Sciweavers

Share
SIAMDM
2002
124views more  SIAMDM 2002»
9 years 6 months ago
Scheduling Unrelated Machines by Randomized Rounding
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...
Andreas S. Schulz, Martin Skutella
CORR
2010
Springer
153views Education» more  CORR 2010»
9 years 7 months ago
GraphLab: A New Framework for Parallel Machine Learning
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuf...
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny B...
JSSPP
1995
Springer
9 years 10 months ago
Time Space Sharing Scheduling and Architectural Support
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...
PPOPP
1993
ACM
9 years 11 months ago
LogP: Towards a Realistic Model of Parallel Computation
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...
PLDI
1993
ACM
9 years 11 months ago
Global Optimizations for Parallelism and Locality on Scalable Parallel Machines
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 ...
Jennifer-Ann M. Anderson, Monica S. Lam
ISCA
1993
IEEE
125views Hardware» more  ISCA 1993»
9 years 11 months ago
Evaluation of Mechanisms for Fine-Grained Parallel Programs in the J-Machine and the CM-5
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...
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
10 years 1 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
books