High-performance incremental scheduling on massively parallel computers: a global approach

Authors:
Min-You Wu;Wei Shu
Affiliations:
Department of Computer Science, State University of New York at Buffalo, Buffalo, NY;Department of Computer Science, State University of New York at Buffalo, Buffalo, NY
Venue:
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Year:
1995

Citing 17
Cited 0

Simulations of three adaptive, decentralized controlled, job scheduling algorithms

Computer Networks and ISDN Systems
A distributed load-balancing policy for a multicomputer

Software—Practice & Experience
Depth-first iterative-deepening: an optimal admissible tree search

Artificial Intelligence
Adaptive load sharing in homogeneous distributed systems

IEEE Transactions on Software Engineering
A comparison of receiver-initiated and sender-initiated adaptive load sharing

Performance Evaluation
A Partitioning Strategy for Nonuniform Problems on Multiprocessors

IEEE Transactions on Computers
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems

Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Dynamic load balancing for distributed memory multiprocessors

Journal of Parallel and Distributed Computing
Scheduling parallel program tasks onto arbitrary target machines

Journal of Parallel and Distributed Computing - Special issue: software tools for parallel programming and visualization
Execution time support for adaptive scientific algorithms on distributed

Concurrency: Practice and Experience
PYRROS: static task scheduling and code generation for message passing multiprocessors

ICS '92 Proceedings of the 6th international conference on Supercomputing
Applications and performance analysis of a compile-time optimization approach for list scheduling algorithms on distributed memory multiprocessors

Proceedings of the 1992 ACM/IEEE conference on Supercomputing
Load Distributing for Locally Distributed Systems

Computer
Hypertool: A Programming Aid for Message-Passing Systems

IEEE Transactions on Parallel and Distributed Systems
Strategies for Dynamic Load Balancing on Highly Parallel Computers

IEEE Transactions on Parallel and Distributed Systems
The PARTY Parallel Runtime System - Invited Talk

Proceedings of the Third SIAM Conference on Parallel Processing for Scientific Computing
Runtime incremental parallel scheduling (RIPS) for large-scale parallel computers

FRONTIERS '95 Proceedings of the Fifth Symposium on the Frontiers of Massively Parallel Computation (Frontiers'95)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Runtime incremental parallel scheduling (RIPS) is a new approach for load balancing. In parallel scheduling, all processors cooperate together to balance the workload. Parallel scheduling accurately balances the load by using global load information. In incremental scheduling, the system scheduling activity alternates with the underlying computation work. RIPS produces high-quality load balancing and adapts to applications of nonuniform structures. This paper presents methods for scheduling a single job on a dedicated parallel machine.