Scalable Parallel Numerical CSP Solver
arXiv:1411.1507v11 citations
Originality Synthesis-oriented
AI Analysis
This addresses the need for faster NCSP solving in computational domains, though it appears incremental as it builds on existing parallelization techniques.
The paper tackled the problem of solving numerical constraint satisfaction problems (NCSPs) by developing a parallel solver that scales across multiple cores, achieving up to a 119-fold speedup using 256 cores.
We present a parallel solver for numerical constraint satisfaction problems (NCSPs) that can scale on a number of cores. Our proposed method runs worker solvers on the available cores and simultaneously the workers cooperate for the search space distribution and balancing. In the experiments, we attained up to 119-fold speedup using 256 cores of a parallel computer.