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From: Kim K. T. <kue...@vo...> - 2010-03-19 08:05:19
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Hi Deepak, there are several ways to improve the performance. Before you do that i' ll suggest you to use boost::chrono to see where the bottleneck of your application is.http://svn.boost.org/svn/boost/sandbox/chrono/libs/chrono/doc/html/index.html It will measure the time you use for your application. For example. real 0.832s, cpu 0.813s (97.7%), user 0.813s, system 0.000s After that you can playing around by changing the container ( from vector to list or to quantlib::array, boost::array,...) Try to rewrite your payoff function. If all this dont help , i 'll suggest you to port your calculation into a graphic processor. To help you get starting see the article from Mark S. Joshi Graphical Asian Options Abstract We study the problem of pricing an Asian option using CUDA on a graphics processing unit. We demonstrate that it is possible to get accuracy of 2E-4 in less than a fiftieth of a second. Cheers, Kim Deepak schrieb: > > Hi Guys, > > I’m using *Monte Carlo engine and Path Generators* to price some > option types, I want to know what steps should I take to reduce the > computation time, or I can say I want to improve performance, I know > it all depends on the number of iterations, but I can’t reduce it, I > want other options like distributed/Parallel/Multithreading or > anything similar, to price my options, if there is anything already > done in this direction please tell me, > > I want you guys to give your thoughts even if I’ll have to implement, > I want to discuss first, QuantLib is a great library may be I can > contribute, Please give your inputs. > > Thanks & Regards, > *Deepak* > > > |