NDLI: Exploiting concurrency among tasks in partitionable parallel processing systems

Content Provider	IEEE Xplore Digital Library
Author	Nation, W.G. Maciejewski, A.A. Siegel, H.J.
Copyright Year	1992
Description	Author affiliation: Endicott Eng. Lab., IBM Corp., NY, USA (Nation, W.G.)
Abstract	One benefit of partitionable parallel processing systems is their ability to execute multiple, independent tasks simultaneously. Previous work has identified conditions such that, when there are k tasks to be processed, partitioning the system such that all k tasks are processed simultaneously results in a minimum overall execution time. An alternate condition is developed that provides additional insight into the effects of parallelism on execution time. This result, and previous results, however, assume that execution times are data independent. It is shown that data-dependent tasks do not necessarily execute faster when processed simultaneously even if the condition is met. A model is developed that provides for the possible variability of a task's execution time and is used in a new framework to study the problem of finding an optimal mapping for identical, independent data-dependent execution time tasks onto partitionable systems. Extension of this framework to situations where the k tasks are non-identical is discussed.
Starting Page	30
Ending Page	38
File Size	904750
Page Count	9
File Format	PDF
ISBN	0818626720
DOI	10.1109/IPPS.1992.223076
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Concurrent computing Parallel processing Large-scale systems Laboratories Signal processing algorithms Signal processing Satellites Computational modeling Histograms Oceans
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Parallel numerical asynchronous iterative algorithms: Large scale experimentations

Concurrency characteristics in DSP programs

Parallel Algorithms for Large Scale Power System Dynamic Simulation

Towards efficient mapping in large-scale trace-driven parallel performance simulation

Benchmarking parallel simulation algorithms

Optimizing All-to-All Collective Communication by Exploiting Concurrency in Modern Networks

Flexible data parallel training of neural networks using MIMD-Computers

Massively Parallel Computation For Monte Carlo Device Simulation

On parallelization of neural classification algorithms

Exploiting concurrency among tasks in partitionable parallel processing systems

Similar Documents

Parallel numerical asynchronous iterative algorithms: Large scale experimentations

Concurrency characteristics in DSP programs

Parallel Algorithms for Large Scale Power System Dynamic Simulation

Towards efficient mapping in large-scale trace-driven parallel performance simulation

Benchmarking parallel simulation algorithms

Optimizing All-to-All Collective Communication by Exploiting Concurrency in Modern Networks

Flexible data parallel training of neural networks using MIMD-Computers

Massively Parallel Computation For Monte Carlo Device Simulation

On parallelization of neural classification algorithms

Exploiting concurrency among tasks in partitionable parallel processing systems