Testing combinations of multiple arrays with Cuda

Question

I have the below code written in php and have been reading up on Cuda to utilize the GPU processing power of my old Geforce 8800 Ultra. How do I convert this nested combinations test to Cuda parallel processing code (if even possible...)? The total combinations of the 2d arrays: $a, $b, $c, $d, $e quickly rise into the trillions...

foreach($a as $aVal){
    foreach($b as $bVal){
        foreach($c as $cVal){
            foreach($d as $dVal){
                foreach($e as $eVal){

                    $addSum = $aVal[0]+$bVal[0]+$cVal[0]+$dVal[0]+$eVal[0];
                    $capSum = $aVal[1]+$bVal[1]+$cVal[1]+$dVal[1]+$eVal[1];
                    if($capSum <= CAP_LIMIT){
                        $tempArr = array("a" => $aVal[2],"b" => $aVal[2],"c" => $aVal[2],
                        "d" => $aVal[2],"e" => $aVal[2],"addTotal" => $addSum,"capTotal" => $capSum);

                        array_push($topCombinations, $tempArr);

                        if(count($topCombinations) > 1000){
                           $topCombinations = $ca->arraySortedDescend($topCombinations);
                           array_splice($topCombinations, 900);

                        }
                    }  
                }
            }
        }
    }
}

Answer 1

This is a very wide-open question. It requires conversion between languages as well as designing a parallel algorithm. I won't go into too much detail, but in a nutshell:

How you parallelize it depends on the size of your arrays ($a - $e). If they are large enough, you could parallelize only the outer one or two loops across threads in a grid, and do the inner loops sequentially. If they are not super large, you might want to either flatten 2-3 of the outer loops or possibly implement them using 2D or 3D thread blocks and grids in CUDA.