George Hotz | Programming | hand optimizing a resnet 50 in tinygrad | | Part 1
Date of the stream 29 Sep 2023.
from $1250 buy & best ADAS system in the world
Live-stream chat added as Subtitles/CC - English (Twitch Chat) - at the bottom - Show Transcript
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Chapters:
00:00:00 muted intro
00:00:40 un-muted intro
00:00:50 taiwan and india
00:01:50 how free is taiwan, china, check in hotel
00:03:20 free internet in taiwan
00:04:00 wechat in china
00:05:55 story time, iceland
00:07:00 safe singapur
00:09:20 brazil, south africa
00:11:10 George trying not be controversial
00:12:10 grants, fixing the empire
00:13:45 dismantling our late-stage capitalist society
00:14:40 George stating his political preference
00:15:30 Elon Musk the next Caesar, bike trip
00:17:00 Ukraine gdp per capita, taiwan gdp per capita
00:17:50 progressive, can’t make everyone happy in politics
00:18:20 sarcasm
00:19:00 eastern europe bike trip, andrew tate
00:20:10 countries to avoid
00:23:05 shipping for non-US citizens for tinybox
00:23:45 sweden, dubai
00:28:25 direction of tinygrad
00:30:30 building a wall
00:31:00 declining empires
00:32:50 china spending power, kenya poor
00:35:00 favorite countries in europe, dubai
00:36:15 libertarian india
00:36:50 hand coding resnet 50
00:40:10 kernels in resnet
00:43:05 operations for the resnet, the power of the new tinygrad abstractions
00:46:10 simple abstractions in tinygrad = fast
00:46:20 init does lots of adds
00:47:25 renderer, kernel code
00:48:55 cleanest abstractions anywhere nn
00:49:20 not optmized kernel, optimization
00:49:50 benchmarking
00:58:40 kind of wrong, some kernels bad
01:01:35 how nice is tinygrad
01:08:40 love for python
01:09:30 faster
01:11:20 MadDogNation is gifting 34 subs!
01:12:40 focusing on slowest
01:21:25 multiview shapetracker
01:25:40
01:27:10 reshaping to real size
01:27:40 very happy with this infrastructure
01:31:35 let’s make it faster
01:35:25 metal max fmax
01:39:25 gated loads, finding bugs
01:41:30 108 GFLOPS
01:43:30 we have to start thinking
01:47:30 we build an optimizer
01:49:30 upcast, search and optimization is amazing
01:52:25 out of ideas
01:59:50 that kernel just looks fast it just isn’t
02:03:20 that kernel was not the problem
02:04:45 automatic optimizer
02:07:25 10% faster, we learn, knowledge is power
02:08:15 running this anywhere
02:08:50 4416 lines, 1000 lines, new goal 5000 lines
02:09:10 thank you for gifting subs!
02:09:40 on topic questions only for non-subs
02:10:03 up to the front tinygrad, short and generic
02:10:55 every part of a full deep learning stack
02:11:05 resnet 50 pytorch like code
02:11:25 tinygrad is a waste of time?
02:12:00 why is pytorch faster? pytorch less capable library
02:12:20 cudnn hand optimized by 20 nvidia engineers for 10 years
02:13:00 the bitter lesson
02:13:10 can’t I just call CUDNN?
02:14:05 generic optimizer so much simpler to reason about
02:14:20 learn a model that look at shapetracker to optimize
02:14:40 recursive self-improvement
02:14:50 AGI inside tinygrad
02:15:20 AGI will run in 4k lines
02:15:40 every piece of tinygrad you can reason about
02:16:15 no more debates, heat death of the universe
02:16:45 AIs will come, monkey civilization
02:17:15 why people think AI is dangerous
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