![]() ![]() The N I'm interested in (as it is used in the ARM app) isĪ single app run processes many transforms of this length on different input data, so it's ok to generate an FFT "plan" and do other setup work up front which can even take some time and I would not consider this part of the runtime to be compared, so in FFTW this looks like this:įftwf_plan fftwf_plan_dft_r2c_1d(int N, float *in, fftwf_complex *out, unsigned flags) įftwf_plan can be an object containing whatever the plan needs to store I think a subset of the FFTW API would be a good template, but if some deviation from it is goo for performance, that would be fine as well. ![]() Imagine the power if they were all connected! Can you provide a pointer to the FFT API and functional call that needs to be implemented (+range of N). HBE Bikeman Posts: 52 Joined: Wed 8:55 pmĪolofsson wrote:Cool! If you improve the FFT for the raspi that would be a great service, since there are about 2M of those in the field. I might be willing to make a formal bet out of it, with (say) a crate of beer as the prize. If anyone thinks he/she can do a 3*2^22 real-to-complex FFT (single precision) faster on the Parallella than the fatest version using the RaspiPi's GPU, please let me know. My personal goal is to make an accelerated version of the "Binary Pulsar Search" app that needs a length 3*2^22 real-to-complex FFT for both the Raspi and the Parallella.Īt the moment I am quite sure the Raspi GPU will beat the 16 core Epiphany. The one none-graphics application that AFAIK has been implemented on the Raspberry Pi GPU so far is FFT. Having said that, the Raspi GPU is not intended for general purpose computing, and that's where the Parallella shines and is innovative, and that's the reason I backed the project and have not regretted it. The GPU on the Raspi SoC is actually quite powerful, it should actually be in the same ballpark as the 16 core Parallella (the Raspi GPU is quoted with a (yeah, mythical) theoretical peak performance of ca 24 GFLOPS (!!) single precision). I guess the big difference is that Parallella uses the FPGA for HDMI output which those other dev boards probably don't? Is that generating a lot of heat? Would a headless version run much cooler?Īnyway, I didn't intend sto sound negative, it's just something I genuinely don't understand.Īs for the Raspberry Pi, I'm not sure I agree 100% with your comment. Well, I guess I'm mostly puzzled because I think I have not seen any heat sinks or fans on boards that use the exact same SoC that the Parallella does. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |