Trellis-SDP: A simple data-parallel programming interface

Some datasets and computing environments are inherently distributed. For example, image data may be gathered and stored at different locations. Although data parallelism is a well-known computational model, there are few programming systems that are both easy to program (for simple applications) and...

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Bibliographic Details
Published in:Workshops on Mobile and Wireless Networking/High Performance Scientific, Engineering Computing/Network Design and Architecture/Optical Networks Control and Management/Ad Hoc and Sensor Networks/Compil pp. 498 - 505
Main Authors: Meng Ding, Lu, P.
Format: Conference Proceeding
Language:English
Published: IEEE 2004
Subjects:
Application software
Communication system security
Content based retrieval
Distributed computing
Information retrieval
Parallel processing
Parallel programming
Sorting
Wide area networks
Workstations
ISBN:9780769521985, 0769521983
ISSN:1530-2016
Online Access:Get full text
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Summary:Some datasets and computing environments are inherently distributed. For example, image data may be gathered and stored at different locations. Although data parallelism is a well-known computational model, there are few programming systems that are both easy to program (for simple applications) and can work across administrative domains. We have designed and implemented a simple programming system, called Trellis-SDP, that facilitates the rapid development of data-intensive applications. Trellis-SDP is layered on top of the Trellis infrastructure, a software system for creating overlay metacomputers: user-level aggregations of computer systems. Trellis-SDP provides a master-worker programming framework where the worker components can run self-contained, new or existing binary applications. We describe two interface functions, namely trellis scan() and trellis gather(), and show how easy it is to get reasonable performance with simple data-parallel applications, such as Content Based Image Retrieval (CBIR) and Parallel Sorting by Regular Sampling (PSRS).
ISBN:9780769521985
0769521983
ISSN:1530-2016
DOI:10.1109/ICPPW.2004.1328061