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How AlphaChip transformed computer chip design

deepmind.google

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Re: How AlphaChip transformed computer chip design

#131

Post by bushbaba »

rossjudson wrote: post #128
Drunk_Engineer wrote: post #73

Earlier quoted context omitted.

I have not read the latest paper, but their previous work was really unclear about metrics being used. Researchers trying to replicate results had a hard time getting reliable details/benchmarks out of Google. Also, my recollection is that Google did not even compute timing, just wirelength and congestion; i.e. extremely primitive metrics. Floorplanning/placement/synthesis is a billion dollar industry, so if their ap…

Like when Google wasted its time writing publicly about Spanner? https://research.google/pubs/spanner-googles-globally-distri... or Bigtable? https://research.google/pubs/bigtable-a-distributed-storage-... or GFS? or MapReduce? or Borg? or...I think you get the idea.

Spanner research paper was in 2012. Bigtable was in 2006. GFS 2003. The last decade has been a 'lost decade' of google. Not much innovation to be honest.

Re: How AlphaChip transformed computer chip design

#132

Post by djmips »

clickwiseorange wrote: post #81
negativeonehalf wrote: post #71

Earlier quoted context omitted.

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 prior statement from the co-lead authors: https://www.nature.com/articles/s41586-024-08032-5 , https://www.annagoldie.com/home/statement - The 2023 ISPD paper didn't pre-train at all. This means no learning from experience, for a learning-base…

Oh, man... this is the same old stuff from the 2023 Anna Goldie statement (is this Anna Goldie's comment?). This was all addressed by Kahng in 2023 - no valid criticisms. Where do I start? Kahng's ISPD 2023 paper is not in dispute - no established experts objected to it. The Nature paper is in dispute. Dozens of experts objected to it: Kahng, Cheng, Markov, Madden, Lienig, Swartz objected publically. The fact that Ka…

> Kahng is the most prominent active researcher in this field. If anyone knows this stuff, it's Kahng.

This is written as a textbook example logical fallacy of appeal to authority.

Re: How AlphaChip transformed computer chip design

#133

Post by Zamiel_Snawley »

ninetyninenine wrote: post #117
Zamiel_Snawley wrote: post #116

Earlier quoted context omitted.

I think only sentimentality can prevent take over by a sufficiently competent AI. I don’t want art that wasn’t made by a human, no matter how visually stunning or indistinguishable it is.

Discounting fraud... what if the AI produces something genuinely better. Genuinely moving you to tears? What then? Imagine your favorite movie, the most moving book. You read it, it changed you, then you found out it was an AI that generated it in a mere 10 seconds. Artificial sentimentality is useless in the face of reality. That human endeavor is simply data points along an multi-dimensional best fit curve.

That’s a challenging hypothetical.

I think it would feel hollowed out, disingenuous.

It feels too close to being a rat with a dopamine button, meaningless hedonism.

I haven’t thought it through particularly thoroughly though, I’d been interested in hearing other opinions. These philosophical questions quickly approach unanswerable.

Re: How AlphaChip transformed computer chip design

#134

Post by lacker »

porphyra wrote: post #56
vighneshiyer wrote: post #41

This work from Google (original Nature paper: https://www.nature.com/articles/s41586-021-03544-w ) has been credibly criticized by several researchers in the EDA CAD discipline. These papers are of interest: - A rebuttal by a researcher within Google who wrote this at the same time as the "AlphaChip" work was going on ("Stronger Baselines for Evaluating Deep Reinforcement Learning in Chip Placement"): http://47.190.8…

The Deepmind chess paper was also criticized for unfair evaluation, as they were using an older version of Stockfish for comparison. Apparently, the gap between AlphaZero and that old version of Stockfish (about 50 elo iirc) was about the same as the gap between consecutive versions of Stockfish.

Indeed, six years later, the AlphaZero algorithm is not the best performing algorithm for chess. LCZero (uses AlphaZero algorithm) won some TCECs after it came out but for the past few years Stockfish (does not use AlphaZero algorithm) has been winning consistently.

https://en.wikipedia.org/wiki/Top_Chess_Engine_Championship

So perhaps the critics had a point there.

