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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 9 days ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
CLUSTER
2003
IEEE
16 years 2 days ago
Improving the Performance of MPI Derived Datatypes by Optimizing Memory-Access Cost
The MPI Standard supports derived datatypes, which allow users to describe noncontiguous memory layout and communicate noncontiguous data with a single communication function. Thi...
Surendra Byna, William D. Gropp, Xian-He Sun, Raje...
IEEEPACT
2002
IEEE
15 years 11 months ago
Cost Effective Memory Dependence Prediction using Speculation Levels and Color Sets
Memory dependence prediction allows out-of-order issue processors to achieve high degrees of instruction level parallelism by issuing load instructions at the earliest time withou...
Soner Önder
HPCA
2001
IEEE
16 years 7 months ago
Automatically Mapping Code on an Intelligent Memory Architecture
This paper presents an algorithm to automatically map code on a generic intelligent memory system that consists of a host processor and a simpler memory processor. To achieve high...
Jaejin Lee, Yan Solihin, Josep Torrellas
APLAS
2009
ACM
16 years 1 months ago
Fractional Ownerships for Safe Memory Deallocation
We propose a type system for a programming language with memory allocation/deallocation primitives, which prevents memory-related errors such as double-frees and memory leaks. The ...
Kohei Suenaga, Naoki Kobayashi