在 C++ 中使用 openMP 实现并行 DES

Question

I am trying to Parallelize DES but hardly getting any speedup. Parallelizing the s-box part is not giving any speed up rather it is running in polynomial time. Here is the s-box part of the DES:

int row[8],col[8],val[8];
    //s box parallelism
    #pragma omp parallel for num_threads(8) schedule(static)
        for (int i = 0; i < 8; i++) {
            //the value of '0' is 48, '1' is 49 and so on. but since we are referring the matrix index, we are interested in 0,1,..
            //So, the '0' should be subtracted . i.e. the 49 value of '1' will be 49-48=1.
                int tid = omp_get_thread_num();
                row[tid] = 2 * int(x[tid * 6] - '0') + int(x[tid * 6 + 5] - '0'); 
                col[tid] = 8 * int(x[tid * 6 + 1] - '0') + 4 * int(x[tid * 6 + 2] - '0') + 2 * int(x[tid * 6 + 3] - '0') + int(x[tid * 6 + 4] - '0');
                val[tid] = sbox[tid][row[tid]][col[tid]];
                result[tid]= decimalToBinary(val[tid]);
        }

Is there a way I can parallelize s-boxes to improve speedup? or is there another part of algorithm which can be parallelized to get maximum speedup? Any examples?

Answer 1

use auto range1= std::async(dowork) to calculate ranges in parallel and return range1.get()+range2.get() etc..