On 13.01.2011 01:49, Tom Rondeau wrote: > >From my experiments, I don't thinks its a A _and_ B situation. I think > if you have either A) a large amount of data _OR_ B) have to pound on > it furiously, you get a win. Most filters needed for normal comms is > not enough data or computation, but doing, maybe, a turbo product code > or some heavy compute task with normal amounts of data (say, blocks of > around 8k samples), you can get a win.
Even for FFT you have to check it carefully. I really lost time with the GPU. Some benchmarks only count kernel time without transfer time, some others compare an optimized CUFFT against a non-optimized CPU implementation. You have to compare GPU time including transfers against something like FFTW. After that, the speedup is not very high any more, depending on the transform size. To really boost your computations, more operations should be done on the same data set. I think FFT is not very suitable for GPU because of the butterfly structure (many data transfers between the blocks). Thinks like FEM (finite element) are more suitable, because differential equations are solved only on local and direct neighbor data. _______________________________________________ Discuss-gnuradio mailing list [email protected] http://lists.gnu.org/mailman/listinfo/discuss-gnuradio
