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ISPASS
2009
IEEE
14 years 2 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
BMCBI
2010
218views more  BMCBI 2010»
13 years 7 months ago
Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets
Background: Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve...
Michael Scharfe, Rainer Pielot, Falk Schreiber
ICFP
2004
ACM
14 years 7 months ago
Making a fast curry: push/enter vs. eval/apply for higher-order languages
Higher-order languages that encourage currying are implemented using one of two basic evaluation models: push/enter or eval/apply. Implementors use their intuition and qualitative...
Simon Marlow, Simon L. Peyton Jones
HIPEAC
2005
Springer
14 years 1 months ago
A Practical Method for Quickly Evaluating Program Optimizations
This article aims at making iterative optimization practical and usable by speeding up the evaluation of a large range of optimizations. Instead of using a full run to evaluate a s...
Grigori Fursin, Albert Cohen, Michael F. P. O'Boyl...
CASES
2000
ACM
13 years 11 months ago
Flexible instruction processors
This paper introduces the notion of a Flexible Instruction Processor (FIP) for systematic customisation of instruction processor design and implementation. The features of our app...
Shay Ping Seng, Wayne Luk, Peter Y. K. Cheung