On 12.01.2011 14:25, Michael Dickens wrote:
> the CPU).  I think that if a GPU can be used, it will be most effective in 
> things like filterbanks, or when searching for packets (via their unique sync 
> sequence, so matched filtering), or very large FIR filters -- places where a 
> LOT of computations and data must be processed and can be parallelized 
> easily.  In my initial testing, doing something "simple" 

Is there an efficient parallel FIR implementation for CUDA? You need only few 
operations on
a large set of data. So, isn't this too much for the stream-processor 
local-memory?
If GPU global memory has to be used, this would lead to a slower concurrent 
access.
And then there is still the transfer time from/to the computer RAM.
It would be great to have a fast filter, but is it really faster than an 
optimized SSE CPU FIR?
I had the feeling, that the ratio of computing operations vs. number of samples 
has to be
high for a significant GPU vs. CPU speedup.
I'm curious about how much speedup you can achieve for FIR filters
(let's say large/sharp filters of 1024 taps).


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