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» Dynamic Scheduling with Genetic Programming
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ATAL
2005
Springer
13 years 10 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ECRTS
2010
IEEE
13 years 6 months ago
Making DRAM Refresh Predictable
Embedded control systems with hard real-time constraints require that deadlines are met at all times or the system may malfunction with potentially catastrophic consequences. Sched...
Balasubramanya Bhat, Frank Mueller
CORR
2008
Springer
185views Education» more  CORR 2008»
13 years 5 months ago
Realizing Fast, Scalable and Reliable Scientific Computations in Grid Environments
The practical realization of managing and executing large scale scientific computations efficiently and reliably is quite challenging. Scientific computations often invo...
Yong Zhao, Ioan Raicu, Ian T. Foster, Mihael Hateg...
COMPUTER
2002
103views more  COMPUTER 2002»
13 years 4 months ago
SimpleScalar: An Infrastructure for Computer System Modeling
tail defines the level of abstraction used to implement the model's components. A highly detailed model will faithfully simulate all aspects of machine operation, whether or n...
Todd M. Austin, Eric Larson, Dan Ernst
MICRO
2005
IEEE
114views Hardware» more  MICRO 2005»
13 years 10 months ago
Address-Indexed Memory Disambiguation and Store-to-Load Forwarding
This paper describes a scalable, low-complexity alternative to the conventional load/store queue (LSQ) for superscalar processors that execute load and store instructions speculat...
Sam S. Stone, Kevin M. Woley, Matthew I. Frank