Viewing profile — negativeonehalf
negativeonehalf
HN member- Joined
- Wed, Sep 18, 2024, 2:19 AM UTC
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About negativeonehalf
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Recent public activity
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Comment #42210197
Meanwhile Google has already used AI for this exact stage of chip design with AlphaChip: https://deepmind.google/discover/blog/how-alphachip-transfor... And they've responded to th…
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Comment #42210153
> Nature doesn't exactly have an stellar track record ensuring Google's results are verifiable ... https://retractionwatch.com/2024/05/14/nature-earns-ire-over ... They open-source…
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Comment #42208197
The "whistleblower"'s admission that he "did not have evidence to support his suspicion of fraud" is pretty damning. He fails to meet a much, much lower bar than direct observation…
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Comment #42208034
Update: Synopsys disavowed Markov's paper: "Regarding the CACM article that Igor Markov's comments and writings do not represent Synopsys views or opinions in any way. Synopsys is …
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Comment #41733834
Unfortunately, there aren't publicly available benchmarks for modern technology node sizes, at least not that I'm aware of. Kahng compared on 45nm and 12nm chips, which are very di…
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Comment #41727992
There's a lot of... passionate discussion in this thread, but we shouldn't lose sight of the big picture -- Google has used AlphaChip in multiple generations of TPU, their flagship…
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Comment #41727912
Unfortunately, commercial EDA companies generally have restrictive licensing agreements that prohibit direct public comparison. Still, the fact that Google uses it for TPU is prett…
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Comment #41727830
[flagged]
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Comment #41727807
See this ISPD 2022 paper where the AlphaChip authors dive more into the value of pre-training (Figure 7, Figure 8): https://dl.acm.org/doi/pdf/10.1145/3505170.3511478
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Comment #41691321
In the blog post, they announce MediaTek's widespread usage, the deployment in multiple generations of TPU with increasing performance each generation, Axion, etc. Chips designed w…
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Comment #41691228
For a more thorough discussion on pre-training, see this ISPD 2022 paper by the AlphaChip people: https://dl.acm.org/doi/pdf/10.1145/3505170.3511478 As for external usage of the me…
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Comment #41689770
You are now using multiple new accounts based on the name of one of the authors (Anna Goldie) and her husband (Gabriel). First this one ('gabegobblegoldi'), and then 'anna-gabriell…
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Comment #41689666
See their ISPD 2022 paper, which goes into more detail about the value of pre-training (e.g. Figure 7): https://dl.acm.org/doi/pdf/10.1145/3505170.3511478 Sometimes training from s…
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Comment #41677001
The quick-start guide in the repo that said you don't have to pre-train for the sample test case, meaning that you can validate your setup without pre-training. That does not mean …
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Comment #41676304
They optimize using a fast heuristic based on wirelength, congestion, and density, but they evaluate with full P&R. It is definitely interesting that they get good timing without e…
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Comment #41676211
The Nature paper describes the importance of pre-training repeatedly. The ability to learn from experience is the whole point of the method. Pre-training is just training and savin…
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Comment #41676027
The original paper reports P&R metrics (WNS, TNS, area, power, wirelength, horizontal congestion, vertical congestion) - https://www.nature.com/articles/s41586-021-03544-w (no payw…
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Comment #41675865
For AlphaChip, pre-training is just training. You train, and save the weights in between. This has always been supported by the Google's open-source repository. I've read Kahng's F…
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Comment #41675478
Prior to AlphaChip, macro placement was done manually by human engineers in any production setting. Prior algorithmic methods especially struggled to manage congestion, resulting i…
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Comment #41675410
Definitely a big part of it. Chips enable better EDA tools, which enable better chips. First it was analytic solvers and simulated annealing, now ML. Exciting times!
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Comment #41675380
FD: I have been following this whole thing for a while, and know personally a number of the people involved. The AlphaChip authors address criticism in their addendum, and in a pri…
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Comment #41664849
6% is just the latest one - this is a real-deal engineering task in the chip design process, that an AI can do better than a human expert, and the gap is growing with time. I'm sur…
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Comment #41664198
Chips are the limiting factor for AI, and now we have AIs making chips better than human engineers. This feels like an infinite compute cheat code, or at least a way to get us very…
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Comment #41633027
Wow, thank you! I've been wanting to learn about GPUs on my next flight, and this is the perfect material for that.
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Comment #41600725
I am saying that we should not destroy a major source of prosperity. Targeted advertising is far more effective than untargeted because it lets you show ads to people who might hav…