34 search results - page 1 / 7 » Machine learning based online performance prediction for run... |
ISPASS
2009
IEEE
2009
IEEE
Machine learning based online performance prediction for runtime parallelization and task scheduling
13 years 11 months ago
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
PPOPP
2009
ACM
14 years 5 months ago
2009
ACM
The efficient mapping of program parallelism to multi-core processors is highly dependent on the underlying architecture. This paper proposes a portable and automatic compiler-bas...
ICPADS
2010
IEEE
13 years 2 months ago
2010
IEEE
To fully tap into the potential of heterogeneous machines composed of multicore processors and multiple accelerators, simple offloading approaches in which the main trunk of the ap...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
CLUSTER
2002
IEEE
13 years 4 months ago
2002
IEEE
Abstract. We describe and evaluate the Running Time Advisor (RTA), a system that can predict the running time of a compute-bound task on a typical shared, unreserved commodity host...