Can use PP features much better (untested, illustrative):pp_def('sms_WxH_pdlpp_4loops', Pars => 'a(m,n); [o]b(p,q);', OtherPars => 'PDL_Indx par_sm_w; PDL_Indx par_sm_h;', RedoDimsCode => '$SIZE(p) = $SIZE(m) - $COMP(par_sm_w) + 1; $SIZE(q) = $SIZE(n) - $COMP(par_sm_h) + 1;', Code => ' PDL_Indx i, j, k, l, w, h, W, H; w = $COMP(par_sm_w); h = $COMP(par_sm_h); W = $SIZE(m); H = $SIZE(n); for (i = 0; i < H - h + 1; i++) { for (j = 0; j < W - w + 1; j++) { for (k = 0; k < w; k++) { for (l = 0; l < h; l++) { $b(p=>j, q=>i) += $a(m=>j+k, n=>i+l); } } } } ', );
Features used above: OtherPars can set $SIZE of dims not otherwise used. When something is a $SIZE, you can loop() over it. If an index (named dim) is indexed by a variable of the same name, it can be omitted (as for $b() above). Obviously I used the fact that you can give several loops at once, which is very neat. Finally, your loop conditions were recalculating the expressions used to set $SIZE(p) etc.pp_def('sms_WxH_pdlpp_4loops', Pars => 'a(m,n); [o]b(p,q);', OtherPars => 'PDL_Indx par_sm_w => w; PDL_Indx par_sm_h => h;', RedoDimsCode => '$SIZE(p) = $SIZE(m) - $SIZE(w) + 1; $SIZE(q) = $SIZE(n) - $SIZE(h) + 1;', Code => 'loop(q,p,w,h) %{ $b() += $a(m=>p+w, n=>q+h); %}', );
Looking at the loop(), I suspect you want to switch the w and h loops to do everything as much as possible on the fastest-moving dimension. This algorithm would probably benefit a lot from tiling for maximum cache-hitting, which should probably become a proper PP feature. If someone wants to open a PDL issue with suggestions as to what the syntax would look like, it will probably get implemented and used on matmult.
In reply to Re: Fast sliding submatrix sums with PDL (inspired by PWC 248 task 2)
by etj
in thread Fast sliding submatrix sums with PDL (inspired by PWC 248 task 2)
by Anonymous Monk
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