (inspired by PWC 248 task 2) by Anonymous Monk
in thread Fast sliding submatrix sums with PDL (inspired by PWC 248 task 2) by Anonymous Monk

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