| Re: CUDA version of RANDOMN? [message #61999 is a reply to message #61998] |
Fri, 15 August 2008 10:15   |
wlandsman
Messages: 743
Registered: June 2000
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Senior Member |
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On Aug 15, 11:28 am, wlandsman <wlands...@gmail.com> wrote:
> On Aug 15, 11:16 am, "hotplainr...@gmail.com" <hotplainr...@gmail.com>
> wrote:
>
>
>
>> On Aug 16, 12:28 am, wlandsman <wlands...@gmail.com> wrote:
>
>>> On Aug 15, 10:11 am, "hotplainr...@gmail.com" <hotplainr...@gmail.com>
>>> wrote:
>
>>>> Hey guys,
>
>>>> I need to write a kernel to replace the IDL RANDOMN POISSON
>
>>>> for loop
>>>> for loop
>>>> for loop
>>>> c = data[x,y,b]
>>>> if c gt 0.0 then begin
>>>> n = RANDOMN( seedP, POISSON=c )
>>>> endif else begin
>>>> n = 0
>>>> endelse
>>>> data[x,y,b] = n
>>>> endfor
>>>> endfor
>>>> endfor
>
>>>> Could someone point out an example code of how RANDOMN POISSON so that
>>>> I can implement it in CUDA?
>
>>> Your best bet is to probably look at the Poisson generating algorithm
>>> in "Numerical Recipes in C" if you are going to implement it CUDA.
>
>>> I have implemented the "Numerical Recipes in C" algorithm into the IDL
>>> procedure poidev.pro at http://idlastro.gsfc.nasa.gov/ftp/pro/math/poidev.pro.
>>> Although poidev.pro is normally slower than calling randomn(POISSON=),
>>> it has advantages for just the problem you describe, which can be
>>> written as simply
>
>>> data = poidev(data)
>
>>> rather than using a triple FOR loop. --Wayne
>
>> Thanks for the reply. I was about to use your code until I discovered
>> the problem of achieving this.
>
>> c = data[x,y,b]
>> if c gt 0.0 then begin
>> n = RANDOMN( seedP, POISSON=c )
>> endif else begin
>> n = 0
>> endelse
>
>> I guess the only way is to code a poisson kernel and then do tiling on
>> the data.
>
> Yes, that does mean the code becomes 3 lines instead of 1
>
> g = where( data GT 0, Ng ,complement=g1, Ncomplement=Ng1)
> if Ng GT 0 then data[g] = poidev(data[g])
> if Ng1 GT 0 then data[g1] = 0
>
> --Wayne
I still made it too complicated. poidev automatically sets any
negative numbers to zero (since the Poisson distribution is not
defined for negative numbers). So the original code
data = poidev(data)
should be fine. --Wayne
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