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,...
Wepresent an object-oriented framework for constructing parallel implementations of stencil algorithms. This framework simplifres the development process by encapsulating the comm...
John F. Karpovich, Matthew Judd, W. Timothy Straye...
Heterogeneous networks of computers have rapidly become a very promising commodity computing solution, expected to play a major role in the design of high performance computing sy...
This paper describes a parallel rendering method based on the adaptive supersampling technique to produce anti-aliased images with minimal memory consumption. Unlike traditional s...
Sam Lin, Rynson W. H. Lau, Xiaola Lin, Paul Y. S. ...