Right now, FPGAs deliver slightly better perf/W than GPUs, but significantly inferior FP32 performance. That said, they do shine for simple embarrassingly para

Right now, FPGAs deliver slightly better perf/W than GPUs, but significantly inferior FP32 performance. That said, they do shine for simple embarrassingly parallel tasks assuming the task does not require FP32 operations. A good example here is bitcoin mining. That changes this year with the release of Altera's Arria 10, which comes with 1.3 TFLOPS of hardcoded FP32 math units. The other gamechanger is the ability to write kernels in OpenCL rather than VHDL. However, the build time for OpenCL on FPGAs is still many hours compared to tens of seconds for GPUs so my guess is that GPUs will remain the development platform for FPGA code for the foreseeable future, occasionally deploying to FPGA on a daily basis or so. Drifting a little off-topic, the SDKS and libraries for all the accelerators should be free. That's what makes me such a CUDA fanboy. I'm looking at you Intel. Charging for your Xeon Phi/CPU OpenCL compiler? Bzzzzt wrong...