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Towards Automated Benchmarking and Evaluation of Heterogeneous Systems in Finance

  • Christian De Schryver
  • Carolina Pereira Nogueira

Abstract

Benchmarking and fair evaluation of computing systems is a challenge for High Performance Computing (HPC) in general, and for financial systems in particular. The reason is that there is no optimal solution for a specific problem in most cases, but the most appropriate models, algorithms, and their implementations depend on the desired accuracy of the result or the input parameters, for instance. In addition, flexibility and development effort of those systems are important metrics for purchasers from the finance domain and thus need to be well-quantified. In this section we introduce a precise terminology for separating the problem, the employed model, and a solution that consists of a selected algorithm and its implementation. We show how the design space (the space of all possible solutions to a problem) can be systematically structured and explored. In order to evaluate and characterize systems independent of their underlying execution platforms, we illustrate the concept of application-level benchmarks and summarize the state-of-the-art for financial applications. In particular for heterogeneous and Field Programmable Gate Array (FPGA)-accelerated systems, we present a framework structure for automatically executing and evaluating such benchmarks. We describe the framework structure in detail and show how this generic concept can be integrated with existing computing systems. A generic implementation of this framework is freely available for download.

Keywords

Monte Carlo Design Space Option Price Field Programmable Gate Array Software Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We gratefully acknowledge the partial financial support from the Center of Mathematical and Computational Modelling (CM)2 of the University of Kaiserslautern, from the German Federal Ministry of Education and Research under grant number 01LY1202D, and from the Deutsche Forschungsgemeinschaft (DFG) within the RTG GRK 1932 “Stochastic Models for Innovations in the Engineering Sciences”, project area P2. The authors alone are responsible for the content of this work. Furthermore, we thank Gordon Inggs from Imperial College London for his helpful inputs related to the current benchmark state and scheduler expertise.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Christian De Schryver
    • 1
  • Carolina Pereira Nogueira
    • 1
  1. 1.Microelectronic Systems Design Research GroupUniversity of KaiserslauternKaiserslauternGermany

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