Hi ,
  My area of expertise is Big Data and distributed computation. I am just
curious : Using Cuda you'll still stay in the context of single box , but
using such framework like Storm (CEP) http://storm-project.net/ can process
simultaneously in different machines. Does it make sense to use
JbookTrader in context of distributed environment?


On Tue, Apr 16, 2013 at 5:39 PM, Eugene Kononov <[email protected]>wrote:

>
> Just wondering if anyone has looked at use parallel processing for
>> optimizing strategies yet. I've been using the NVIDIA's CUDA library for
>> other heavy lifting jobs with good results. There's a project called JCUDA
>> which supplies a Runtime API with Java bindings for CUDA. If no one has
>> written anything for this yet, I may take it on as a side project.
>>
>>
>
> Yes, we are actively working on this. We are using aparapi:
> https://code.google.com/p/aparapi/
>
> Riunning the JBT optimization on he high end GPU (AMD Radeon 7900 series)
> indicates a speedup in the order of 1000 times faster. The big drawback is
> that it required a complete re-write of the multiple JBT classes,
> essentially flattening the object-oriented model into array processing of
> this type:
>
> final float inA[] = .... // get a float array of data from somewhere
> final float inB[] = .... // get a float array of data from somewhere 
> (inA.length==inB.length)
> final float result = new float[inA.length];
>
> for (int i=0; i<array.length; i++){
>
>     result[i]=intA[i]+inB[i];
> }
>
> What kind of speed up do you get with CUDA/NVidia? How much modifications to 
> the JBT code did it require?
>
>
>
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