cec

14 ms·

1.
by cec 2mo ago
I'm not a big fan of the encroachment of AI into Adobe's apps, so I'm using AI to build a replacement for those apps (a small web-based photo organizer and editor, just the tiny subset of the Lightroom features I need for my
2.
by cec 2y ago
Hey! The idea isn't to replace the compiler with an LLM, the tech is not there yet. Where we see value is in using these models to guide an existing compiler. E.g. orchestrating optimization passes. That way the LLM won't break yo
3.
by cec 3y ago
Is a MacOS build of YNAB 4 still available?
4.
by cec 3y ago
We use the same architecture as other LLMs, but we include no natural language in our pretraining. We figured a single-domain training corpus would make evaluation easier. We’ll be looking at layering this on top of something like Code Llam
5.
by cec 3y ago
Hey, we’re targeting code size in this work, not runtime performance. You would use an option like -O3 to optimize for runtime and -Oz to optimize for code size. The pass pipelines are different for both
6.
by cec 3y ago
Program synthesis is part of the loss function, which is what makes it a auxiliary learning task. We haven’t experimented with model size yet, we just used the same configuration as the smallest Code Llama. We did play with dataset size and
7.
by cec 3y ago
There’s a researcher at Edinburgh who is looking into this. You may want to reach out. Check the related work section in this paper
8.
by cec 3y ago
Hey Jon, we don't change semantics. We just choose optimization passes to run to match a particular input code. Agreed that code size wins could regress performance. We don't measure that yet, but will be looking into it next. The
9.
by cec 3y ago
Hey, yes that's right, and good callout on GEP instructions. We admit that instruction count is a bit handwavy, but we use it as a starting point as that's what the prior works we compare against optimize for. We'll be lookin
10.
by cec 3y ago
Hey, author here. We use machine learning to generate a list of _optimization passes_ for the compiler to run. These optimization passes give us a 3.0% improvement over the default (-Oz), and are what generates correct code. We don't d
11.
by cec 6y ago
This. For now we rely on differential testing against a gold-standard implementation (e.g. unoptimized). For the action space we expose, any semantics-breaking change induced by our tool is a compiler bug.
12.
by cec 6y ago
Author here. In the sense that a trained neural net produces the same output from the same input, this is deterministic. But I don’t think that’s what you’re getting at. Where it gets interesting is if we inserted a feedback loop (such as F
13.
by cec 6y ago
https://github.com/chriscummins/phd
14.
by cec 9y ago
I'd be careful about asking your co-workers for "dick pics".
15.
by cec 9y ago
No, HI is Brady Haran and CGP Grey, though I suspect Brady may have collaborated with Tom.
16.
by cec 9y ago
The paper says "we started a high-priority project to quickly produce a custom ASIC for inference (and bought off-the-shelf GPUs for training)."
17.
by cec 10y ago
Give texstudio a try. I find it offers exactly the kind of IDE-style features that I was missing from Emacs and other editors.
18.
by cec 10y ago
For offline writing (e.g. emacs/vim), I've found textlint[1] to work really nicely, and fits well into a LaTeX+Makefile workflow. [1] https://github.com/textlint/textlint
19.
by cec 10y ago
No. && would cause the next command to begin once the previous had successfully completed. A successful install shoudn't start the next install attempt, hence ||. On the other hand, OP and this comment miss the beauty of Randal
20.
by cec 11y ago
I'm not sure if I can agree with that reasoning. Sure, no-one is impressed with an Apple II now, but that doesn't degrade how significant it was then . By that measure, did the Wright bothers really need to put in all of that tim
21.
by cec 11y ago
I love how in all of their "meet the fleet" headshots, the birds are totally out of focus, only the grass in the background is clear
22.
by cec 11y ago
Great post, definitely giving this a try.
23.
by cec 11y ago
Off topic, but does anyone know how the author generated this web version of the paper? It looks like as though they've automatically generated it from the LaTeX source of the PDF. It looks brilliant, and much easier to read in the bro
24.
by cec 11y ago
> I'm no biologist, but I don't think our brains are going around trying to do a grid search for the best hyperparameters. Is that not essentially the process of evolution through natural selection? One giant optimisation probl
25.
by cec 11y ago
I think the author does a great job at venting frustration at the state of autotuning systems research, though I would disagree that the research interest has dried up. On the contrary, autotuning research is alive and kicking, the problem
26.
by cec 11y ago
Great stuff. I personally find it useful to have an additional "Regression" label to tag bug reports that have cropped up as a result of new work (this happens surprisingly often).
27.
by cec 12y ago
Since this is for git repositories you'd probably want to sub that `find -type f' for `git ls-files'.
28.
The weekend that 130,241 people dropped by(chriscummins.cc)
1 points by cec 12y ago|0 comments
29.
by cec 12y ago
The fitness value represents the difference between the pixels of the "goal" image and the pixels of the current individual [1]. It will not necessarily reflect the perceived similarity between two images, which will change from p
30.
by cec 12y ago
You are right. The "DNA" label is inaccurate, but jal278 explained the reasoning perfectly. I'd be happy to hear suggestions for a better term though! ;)

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