Accelerating financial code through parallelisation and source-level optimisation

Nan Zhang, Ka Lok Man

Research output: Contribution to journalConference articlepeer-review


In this paper we summarise the experiences we obtained during past years in accelerating financial code through parallelisation and source-level optimisation. We have been focusing on developing optimised parallel programs to speedup financial computations where either binomial tree method or Monte Carlo simulation was applicable. The parallelisation was through explicit POSIX multi-threading on x86 shared-memory multi-processor systems. The source-level optimisations we found most useful were data structure optimisation and elimination of common sub-expressions.

Original languageEnglish
JournalLecture Notes in Engineering and Computer Science
Issue numberJanuary
Publication statusPublished - 2014
EventInternational MultiConference of Engineers and Computer Scientists, IMECS 2014 - Kowloon, Hong Kong
Duration: 12 Mar 201414 Mar 2014


  • Binomial tree method
  • Monte Carlo simulation
  • POSIX multithreading
  • Parallel computing
  • Source code optimisation

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