tinygrad VS data_jd

Might be a silly question but is GGML a similar/competing library to George Hotz's tinygrad [0]?

[0] https://github.com/geohot/tinygrad

at first glance i thought may its like tinygrad. but looks has many ops than that tiny grad but most maps to underlying hardware provided ops?

i wonder how well tinygrad's apporach will work out, ops fusion sounds easy, just a walk a graph, pattern match it and lower to hardware provided ops?

Anyway if anyone wants to understand the philosophy behind tinygrad, this file is great start https://github.com/geohot/tinygrad/blob/master/docs/abstract...

There are currently at least 3 ways to run llama on m1 with GPU acceleration. - mlc-llm (pre-built, only 1 model has been ported) - tinygrad (very memory efficient, not that easy to integrate into other projects) - llama-mps (original llama codebase + llama adapter support)

Hopefully we will see now full support with AMD hardware on https://github.com/geohot/tinygrad. You can read more about it on https://tinygrad.org/

tinygrad

https://github.com/geohot/tinygrad/tree/master/accel/ane

But I have not tested it on Linux since Asahi has not yet added support.

llama.cpp runs at 18ms per token (7B) and 200ms per token (65B) without quantization.

I suspect the J package Jd is probably the most non-trivial public codebase. I don’t love the coding style (functions are long and scripted) and it doesn’t make use of newer lambda functions (“direct definitions”) which are easier to read. https://github.com/jsoftware/data_jd

I found this license for jd itself. It is free only for non-commercial use:

https://github.com/jsoftware/data_jd/blob/master/doc/License...

The link you mentioned only applies to the jsource folder: the jengine code.

A longer piece from GitHub: csvreportsummary=: 3 : 0 t=. <;.2 fread PATHLOGLOGFILE b=. (<,LF)=t b=. b+.(<'!')={.each t b=. b+.(<'src: ')=5{.each t b=. b+.(<'snk: ')=5{.each t b=. b+.(<'elapsed: ')=9{.each t b=. b+.(<'rows: ')=6{.each t b=. b+.(<'error: ')=7{.each t ;b#t )