๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

On Multicast Algorithms for Heterogeneous Networks of Workstations

โœ Scribed by R. Libeskind-Hadas; J.R.K. Hartline; P. Boothe; G. Rae; J. Swisher


Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
197 KB
Volume
61
Category
Article
ISSN
0743-7315

No coin nor oath required. For personal study only.

โœฆ Synopsis


Networks of workstations (NOWs) provide an economical platform for high performance parallel computing. Such networks may comprise a variety of different types of workstations and network devices. This paper addresses the problem of efficient multicast in a heterogeneous communication model. Although the problem of finding optimal multicast schedules is known to be NP-complete in this model, a greedy algorithm has been shown experimentally to find good solutions in practice. In this paper we show that the greedy algorithm finds provably near-optimal schedules in polynomial time and that optimal schedules can be found in polynomial time when the number of distinct types of workstations is bounded by a constant. Specifically, this paper presents three results. First, when there are n workstations of some constant k distinct types, the greedy algorithm is shown to find schedules that complete at most a constant additive term later than optimal. Second, an algorithm is given that finds optimal schedules in time O(n 2k ). Finally, it is shown that for the general problem, the greedy algorithm finds solutions that complete the multicast in at most twice the optimal time.


๐Ÿ“œ SIMILAR VOLUMES


Stardust: An Environment for Parallel Pr
โœ Gilbert Cabillic; Isabelle Puaut ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 328 KB

This paper describes Stardust, an environment for parallel programming on networks of heterogeneous machines. Stardust runs on distributed memory multicomputers and networks of workstations. Applications using Stardust can communicate both through message-passing and through distributed shared memor

Application Level Fault Tolerance in Het
โœ Adam Beguelin; Erik Seligman; Peter Stephan ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 425 KB

We have explored methods for checkpointing and restarting processes within the distributed object migration environment (Dome), a C++ library of data parallel objects that are automatically distributed over heterogeneous networks of workstations (NOWs). System level checkpointing methods, although t

Coordinating Parallel Processes on Netwo
โœ Xing Du; Xiaodong Zhang ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 355 KB

The network of workstations (NOW) we consider for scheduling is heterogeneous and nondedicated, where computing power varies among the workstations and local and parallel jobs may interact with each other in execution. An effective NOW scheduling scheme needs sufficient information about system hete

Optimal Communication Algorithms for Het
โœ Xiaodong Wang; Vwani P. Roychowdhury ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 330 KB

We present efficient algorithms for designing optimal collective communication primitives for cluster-based heterogeneous computing across Asynchronous Transfer Mode (ATM) networks. The virtual path (VP) concept is known to be a powerful transport mechanism for ATM networks. In many parallel process

Usefulness of adaptive load sharing for
โœ Clarke, Sheldon; Dandamudi, Sivarama P. ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 128 KB

Networks of workstations (NOWs) can be used for parallel processing by using public domain software like PVM. However, NOW-based parallel processing suffers from node heterogeneity, background load variations, and high-latency, low-bandwidth communication network. Previous studies on load sharing in

Parallel Labeling of Three-Dimensional C
โœ Felipe Knop; Vernon Rego ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 323 KB

Cluster algorithms have application in diverse areas, including statistical mechanics of polymer solutions, spin models in physics, and the study of ecological systems. Most parallel cluster labeling algorithms are designed for SIMD and MIMD multiprocessors and based on relaxation methods. We presen