[HN Gopher] From Unemployment to Lisp: Running GPT-2 on a Teen's...
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From Unemployment to Lisp: Running GPT-2 on a Teen's Deep Learning
Compiler
Author : AymanB
Score : 79 points
Date : 2024-12-10 16:12 UTC (6 hours ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| AymanB wrote:
| A couple months ago I found myself unemployed, uncertain about
| what to do next. I wanted to learn more about deep learning, but
| from a systems prespective. Coming from Andrew's Ng course on
| supervised learning, I was eager to learn more about how deep
| learning frameworks (or deep learning compilers) like Pytorch or
| Tinygrad.
|
| I started to poke around Tinygrad, learning from the tutorials I
| found online, and I found it fascinating because it was an actual
| compiler, it took conventional python code and translated them
| into an Abstract Syntax Tree that was parsed into UOps and
| ScheduleItems, to finally have a codegen layer. While the design
| was interesting, the code was hard to read.
|
| That's when I stumbled across something completly unexpected, A
| deep learning compiler built on Common Lisp, maintained by a
| Japanese 18-year-old during his gap year. And currently we have
| acomplished something great, it can run gpt2!
|
| For now, it just generates C-kernels, but in the future we would
| like to support cuda codegen as well as many other features, and
| serve as a learning tool for anyone who would like to get to work
| on deep learning compilers in Common Lisp.
| a2code wrote:
| In general, a compiler takes source code and generates object
| code or an executable. Can you elaborate on what your compiler
| takes as input and generates as an output?
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