3 ms·

> that bag needs people that write HDL and understand computer architecture to make good use of Over time I suppose they could have some machine learning that

> that bag needs people that write HDL and understand computer architecture to make good use of Over time I suppose they could have some machine learning that automatically configures the FPGA based on which programs you are running and the types of computations they have historically used.

londons_explore 8y ago
machine learning that automatically writes HDL programs to match functionality of x86 programs and are more efficient when executed on an FPGA than a general purpose CPU haven't yet been invented... Nor do I think they will be invented soon. Machine learning is bad at doing discrete things, bad at things requiring zero mistakes, and bad at problems for which the answer can't be perfectly verified (due to needing to solve the halting problem).
petra 8y ago
I think spiralgen can also do FPGA(or could do if needed), i.e. automatically generate highly optimized numerical code. http://www.spiralgen.com/ http://www.spiralgen.com/
elteto 8y ago
There’s a pretty cool story about using evolutionary algorithms to program an FPGA for a specific task: https://www.damninteresting.com/on-the-origin-of-circuits https://www.damninteresting.com/on-the-origin-of-circuits. Probably not ML in the sense you were talking but very cool nonetheless. In the end the final result was hyperoptimized FPGA code that only ran on a specific board and used a bunch of nonsensical structures that seemed to be doing nothing, yet would stop the circuit from working if removed!
- qubex 8y ago
  I remember this, thanks for brining it up,:I had read it years ago and it always haunted me. The evolved solution involved using only 37 out of the 100 gates available, no clock, and some units were logically disconnected yet disabling them caused the chip to fail at its task, indicating it was relying on EM effects particular to the chip. Truly amazing (and perhaps a bit creepy too).

londons_explore 8y ago

machine learning that automatically writes HDL programs to match functionality of x86 programs and are more efficient when executed on an FPGA than a general purpose CPU haven't yet been invented... Nor do I think they will be invented soon. Machine learning is bad at doing discrete things, bad at things requiring zero mistakes, and bad at problems for which the answer can't be perfectly verified (due to needing to solve the halting problem).

petra 8y ago

I think spiralgen can also do FPGA(or could do if needed), i.e. automatically generate highly optimized numerical code. http://www.spiralgen.com/ http://www.spiralgen.com/

elteto 8y ago

There’s a pretty cool story about using evolutionary algorithms to program an FPGA for a specific task: https://www.damninteresting.com/on-the-origin-of-circuits https://www.damninteresting.com/on-the-origin-of-circuits. Probably not ML in the sense you were talking but very cool nonetheless. In the end the final result was hyperoptimized FPGA code that only ran on a specific board and used a bunch of nonsensical structures that seemed to be doing nothing, yet would stop the circuit from working if removed!

qubex 8y ago
I remember this, thanks for brining it up,:I had read it years ago and it always haunted me. The evolved solution involved using only 37 out of the 100 gates available, no clock, and some units were logically disconnected yet disabling them caused the chip to fail at its task, indicating it was relying on EM effects particular to the chip. Truly amazing (and perhaps a bit creepy too).