kraken12
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @05:29PM (#36701942)
The 4090 has half the memory bandwidth, so it could not get a 5X gain, it would actually run slower on a memory bound LLM like this.
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @03:10PM (#36700126)
Yeah, it is an architectural simulation study, this is what is usually done right at the beginning before resources are allocated to go deep on idea. So in that sense it is imaginary; but this is how new ideas get incubated.
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @03:03PM (#36700047)
Yeah, a preliminary architectural study to sanity check if an idea could potentially pay off.
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @03:02PM (#36700032)
Maybe they could do something like AMD's GPU memory stacking, that is good for scaling, and of course they are using many chips not one chip..
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @03:00PM (#36699997)
Seems like HN comments have determined that the cost number is not fudged..
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @02:59PM (#36699979)
Seems to me the 18 tokens per second from [1] is the throughput and includes the batch size, so I don't think they misread the Deepspeed inference paper. So the chiplet ASIC supercomputer paper would seem to show a decent performance/TCO benefit.
Of course, it's a first architectural study to illustrate the promise of the idea, lots more details to work out in a physical implementation and the final realized benefit is likely to be lower. But even a 3X is huge in this space.
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @02:45PM (#36699765)
Yep, it's a research paper in comp arch, the initial proof-of-concept study before you go and spend real money on it.
Re:Chiplet ASIC supercomputers for LLMs like GPT-4
on Wednesday July 12, 2023 @02:43PM (#36699736)
They are using many chips and taking advantage of the way data flows in LLMs to make it work; so it would be cost-effective unlike Cerebras