Bandwidth-aware resource allocation for heterogeneous computing systems to maximize throughput

Hong, Bin Na; Prasanna, Viktor K.

doi:10.1109/icpp.2003.1240621

Cited by 16 publications

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Master-Slave Tasking on Asymmetric Networks

Banino-Rokkones

Beaumont

Natvig

2006

Euro-Par 2006 Parallel Processing

View full text Add to dashboard Cite

Abstract. This paper presents new techniques for master-slave tasking on treeshaped networks with fully heterogeneous communication and processing resources. A large number of independent, equal-sized tasks are distributed from the master node to the slave nodes for processing and return of result files. The network links present bandwidth asymmetry, i.e. the send and receive bandwidths of a link may be different. The nodes can overlap computation with at most one send and one receive operation. A centralized algorithm that maximizes the platform throughput under static conditions is presented. Thereafter, we propose several distributed heuristics making scheduling decisions based on information estimated locally. Extensive simulations demonstrate that distributed heuristics are better suited to cope with dynamic environments, but also compete well with centralized heuristics in static environments.

show abstract

Master-Slave Tasking on Asymmetric Networks

Banino-Rokkones

Beaumont

Natvig

2006

Euro-Par 2006 Parallel Processing

View full text Add to dashboard Cite

show abstract

Evolution of Competing Strategies in a Threshold Model for Task Allocation

Goldingay

Mourik

2010

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2010

View full text Add to dashboard Cite

Optimizing the Reliability of Streaming Applications Under Throughput Constraints

Benoît

Bouziane

Robert

2011

Int J Parallel Prog

View full text Add to dashboard Cite

Mapping a pipelined application onto a distributed and parallel platform is a challenging problem. The problem becomes even more difficult when multiple optimization criteria are involved, and when the target resources are heterogeneous (processors and communication links) and subject to failures. This paper investigates the problem of mapping pipelined applications, consisting of a linear chain of stages executed in a pipeline way, onto such platforms. The objective is to optimize the reliability under a performance constraint, i.e., while guaranteeing a threshold throughput. In order to increase reliability, we replicate the execution of stages on multiple processors. We compare interval mappings, where the application is partitioned into intervals of consecutive stages, with general mappings, where stages may be partitioned without any constraint, thereby allowing a better usage of processors and communication network capabilities. However, the price to pay for general mappings is a dramatic increase in the problem complexity. We show that computing the period of a given general mapping is an NP-complete problem, and we give polynomial bounds to determine a (conservative) approximated value. On the contrary, the period of an interval mapping obeys a simple formula, and we provide an optimal dynamic programming Part of this work has appeared in ISPDC'123 Int J Parallel Prog (2011) 39:584-614 585 algorithm for the bi-criteria interval mapping problem on homogeneous platforms. On the more practical side, we design a set of efficient heuristics, and we compare the performance of interval and general mapping strategies through extensive simulations.

show abstract

Bandwidth-aware resource allocation for heterogeneous computing systems to maximize throughput

Abstract: In

Cited by 16 publications

References 13 publications

Master-Slave Tasking on Asymmetric Networks

Master-Slave Tasking on Asymmetric Networks

Evolution of Competing Strategies in a Threshold Model for Task Allocation

Optimizing the Reliability of Streaming Applications Under Throughput Constraints

Contact Info

Product

Resources

About