The paper proposes an approach for parallelization of computations across a collection of clusters with heterogeneous nodes with both GPUs and CPUs. The proposed system partitions input data into chunks and assigns to par- ticular devices for processing using OpenCL kernels defined by the user. The sys- tem is able to minimize the execution time of the application while maintaining the power consumption of the utilized GPUs and CPUs below a given threshold. We present real measurements regarding performance and power consumption of various GPUs and CPUs used in a modern parallel system. Furthermore we show, for a parallel application for breaking MD5 passwords, how the execution time of the real application changes with various upper bounds on the power consumption.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-642-45249-9_5
- Category
- Aktywność konferencyjna
- Type
- materiały konferencyjne indeksowane w Web of Science
- Language
- angielski
- Publication year
- 2014
