Not sure where you take the 1000x improvement from? I was talking about a 
30x - and this was an ad hoc guess.

If you look around, there are comparisons which make this seem realistic 
(e.g., http://www.hs.uni-hamburg.de/DE/Ins/Per/Abhranil/summer_report.pdf), 
but this also shows it dependents very much on the task specifics. This 
would be the interesting question here, whether such a speed-up would be 
realistic.
(there the border is at a factor of 400, but this obviously depends on the 
specifics of the CPU and GPU compared)


Am Donnerstag, 9. Oktober 2014 11:33:27 UTC+2 schrieb Judson Wilson:
>
> I didn't notice this was in the original thread. A factor of 1000x 
> improvement? REALLY? I have a hard time believing it.
>
>
> On Thu, Oct 9, 2014 at 1:18 AM, Klaus <[email protected] <javascript:>> 
> wrote:
>
>> Your mileage may vary. 
>> For me, such a solution might mean a speedup of about 30 (given the 
>> number of graphics cores, the differences in performance, non-optimal 
>> parallelization, etc. - but it is a rather wild, but conservative guess). 
>> If you look at pricing on the cloud, using this might cost like 5-10 USD 
>> / hour (were also partial hours count). 
>> Given the number of runs one has to do to reach a reasonable result, this 
>> can easily go to dozens/hundreds of hours. This might be ok from your 
>> perspective, it seems like a bad deal from my point of view. (this is also 
>> why modern high-performance computers often take a GPU heavy approach)
>> So, I think, going GPU first is probably a good idea, then one might want 
>> to cascade it later with a multicomputer approach (AWS offers specific GPU 
>> instances for the cloud). 
>>
>> But all this is mute, the question is whether any one with the necessary 
>> expertise is pursuing this approach. 
>> Or perhaps someone has better data for estimating the kinds of results to 
>> be expected. 
>>
>> Klaus
>>
>>
>>
>> Am Mittwoch, 8. Oktober 2014 22:14:44 UTC+2 schrieb Judson Wilson:
>>>
>>> I think it would be more worthwhile to do a cloud based multi-computer 
>>> approach.
>>>
>>> On Wed, Oct 8, 2014 at 3:55 AM, Klaus <[email protected]> wrote:
>>>
>>>> Hi, 
>>>>
>>>> I was just wondering: was there any further efforts to do CUDA-based 
>>>> backtesting for JBT?
>>>>
>>>> Cheers
>>>>  Klaus
>>>>
>>>>
>>>> Am Donnerstag, 18. April 2013 03:44:58 UTC+2 schrieb Sheb Latsama:
>>>>
>>>>> I am looking into this, but it is still far from ready for prime 
>>>>> time.  I have a good speedup, but for some reason the results are 
>>>>> diverging 
>>>>> from the expected values in seemingly random ways.  I will update the 
>>>>> group 
>>>>> when I have something ready to share... it is still 'pre-alpha' at this 
>>>>> point.
>>>>>
>>>>> I asked Eugene to remove some info I shared with him on this topic as 
>>>>> it is premature at this point, and he was kind enough to do so.
>>>>>
>>>>> On Tuesday, April 16, 2013 6:56:40 AM UTC-7, Mick O'Donnell wrote:
>>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> 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.
>>>>>>
>>>>>> http://www.jcuda.org/
>>>>>>
>>>>>> regards,
>>>>>>
>>>>>> Michael
>>>>>>
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