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22 Commits

Author SHA1 Message Date
Louis Fortier-Dubois e2a3329997
Feat/wgpu/autotune compute (#906) 2023-10-29 16:44:59 -04:00
Nathaniel Simard 233922d60c
Chore: Bump version for next release (#900) 2023-10-24 19:31:13 -04:00
Alex Errant 9f2bc599b8
Add a `sync` feature to common, core, and tensor (#893) 2023-10-24 14:32:01 -04:00
Nathaniel Simard 84df5554b1
Use const seed (#894) 2023-10-24 09:53:11 -04:00
Louis Fortier-Dubois d96f73da0a
Feat/compute/autotune (#861) 
* wip autotune compute

* too much generics

* wip

* megawip

* in progress

* first test passes

* first test passes

* fixed test

* refactor for cache hit and miss

* cleanup and fixes

* doc and stuff

* doc and stuff

* clippy

* format

* remove lifetime

* cleanup operation

* wip

* wip

* compiles

* wip mutable borrow

* refactor with autotune server

* wip tune benchmark

* test passes

* fix autotune key

* cache hit miss tests

* refactor wgpu to match burn-compute

* better operation execution

* cleanup & refactor

* test for parametered kernel

* fmt

* fmt

* clippy

* allow clippy

* fix no-std

* fmt

* review and ci

* Fix CI

* delete dummy benchmarks again

---------

Co-authored-by: nathaniel <nathaniel.simard.42@gmail.com>
 2023-10-23 11:29:44 -04:00
Dilshod Tadjibaev e2a17e4295
Add image classification web demo with WebGPU, CPU backends (#840) 2023-10-05 10:29:13 -04:00
Louis Fortier-Dubois 163e48c969
wgpu: Yet another (faster) matmul (#836) 2023-10-02 14:05:53 -04:00
Damien Elmes e363813911
Use thread-local RNG to generate IDs (#839) 
We've been exploring dividing our data set up into multiple batches,
and training those batches in parallel. I noticed that performance did
not scale with core count, and after some digging, found that this was
mainly due to the Mutex being used to generate IDs. With the following
change, training across 16 cores went from 21s to 4.2s.

thread_rng was previously discussed on #703, but I don't believe that
applies here, as this is just used for UUID creation.
 2023-10-02 14:05:27 -04:00
Nathaniel Simard ca787d6446
Feat/async read (#833) 2023-09-28 17:09:58 -04:00
Louis Fortier-Dubois aa90fe8efb
Refactor/burn benchmark (#829) 2023-09-28 09:38:21 -04:00
Nathaniel Simard ac4adb54ea
Burn compute (#809) 2023-09-18 19:56:53 -04:00
Nathaniel Simard af0be5cfeb
Chore: bump version (#777) 2023-09-06 12:15:13 -04:00
Dilshod Tadjibaev 8448611908
License fixes (#648) 2023-08-16 12:45:35 -04:00
Nathaniel Simard 0a5a2d729a
chore: bump version for next release (#533) 2023-07-26 09:46:28 -04:00
Dilshod Tadjibaev eda241f8cf
Add missing docs and enable missing_docs warn lint (#420) 2023-06-21 14:12:13 -04:00
Dilshod Tadjibaev 834c7ecc1f
Clean up cargo descriptions and formatting (#403) 2023-06-15 09:20:53 -04:00
Dilshod Tadjibaev 05763e1878
Bump version to the next minor to indicate dev (#344) 2023-05-10 18:02:08 -04:00
Nathaniel Simard 29eecd6383
Prepare next release (#335) 2023-05-06 10:32:23 -04:00
nathaniel ef92d8dd1a fix: missing info in cargo.toml 2023-03-21 09:56:34 -04:00
Nathaniel Simard 4e28e2a776
chore: prepare release v0.6.0 (#246) 2023-03-21 09:47:37 -04:00
Nathaniel Simard e6e7f4de42
feat: inplace tensor api. (#187) 2023-03-01 10:55:51 -05:00
Dilshod Tadjibaev fb925acc73
Make burn and burn-core packages no_std compatible (#168) (#173) 
* Make burn-ndarray and burn-tensor no_std compatible (#168)
 2023-02-25 09:38:01 -05:00