It is widely acknowledged in high-performance computing circles that parallel input/output needs substantial improvement in order to make scalable computers truly usable. We prese...
Rajesh Bordawekar, Alok N. Choudhary, Ken Kennedy,...
The Cross-Entropy (CE) method is a modern and effective optimization method well suited to parallel implementations. There is a vast array of problems today, some of which are hig...
Gareth E. Evans, Jonathan M. Keith, Dirk P. Kroese
Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
In this paper, we suggest a parallel algorithm based on a shared memory SIMD architecture for solving an n item subset-sum problem in time O(2n/2 /p) by using p = 2q processors, 0...
Carlos Alberto Alonso Sanches, Nei Yoshihiro Soma,...