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aportnoy

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投稿

Train an RL agent to play tic-tac-toe

github.com
3 ポイント·投稿者 aportnoy·6 か月前·1 コメント

Show HN: Reinforcement learning tic-tac-toe in C, annotated

github.com
2 ポイント·投稿者 aportnoy·6 か月前·0 コメント

Pretraining Large Language Models with NVFP4

arxiv.org
1 ポイント·投稿者 aportnoy·9 か月前·0 コメント

Visualize core-to-core latency

github.com
2 ポイント·投稿者 aportnoy·3 年前·0 コメント

Show HN: Visualize core-to-core latency in ~200 lines of C and Python

github.com
2 ポイント·投稿者 aportnoy·3 年前·1 コメント

Apache log pretty printer in 130 lines of C

github.com
2 ポイント·投稿者 aportnoy·3 年前·0 コメント

Show HN: Pretty print Apache logs in 130 lines of C99

github.com
1 ポイント·投稿者 aportnoy·3 年前·0 コメント

コメント

aportnoy
·5 か月前·議論
Is Bel a smaller LISP than what's described in The Roots of Lisp? [1]

[1] https://paulgraham.com/rootsoflisp.html
aportnoy
·6 か月前·議論
aportnoy.com
aportnoy
·2 年前·議論
For NVIDIA,

1. play around with the NVPTX LLVM backend and/or try compiling CUDA with Clang,

2. get familiar with the PTX ISA,

3. play around with ptxas + nvdisasm.
aportnoy
·3 年前·議論
Well then… test your memory :)
aportnoy
·3 年前·議論
Don't overclock your memory.
aportnoy
·3 年前·議論
Wow I came back to post this exact reply. I set my system to a slightly high frequency, ran memtest overnight with errors.

Set it back down to a supported frequency, ran a full memtest suite again with no errors.

Never had any issues since.
aportnoy
·3 年前·議論
> But the lack of ECC was a huge bummer at the time of purchasing my system.

Why?..
aportnoy
·3 年前·議論
> extremely opinionated

I have not seen a single codebase that widely uses uint8_t and does not typedef it to u8. It is the exact opposite of "extremely opinionated".
aportnoy
·3 年前·議論
Note Sam Altman is a Cerebras investor.
aportnoy
·3 年前·議論
Asking because I am on that team :)

I went through the same hiring process and had a positive experience at every stage. I had a strong competing offer but went with the JAX team at NVIDIA.

I'll pass it along as feedback.
aportnoy
·3 年前·議論
What happened?
aportnoy
·3 年前·議論
1 is the multiplicative identity

0 is the additive identity

all([]) is True

any([]) is False
aportnoy
·3 年前·議論
Go to the blog and skip to results: https://ai.meta.com/blog/seamless-m4t/
aportnoy
·3 年前·議論
The project is a port of https://github.com/nviennot/core-to-core-latency from Rust to C.
aportnoy
·3 年前·議論
I used to surf near Scripps Pier while in college and I remember there were always a couple people sitting outside in beach chairs working on their laptops.

Salk Institute is an even more surreal place.
aportnoy
·3 年前·議論
The funny thing is Perl is now arguably more obsolete than sed and awk.
aportnoy
·3 年前·議論
I recently interviewed with a fantastic startup in that space called TestFit (testfit.io).
aportnoy
·3 年前·議論
This definitely isn't "printing" in the original sense, just a serialization algorithm.
aportnoy
·3 年前·議論
In the original LISP with dynamic scoping I think it would be fair to serialize that expression as is: "just use whatever value is bound to 'y' at the time of evaluation, if any".
aportnoy
·3 年前·議論
Everything is an object that is either a cons cell or an atom. Associate the address of each object with a unique index.

Serialize each object as a pair (index, obj), where 'index' maps back to the original address where the object was stored, and 'obj' is a pair of indices if the object is a cons cell, or the appropriate representation (string literal, integer, etc.) if the object is an atom.

Then to deserialize allocate a memory location for every index and load the objects as is. Then replace the indices with the corresponding (new) addresses.