[CthulhuOvermind]

I feel I can talk about this! My master's thesis was computation of a neural network using FPGA + CPU. The original SNN code was in C++, my thesis implemented in in OpenCL. This was using the Altera OpenCL to FPGA implementation

Essencially taking the inner-most loop (that computed if a neuron would spike or not) and implementing it as a kernel in OpenCL.

Step 1 was showing increase from single-thread C++ to OpenCL kernel. Increase was 6-10x using a i7-2600k and running on all logical cores. Step 2 was implementing in FPGA. This means pre-shipping data to the FPGA while CPU calculated other things, and beginning computation on the FPGA, and receiving responses back on CPU. Performance was 75x compared to single-thread C++ code.

Important notes that I didn't expect: Bottleneck was memory transfer bandwidth across PCI-E. Power consumption was less on FPGA compared to CPU. Development time was significantly lessened. Altering the design is simple when going from OpenCL > FPGA, compared to Verilog > FPGA

[qubex]

In the late nineties I had the rare opportunity to work with a very exotic “FPGA hypercomputer” (yes, the marketing makes me cringe) that basically consisted of an array of FPGAs that instantiated logic at the hardware level and dynamically readjusted if required. It was a prototype built by now-defunct Starbridge Systems and designed, amongst others, by Fagin of Intel microprocessor fame.

[tkinom]

Interesting....

What kind tool do you use for OpenGL to FPGA?

[jdmoreira]

OpenCL - https://en.wikipedia.org/wiki/OpenCL

[semi-extrinsic]

>Bottleneck was memory transfer bandwidth across PCI-E

This is why Nvidia are working on NVLink to replace PCI-E.

[rw]

Is your thesis online where we can look at it?