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» Optimizing for parallelism and data locality
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CJ
1999
87views more  CJ 1999»
15 years 4 months ago
Evolution-Based Scheduling of Computations and Communications on Distributed Memory Multicomputers
We present a compiler optimization approach that uses the simulated evolution (SE) paradigm to enhance the finish time of heuristically scheduled computations with communication t...
Mayez A. Al-Mouhamed
187
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IEEEPACT
2002
IEEE
15 years 10 months ago
A Framework for Parallelizing Load/Stores on Embedded Processors
Many modern embedded processors (esp. DSPs) support partitioned memory banks (also called X-Y memory or dual bank memory) along with parallel load/store instructions to achieve co...
Xiaotong Zhuang, Santosh Pande, John S. Greenland ...
NIPS
2007
15 years 6 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
AAAI
2010
15 years 6 months ago
Local Search in Histogram Construction
The problem of dividing a sequence of values into segments occurs in database systems, information retrieval, and knowledge management. The challenge is to select a finite number ...
Felix Halim, Panagiotis Karras, Roland H. C. Yap
TSMC
2011
324views more  TSMC 2011»
14 years 12 months ago
Genetic Algorithms With Guided and Local Search Strategies for University Course Timetabling
—The university course timetabling problem (UCTP) is a combinatorial optimization problem, in which a set of events has to be scheduled into time slots and located into suitable ...
Shengxiang Yang, Sadaf Naseem Jat