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Tomasz,
Please provide some insight here. Is this for real? If so then can
we all expect to see a future version of Amibroker that takes
advantage of this? I really want to believe this but it just seems to
good to be true.
Pete :-)
--- In amibroker@xxxxxxxxxxxxxxx, "Paul Ho" <paul.tsho@xxx> wrote:
>
> I'm very interested
> could you elaborate a bit more
> What model of Nvidia chipset are you using, and with how much memory?
> Not sure exactly what you mean when you say
> It uses AmiBroker to load the symbol data and perform calculations
> that do not depend on the optimization parameters. Once loaded into
> video memory, repeated passes can be made with different parameters,
> avoiding any overhead.
> Can you give me some examples. I presume when your dll is called. AB
passes
> one or more arrays of data belonging to 1 symbol, is that true?
> Not sure exactly what the rest mean either. How many functions are you
> running in your dll, and what does each of the do?
> Great of you to share your insight.
> Cheers
> Paul.
>
>
>
> _____
>
> From: amibroker@xxxxxxxxxxxxxxx [mailto:amibroker@xxxxxxxxxxxxxxx]
On Behalf
> Of dloyer123
> Sent: Tuesday, 5 August 2008 9:19 AM
> To: amibroker@xxxxxxxxxxxxxxx
> Subject: [amibroker] Freakishly fast backtest using 64 cores
>
>
>
> Greetings,
>
> I ported part of my AFL backtest code to a plugin, that takes
> advantage of the graphics math cores on the video card that are
> normally used for 3d graphics.
>
> I was able to get a several thousand fold performance improvement
> over AFL code alone.
>
> My goal was to reduce the 25 seconds AFL code alone uses for a single
> portfolio level back test to less than 1 second, allowing multi day
> optimization and walkforward runs to complete in a more reasonable
> time, and also just to see how fast I could get it to run.
>
> The backtest runs over 1 year of 5 minute bars for about 1000
> symbols. 1 year of data normally takes 25 seconds for AmiBroker
> alone, or 18 seconds for 6 months of data. A typical optimization
> run takes hundreds of these passes per walk forward step, taking
> hours.
>
> Using the Nvidia CUDA API, running on my mid range video card. It
> was much faster. Much, much, much faster. How fast?
>
> It reduced the run time from 25s to... 4.4ms. That is more than
> 200/s!
>
> I didnt believe the timing when I saw it at first. So, I put 1,000
> runs in a loop and sure enough, it ran 1,000 iterations in about 4
> 1/2 seconds. This far exceeded my gaol or expectations.
>
> The resulting trade list matches that obtained by the AFL version of
> this code.
>
> I estimate that it is processing 32GB of bar data/sec.
>
> Getting this to work at peak performance was tricky. Most of what I
> have learned about code optimization does not apply.
>
> It uses AmiBroker to load the symbol data and perform calculations
> that do not depend on the optimization parameters. Once loaded into
> video memory, repeated passes can be made with different parameters,
> avoiding any overhead.
>
> For non backtest/optimization runs, the code just evaluates one
> symbol and passes the data back to AmiBroker buy/sell/short/cover
> arrays, making it easy to test, validate and visualize the trades.
> There is very little performance gain in this case.
>
> There are problems, however. To run optimizations at peak speed, I
> can not use AmiBroker to calculate the optimization goal function.
> So, I am in the process of writing code to match signals and
> calculate the portfolio fitness function. Once I do this, I will be
> able to perform full optimizations and walk forwards at 3 orders of
> magnitude faster than is possible with AmiBroker alone.
>
> Also, this is not general purpose code. Changing the system code
> means changing a dll written in C. However, there is no reason that
> this could not be made more general.
>
> I have made some prototypes of "Cuda" versions of basic AFL
> functions. The idea is to queue the function calls into a definition
> executed by a micro kernel running on the graphics cores. The result
> would be the ability to use the full power of the graphics cores by
> modifying AFL code to use Cuda aware versions with no changes to C
> code. It would be an interesting, but big project.
>
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