Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures
| Autor: | Przemyslaw Stpiczynski |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Pseudorandom number generator
020203 distributed computing Multi-core processor Xeon Computer science Computation 02 engineering and technology Parallel computing Software_PROGRAMMINGTECHNIQUES ComputerSystemsOrganization_PROCESSORARCHITECTURES Theoretical Computer Science Computational science Hardware and Architecture 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Monte Carlo integration Implementation Algorithm Software Xeon Phi Information Systems |
| Zdroj: | The Journal of Supercomputing. 74:936-952 |
| ISSN: | 1573-0484 0920-8542 |
| DOI: | 10.1007/s11227-017-2172-x |
| Popis: | The aim of this paper is to show that the multidimensional Monte Carlo integration can be efficiently implemented on computers with modern multicore CPUs and manycore accelerators including Intel MIC and GPU architectures using a new vectorized version of LCG pseudorandom number generator which requires limited amount of memory. We introduce two new implementations of the algorithm based on directive-based parallel programming standards OpenMP and OpenACC and consider their performance using Hockney–Jesshope theoretical model of vector computations. We also present and discuss the results of experiments performed on dual-processor Intel Xeon E5-2670 computers with Intel Xeon Phi 7120P and NVIDIA K40m. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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