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Dell has 3 off the shelf
> laptops in their entertainment/performance range that use GeForce
> 8600M and 8700M with 256MB & 2*2456MB (min 256 required for CUDA?)
Mobile ones are very poor cousins. Belive me. I own brand new notebook (ASUS) with GeForce8600M
and it is SLOW in 3D. I mean SLOW. Did I mention that it is SLOW?
In 3D Mark it gets the same results as my 3 year old desktop 6600GT.
Best regards,
Tomasz Janeczko
amibroker.com
----- Original Message -----
From: "brian_z111" <brian_z111@xxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
Sent: Tuesday, August 12, 2008 12:40 AM
Subject: [amibroker] Re: Freakishly fast backtest using 64 cores
> DL
>
>
> I am following at the top level and understand what you are doing OK
> (you make me wish I had learnt programming/IT).
>
> I like your CPU.
>
> Allowing niche trading is what AB is all about?
>
> I'll put my money on MS/"general purpose computing on GPU" - I don't
> think the masses are in love with MS but for 80% of people who can do
> 80% of what they want with MS the price to move elsewhere is too
> high - they are just in love with max output for min input.
>
> If you go to the trouble to write a plug-in do you think it will be
> around long/require much ongoing support from you?
>
> I can see the benefits of the speed - for a group of traders it is a
> definite edge they would have for a year or two (I don't think any
> other trading software will be seeing this for a while? - especially
> in the AT area where more crunching could be done fast enough to keep
> up with live data.
>
> I don't blame Tomasz for not sitting his backside on the cutting
> edge - too dangerous for developers with long term clientele.
>
> Not having a go at Tomasz - to clarify - Tomeasz said GEForce 8800
> can't be put in a notebook?
>
> To my understanding there seems to be a reasonable number of laptops
> around that could use your method e.g. Dell has 3 off the shelf
> laptops in their entertainment/performance range that use GeForce
> 8600M and 8700M with 256MB & 2*2456MB (min 256 required for CUDA?)
>
> I looked at the GeF links in Paul's post but they didn't have much
> specific info there that I could see - I assume the above cards wiil
> run your system.
>
> I am not a buyer for now but good luck with it and what you have done
> already is a good contribution to AB - once someone on the block has
> a new super-dooper gadget pretty soon the neighbours want one too and
> demand grows.
>
> brian_z
>
>
>
> --- In amibroker@xxxxxxxxxxxxxxx, "dloyer123" <dloyer123@xxx> wrote:
>>
>> This uses the mid range video card that happened to come with my
>> system, a 9800GT. The newer 260 and 280 cards are 3 to 4 times
>> faster. The 260 can be found at best buy for $300. Some laptops
>> have compatible cards as well.
>>
>> The video card has its own memory, mine has 512MB, some have as
> much
>> as 1GB. This memory is very fast, once it is loaded from the main
>> system. Nvidia has a professional line of products that have much
>> more memory.
>>
>> Get get the best performance, my AFL code makes one pass over the
>> data, calling a Dll. The Dll takes all of the data needed by the
>> calculation and loads a copy to the video card. This upload is
> slow,
>> the entire upload takes about 45 seconds for all 1000 symbols.
>>
>> Once all of the data is uploaded, the Dll loads a "kernel" into the
>> graphics cores that perform the actual computation and generates
> the
>> trade list. This part is very fast and performs all of the same
>> functions that my AFL version does. The resulting trade list is
> the
>> same.
>>
>> Because the data loaded into video memory, it can be resused for
> many
>> passes over the data with different optimization values. So,
>> hundreds of combinations of optimization values can be tried per
>> second.
>>
>> For non optimization runs, the Dll just loads one symbol into video
>> memory and processes it. Counting the overhead of moving data to
> the
>> video card and extracting the trade list for a single symbol, the
>> result is similar to AFL code alone. This lets me test the code
> and
>> make sure it is correct.
>>
>> This approach works best when the data only needs to be loaded
> once,
>> then "resused" many times. It also works best when there is a lot
> of
>> data to work with.
>>
>> What is more interesting to me and what would be more useful for
>> others would be a general drive that requires no Dll changes to
>> modify the system. The performance would not be as good as hand
>> optimized code, but would still be much better than AFL code
> alone.
>> It would take trading system design to a whole new level. It would
>> provide enough performance to make working with Intra day data as
>> easy as daily data is today.
>>
>> Writing such a driver would be hard, but I have already done some
>> prototypes and design work. I am tempted to do it for my own use.
>> If I made it available to others supporting it would be a PITA.
>>
>>
>>
>>
>> --- In amibroker@xxxxxxxxxxxxxxx, "Paul Ho" <paul.tsho@> 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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