A bridging model for parallel computation
Communications of the ACM
Direct bulk-synchronous parallel algorithms
Journal of Parallel and Distributed Computing
A parallel quasi-Monte Carlo approach to pricing multidimensional American options
International Journal of High Performance Computing and Networking
High Performance Implementation of Binomial Option Pricing
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
Parallelization of Pricing Path-Dependent Financial Instruments on Bounded Trinomial Lattices
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part II
Distributed Asynchronous Iterative Algorithms: New Experimentations with the Jace Environment
GPC '09 Proceedings of the 4th International Conference on Advances in Grid and Pervasive Computing
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Cache-optimal algorithms for option pricing
ACM Transactions on Mathematical Software (TOMS)
Evaluating multicore algorithms on the unified memory model
Scientific Programming - Software Development for Multi-core Computing Systems
APPT'07 Proceedings of the 7th international conference on Advanced parallel processing technologies
Option pricing, maturity randomization and distributed computing
Parallel Computing
Parallel binomial valuation of american options with proportional transaction costs
APPT'11 Proceedings of the 9th international conference on Advanced parallel processing technologies
Parallel computing for option pricing based on the backward stochastic differential equation
HPCA'09 Proceedings of the Second international conference on High Performance Computing and Applications
| Hi-index | 0.00 |
We introduce an architecture independent approach in describing how computations such as those involved in American or European-style option price valuations can be performed in parallel under the binomial tree model. We describe a latency-tolerant parallel algorithm for the multiplicative binomial tree option pricing model. The algorithm is described and analyzed in an architecture independent setting and performance characteristics are expressed in terms of problem size n, the time horizon, and the parameters p, L and g of the bulk-synchronous parallel model of computation. The algorithm achieves optimal theoretical speedup and is within a 1 + o(1) multiplicative factor of the corresponding sequential method. An experimental study of an implementation of the algorithm on a cluster of PC workstations is also undertaken to examine the latency-tolerance of our approach. The implementation with only a recompilation of the same source code works under two diverse parallel programming libraries namely, MPI and BSPlib, thus making it not only architecture but also communication library independent.