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More integration of FPGAs on computers can be really good to exploit relatively long pipeline algorithms that could run in parallel, specially signal processing
by jmrm 3y ago
More integration of FPGAs on computers can be really good to exploit relatively long pipeline algorithms that could run in parallel, specially signal processing ones.
GPUs are really fast but using some kind of instructions, while on a FPGA you can practically design what "instruction" is going to run. From the limited experience I had on CUDA but the complexity of your algorithm and how much branches your code have can make your code a lot slower than running it on a CPU, no matter the amount of CUDA cores you have.
It could be incredibly cool that in some near to mid future to being able to run an application that could run some kind of code in the FPGA, like they already does with the GPU, to solve some kind of problems, like audio, image, video processing, and probably machine learning (I don't know too much about current implementations), and with that user-space interface, it could even be earlier than I though.
- mips_r4300i 3y agoI'm all gung-ho for FPGAs since that's a huge part of my job, but I have to admit that GPUs will always be easier, faster, and more convenient for just about everything you'd want to do as some type of accelerator. There would only be exceptions for power usage, and maybe peak throughout. Where FPGAs shine best are in embedded or very obscure applications where GPUs are way too big, power hungry, or cannot support enough parallelization of your specific algo.