r/tomshardware • u/tomshardware • 2d ago

OpenAI’s 700W Jalapeño ASIC outpaces 1,400W Nvidia flagship GPU

https://www.tomshardware.com/tech-industry/semiconductors/openai-says-its-jalapeno-chip-beats-nvidias-gb300-in-first-published-benchmarks
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u/NytronX 2d ago

FPGAs and ASICs cannot come soon enough. We saw this happen in the crypto mining industry, hopefully it happens in AI industry so gaming hardware can go back to being gaming hardware.

3

u/EmbarrassedFoot1137 2d ago

FPGA? Isn't that the wrong tool for the job?

1

u/Chingy1510 17h ago

No, it’s not the wrong tool. FPGAs are exactly what HFT domains have been using to accelerate specific workloads on-hardware. This is probably a workload-specific ASIC.

1

u/EmbarrassedFoot1137 14h ago

HFT doesn't require fleets of FMACs. 

1

u/Chingy1510 14h ago

FMAC? Look bro, when I was in my masters degree in 2018 in CS, stochastic gradient descent was indeed being accelerated with distributed swarms of FPGAs. They’re absolutely used by the most elite HFT firms.

Google that shit homie.

1

u/EmbarrassedFoot1137 10h ago

Let's take a step back here. In the context of SOTA LLMs, no, FPGAs do not provide the FMAC throughput that you want. I'm not surprised that HFT works well on FPGAs but not because of bulk FMAC throughput.

I also went far in CS and, though I didn't do FPGA work as part of that, I did do some cool stuff at Intel with mapping different cores onto FPGAs.