Re: How AlphaChip transformed computer chip design

#135

Post by sanxiyn »

therealcamino wrote: post #125
sroussey wrote: post #57

Earlier quoted context omitted.

The problem is that the competition (our current von neumann architecture) has billions of dollars of R&D per year invested. Better architectures without the yearly investment train will no longer be better quite quickly. You would need to be 100x to 1000x better in order to pull the investment train onto your tracks. Don’t has been impossible for decades. Even so, I think we will see such a change in my lifetime. AI…

If you don't worry about the programming model, it's pretty easy to be way better than than existing methodologies in terms of pure compute. But if you do pay attention to the programming model, they're unusable. You'll see that dozens of these approaches have come and gone, because it's impossible to write software for them.

GPGPU is instructive. It is not easy, but possible to write software for it. That's why it succeeded.

Re: How AlphaChip transformed computer chip design

#137

Post by ok_dad »

djmips wrote: post #132
clickwiseorange wrote: post #81

Earlier quoted context omitted.

Oh, man... this is the same old stuff from the 2023 Anna Goldie statement (is this Anna Goldie's comment?). This was all addressed by Kahng in 2023 - no valid criticisms. Where do I start? Kahng's ISPD 2023 paper is not in dispute - no established experts objected to it. The Nature paper is in dispute. Dozens of experts objected to it: Kahng, Cheng, Markov, Madden, Lienig, Swartz objected publically. The fact that Ka…

> Kahng is the most prominent active researcher in this field. If anyone knows this stuff, it's Kahng. This is written as a textbook example logical fallacy of appeal to authority.

The GP would have had to appeal only to the expert’s opinion, with no actual evidence, but the GP actually gave a lot of evidence to the expertise of the researcher in the form of peer reviewed papers and other links. That’s not an appeal to authority at all.

Re: How AlphaChip transformed computer chip design

#138

Post by ninetyninenine »

Zamiel_Snawley wrote: post #133
ninetyninenine wrote: post #117

Earlier quoted context omitted.

Discounting fraud... what if the AI produces something genuinely better. Genuinely moving you to tears? What then? Imagine your favorite movie, the most moving book. You read it, it changed you, then you found out it was an AI that generated it in a mere 10 seconds. Artificial sentimentality is useless in the face of reality. That human endeavor is simply data points along an multi-dimensional best fit curve.

That’s a challenging hypothetical. I think it would feel hollowed out, disingenuous. It feels too close to being a rat with a dopamine button, meaningless hedonism. I haven’t thought it through particularly thoroughly though, I’d been interested in hearing other opinions. These philosophical questions quickly approach unanswerable.

>These philosophical questions quickly approach unanswerable.

With the current trendline of AI progress in the last decade the question has a high possibility of being answered by being actualized in reality.

It's not a random question either. With AI quickly entrenching itself into every aspect of human creation from art, music, to chip design, this is all I can think about.

Re: How AlphaChip transformed computer chip design

#139

Post by bombita »

bushbaba wrote: post #131
rossjudson wrote: post #128

Earlier quoted context omitted.

Like when Google wasted its time writing publicly about Spanner? https://research.google/pubs/spanner-googles-globally-distri... or Bigtable? https://research.google/pubs/bigtable-a-distributed-storage-... or GFS? or MapReduce? or Borg? or...I think you get the idea.

Spanner research paper was in 2012. Bigtable was in 2006. GFS 2003. The last decade has been a 'lost decade' of google. Not much innovation to be honest.

Attention is all you need is 2017... https://arxiv.org/abs/1706.03762

Re: How AlphaChip transformed computer chip design

#140

Post by sijnapq »

negativeonehalf wrote: post #90
Drunk_Engineer wrote: post #73

Earlier quoted context omitted.

I have not read the latest paper, but their previous work was really unclear about metrics being used. Researchers trying to replicate results had a hard time getting reliable details/benchmarks out of Google. Also, my recollection is that Google did not even compute timing, just wirelength and congestion; i.e. extremely primitive metrics. Floorplanning/placement/synthesis is a billion dollar industry, so if their ap…

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 paywall): https://www.cl.cam.ac.uk/~ey204/teaching/ACS/R244_2021_2022/...

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