We present a new class of randomized approximation algorithms for unrelated parallel machine scheduling problems with the average weighted completion time objective. The key idea i...
In this paper, we describe a new job scheduling class, called \Time Space Sharing Scheduling" (TSSS) for dynamically partitionable parallel machines. As an instance of TSSS, ...
Atsushi Hori, Takashi Yokota, Yutaka Ishikawa, Shu...
A vast body of theoretical research has focused either on overly simplistic models of parallel computation, notably the PRAM, or overly specific models that have few representati...
David E. Culler, Richard M. Karp, David A. Patters...
Data locality is critical to achievinghigh performance on large-scale parallel machines. Non-local data accesses result in communication that can greatly impact performance. Thus ...
er uses an abstract machine approach to compare the mechanisms of two parallel machines: the J-Machine and the CM-5. High-level parallel programs are translated by a single optimi...
Ellen Spertus, Seth Copen Goldstein, Klaus E. Scha...
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...