/BenchParallelMeta

A comparative study of high-productivity high-performance programming languages for parallel metaheuristics

Primary LanguageC++

BenchParallelMeta

This repository contains the source code for the comparative study presented in the paper

Jan Gmys, Tiago Carneiro, Nouredine Melab, El-Ghazali Talbi, Daniel Tuyttens, A comparative study of high-productivity high-performance programming languages for parallel metaheuristics, Swarm and Evolutionary Computation

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Content

Parallel implementations in C++/OpenMP, Julia, Python-Numba and Chapel:

  1. For the 3-dimensional Quadratic Assignment Problem (Q3AP)

    • Q3AP-ILS: Iterated Local Search (ILS) metaheuristic using multi-threaded parallel neighborhood evaluations.
    • Q3AP-GA: Genetic Algorithm, hybridized with Parallel Local Search.

  2. ParallelBatchEval: A micro-benchmark evaluating the performance of parallel batch evaluation of solutions for different batchsizes and different cost functions:

    • Permutation Flowshop Scheduling Problem (PFSP)
    • Quadratic Assignment Problem (QAP)
    • Traveling Salesman Problem (TSP)
    • Q3AP

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How to run

ILS

Python

  • no numba, instance nug12-d, 10 ILS iterations
    • python3 ./ilsQ3AP_numpy.py nug12 10
  • no numba + multiprocessing
    • python3 ./ilsQ3AP_numpy_par.py nug12 10
  • with numba
    • sequential: python3 ./ilsQ3AP_numba_seq.py nug12 100
    • parallel: python3 ./ilsQ3AP_numba_seq.py nug12 100

To set the number of threads in the parallel numba version

  • ex.: export NUMBA_NUM_THREADS=4
  • OpenMP environment variables should be unset as they may interfere

Julia

  • sequential (nug12-d, 100 iterations)

    • julia ./ils_q3ap_seq.jl nug12 100

  • parallel (8 threads)

    • export JULIA_NUM_THREADS=8
    • julia ./ils_q3ap_par.jl nug12 100

C

  • compile:
    • make
  • run with 8 threads (nug12-d, 100 iterations)
    • OMP_NUM_THREADS=8 ./ils nug12 100

ParallelBatchEval

Python

3 arguments required: problem | instance| batchsize

Examples:

  • python3 ./bench.py TSP berlin52 1000
  • python3 ./bench.py FSP ta020 10000
  • python3 ./bench.py QAP nug15 100
  • python3 ./bench.py Q3AP nug12 1000

Julia

3 arguments required: problem | instance| batchsize

Examples:

  • julia ./bench.jl TSP berlin52 1000

C

  • make
  • ./bench -z p=fsp,i=ta120 -b 1000
  • ./bench --help gives some help