Computer Science Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1593

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An Immediate Concurrent Execution (ICE) Abstraction Proposal for Many-Cores
(2008-12) Vishkin, Uzi
Settling on a simple abstraction that programmers aim at, and hardware and software systems people enable and support, is an important step towards convergence to a robust many-core platform. The current paper: (i) advocates incorporating a quest for the simplest possible abstraction in the debate on the future of many-core computers, (ii) suggests “immediate concurrent execution (ICE)” as a new abstraction, and (iii) argues that an XMT architecture is one possible demonstration of ICE providing an easy-to-program general-purpose many-core platform.
A Reference Architecture for the Component Factory
(1991-03) Basili, Victor R.; Caldiera, Gianluigi
Using Simple Abstraction to Guide the Reinvention of Computing for Parallelism
(2009-02-06) Vishkin, Uzi
The sudden shift from single-processor computer systems to many-processor parallel computing systems requires reinventing much of Computer Science (CS): how to actually build and program the new parallel systems. CS urgently requires convergence to a robust parallel general-purpose platform that provides good performance and is easy to program. Unfortunately, this same objective has eluded decades of parallel computing research. Now, continued delays and uncertainty could start affecting important sectors of the economy. This paper advocates a minimalist stepping-stone: settle first on a simple abstraction that encapsulates the new interface between programmers, on one hand, and system builders, on the other hand. This paper also makes several concrete suggestions: (i) the Immediate Concurrent Execution (ICE) abstraction as a candidate for the new abstraction, and (ii) the Explicit Multi-Threaded (XMT) general-purpose parallel platform, under development at the University of Maryland, as a possible embodiment of ICE. ICE and XMT build on a formidable body of knowledge, known as PRAM (for parallel random-access machine, or model) algorithmics, and a latent, though not widespread, familiarity with it. Ease-of-programming, strong speedups and other attractive properties of the approach suggest that we may be much better prepared for the challenges ahead than many realize.