| Re: CUDA version of RANDOMN? [message #61998] |
Fri, 15 August 2008 17:58 |
hotplainrice@gmail.co
Messages: 15
Registered: July 2008
|
Junior Member |
|
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On Aug 16, 3:15 am, wlandsman <wlands...@gmail.com> wrote:
> 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
Thanks Wayne, that function helped me decrease times by half and
provided me with some code if I want to implement it in GPUs.
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| 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
|
Senior Member |
|
|
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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| Re: CUDA version of RANDOMN? [message #62002 is a reply to message #61999] |
Fri, 15 August 2008 08:28 |
wlandsman
Messages: 743
Registered: June 2000
|
Senior Member |
|
|
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
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| Re: CUDA version of RANDOMN? [message #62003 is a reply to message #62002] |
Fri, 15 August 2008 08:16 |
hotplainrice@gmail.co
Messages: 15
Registered: July 2008
|
Junior Member |
|
|
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.
|
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| Re: CUDA version of RANDOMN? [message #62004 is a reply to message #62003] |
Fri, 15 August 2008 08:14 |
hotplainrice@gmail.co
Messages: 15
Registered: July 2008
|
Junior Member |
|
|
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
|
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| Re: CUDA version of RANDOMN? [message #62005 is a reply to message #62004] |
Fri, 15 August 2008 07:28 |
wlandsman
Messages: 743
Registered: June 2000
|
Senior Member |
|
|
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
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