Cited By
View all- Desmettre SKorn RVarela JWehn N(2016)Nested MC-Based Risk Measurement of Complex Portfolios: Acceleration and Energy EfficiencyRisks10.3390/risks40400364:4(36)Online publication date: 18-Oct-2016
Optimization strategies for portable code for Monte Carlo-based value-at-risk systems
Authors: 
Javier Alejandro Varela, Claus Kestel, Christian De Schryver, Norbert Wehn, Sascha Desmettre, Ralf KornAuthors Info & Claims
Article No.: 3, Pages 1 - 8
Abstract
Value-at-risk (VaR) computations are one important basic element of risk analysis and management applications. On the one hand, risk management systems need to be flexible and maintainable, but on the other hand they require a very high computational power. In general, accelerators provide high speedups, but come with a limited flexibility. In this work, we investigate two approaches towards portable and fast code for VaR computations on heterogeneous platforms: operator tuning and the use of OpenCL. We show that operator tuning can save up one third of run time on CPU-based systems in the calibration step. For OpenCL, we present a detailed analysis of run time on CPU, GPU, and Xeon Phi, and evaluate its portability. We also find that the same code runs up to 12x faster in a VaR setting with an accelerator card being present, without any code changes required.
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Published In
November 2015
61 pages
ISBN:9781450340151
DOI:10.1145/2830556
Copyright © 2015 ACM.
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Published: 15 November 2015
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SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis
November 15, 2015
Texas, Austin
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View all- Desmettre SKorn RVarela JWehn N(2016)Nested MC-Based Risk Measurement of Complex Portfolios: Acceleration and Energy EfficiencyRisks10.3390/risks40400364:4(36)Online publication date: 18-Oct-2016
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