Exploration of Parallelization Frameworks for Computational Finance
R. Krishnamurthy, Ikubin Chin, Anjil Chinnapatlolla · 2012
This paper presents a comparison of parallelization frameworks for efficient execution of computational finance workloads. We use a Value-at-Risk (VaR) workload to evaluate OpenCL and OpenMP parallelization frameworks on multi-core CPUs as opposed to GPUs. In addition, we study the impact of SMT on performance using GCC (4.4) and IBM XLC (11.01) compilers for both single-precision and double-precision codes. We use an 8-core, 4-way SMT IBM Power7 with Linux (RHEL 6.0, 2.6.32 kernel) to evaluate OpenCL and OpenMP. Using the IBM XLC compiler, 2-way SMT is able to provide over 30% average improvement as compared to 1 SMT thread per core, whereas, 4-way SMT is able to provide over 50% average improvement as compared to 1 SMT thread per core.