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ISPASS
2009
IEEE
14 years 26 days 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...
CLUSTER
2011
IEEE
12 years 5 months ago
Exploring Fine-Grained Task-Based Execution on Multi-GPU Systems
Using multi-GPU systems, including GPU clusters, is gaining popularity in scientific computing. However, when using multiple GPUs concurrently, the conventional data parallel GPU...
Long Chen, Oreste Villa, Guang R. Gao
EUROPAR
2010
Springer
13 years 6 months ago
Multi-GPU and Multi-CPU Parallelization for Interactive Physics Simulations
Today, it is possible to associate multiple CPUs and multiple GPUs in a single shared memory architecture. Using these resources efficiently in a seamless way is a challenging issu...
Everton Hermann, Bruno Raffin, François Fau...
IJPP
2010
156views more  IJPP 2010»
13 years 3 months ago
ForestGOMP: An Efficient OpenMP Environment for NUMA Architectures
Exploiting the full computational power of current hierarchical multiprocessor machines requires a very careful distribution of threads and data among the underlying non-uniform ar...
François Broquedis, Nathalie Furmento, Bric...
IPPS
2006
IEEE
14 years 2 days ago
Dynamic multi phase scheduling for heterogeneous clusters
Distributed computing systems are a viable and less expensive alternative to parallel computers. However, concurrent programming methods in distributed systems have not been studi...
Florina M. Ciorba, Theodore Andronikos, Ioannis Ri...