Computational challenges in portfolio management
Computing in Science and Engineering
Performance evaluation of GPUs using the RapidMind development platform
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Maxwell - a 64 FPGA Supercomputer
AHS '07 Proceedings of the Second NASA/ESA Conference on Adaptive Hardware and Systems
Sampling from the Multivariate Gaussian Distribution using Reconfigurable Hardware
FCCM '07 Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
A hardware gaussian noise generator using the wallace method
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A mixed precision Monte Carlo methodology for reconfigurable accelerator systems
Proceedings of the ACM/SIGDA international symposium on Field Programmable Gate Arrays
FPGA acceleration of CDO pricing based on correlation expansions
ACM SIGARCH Computer Architecture News - ACM SIGARCH Computer Architecture News/HEART '12
WHPCF '13 Proceedings of the 6th Workshop on High Performance Computational Finance
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The last decade has seen a significant growth in the financial industry. The recent widespread use of Internet technology has increased the accessibility of the general population to financial data, thereby increasing the average portfolio size. This increase, compounded by the need for accurate real-time results, has led to a rising demand for faster risk simulations. Often, accurately pricing widespread instruments, such as Collateralized Debt Obligations (CDOs), can take excessively long due to their multifactor assets dependency. We present a hardware implementation for a MultiFactor Gaussian Copula (MFGC) CDO pricing algorithm. Through a detailed benchmark exploration we demonstrate how reconfigurable hardware could be used to exploit fine-grain parallelism. Our results show that our implementation mapped onto a Xilinx Virtex 5 (XC5VSX50T) FPGA is over 71 times faster than corresponding software running on a single core 3.4 GHz Intel Xeon processor.