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feat: warmup for jit kernel tests #629

Merged
merged 1 commit into from
Nov 24, 2024
Merged

feat: warmup for jit kernel tests #629

merged 1 commit into from
Nov 24, 2024

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yzh119
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@yzh119 yzh119 commented Nov 24, 2024

Currently unittests are slow when using flashinfer jit because we only compile kernels the first time we run it, it's blocking and didn't compile multiple ops in parallel. This PR add a warmup pre-hook to kernel unittests, so that we compile all necessary kernels before running the unittests in JIT mode, which greatly accelerate the unittests.

This PR also fixes the several issues with #628 :

  1. using thread-safe make_dirs(..., exist_ok=True) instead of relying on os.path.exists
  2. change the signature of parallel_load_modules to lists of (jit_module_creation_func, args) instead of lambda function, because lambda function captures variable by ref instead of value, which may cause some unexpected errors.

@yzh119 yzh119 merged commit 8f5f349 into main Nov 24, 2024
yzh119 added a commit that referenced this pull request Nov 24, 2024
…630)

In #629 , page ops are missing in shared-prefix kernel unittest's warmup
function
@yzh119 yzh119 deleted the warmup-jit-tests branch November 24, 2024 07:58
yzh119 added a commit that referenced this pull request Dec 13, 2024
The unittests in AOT mode failed since
#629 because we didn't
use return instead of yield in warmup functions, this PR fixes the
issue.
yzh119 added a commit that referenced this pull request Dec 17, 2024
🤖 I have created a release *beep* *boop*
---


##
[0.2.0](v0.1.6...v0.2.0)
(2024-12-17)

[Release
Blog](https://flashinfer.ai/2024/12/16/flashinfer-v02-release.html).

### Features

* add `rotary_dim` argument to rope APIs for partial apply rope
([#599](#599))
([eb9bc71](eb9bc71))
* add a `use_softmax` field in variant class
([#533](#533))
([d81af97](d81af97))
* add an option `non_blocking` to plan function
([#622](#622))
([560af6f](560af6f))
* add gemma_rmsnorm and gemma_fused_add_rmsnorm
([#477](#477))
([1a6b17e](1a6b17e))
* add group size 3 to GQA decode dispatch
([#558](#558))
([6227562](6227562))
* add JIT compilation support for FA3 templates
([#672](#672))
([d4e8d79](d4e8d79))
* allow the cascade kernels to be executed using varying sequence
lenghts ([#627](#627))
([92ac440](92ac440))
* CUDAGraph compatibility of multi-level cascade inference APIs
([#586](#586))
([2332e8a](2332e8a))
* fix the maximal grid dimension in prefill planning with CUDA graphs
([#639](#639))
([86ca89a](86ca89a))
* improve the precision of the FusedAddRMSNormKernel function
([#587](#587))
([c7dc921](c7dc921))
* JIT compilation
([#507](#507))
([3613a5b](3613a5b))
* modify group-gemm stage number
([#497](#497))
([52dab1d](52dab1d))
* non-contiguous query with paged kv cache
([#553](#553))
([89f2c4a](89f2c4a))
* pass a dynamic token count to the cascade kernels
([#635](#635))
([5fe9f7d](5fe9f7d))
* simplify prefill JIT compilation
([#605](#605))
([fe4f898](fe4f898))
* specify gemm backend
([#648](#648))
([0cc1a51](0cc1a51))
* support cached cos/sin in rope APIs
([#585](#585))
([83e541d](83e541d))
* support huggingface transformer style rope interface
([#568](#568))
([4f40420](4f40420))
* support sm90 cutlass group gemm
([#509](#509))
([794bdda](794bdda))
* torch custom_op fix for rope
([#569](#569))
([3e104bc](3e104bc))
* torch custom_op support: norm
([#552](#552))
([f6e0010](f6e0010))
* torch.compile and custom_op support
([#554](#554))
([9bf916f](9bf916f))
* warmup for jit kernel tests
([#629](#629))
([8f5f349](8f5f349))


### Bug Fixes

* AOT compiler flags on non-sm90
([#522](#522))
([0aa4726](0aa4726))
* batch decode kernel redundant store output to gmem
([#505](#505))
([90e42a7](90e42a7))
* compatible with torch 2.2
([#478](#478))
([ac41d1b](ac41d1b))
* #452
([b53a46f](b53a46f))
* remove redundant load
([#495](#495))
([2de16b0](2de16b0))
* update bmm fp8 test
([#487](#487))
([45eac04](45eac04))


### Performance Improvements

* accelerate JIT compilation speed
([#618](#618))
([eaf73fd](eaf73fd))
* Dense and sparse customizable flashattention-3 template
([#667](#667))
([51236c9](51236c9))
* fix prefill kernel performance degradation (step 1)
([#602](#602))
([595cf60](595cf60))
* fix the performance issue of `append_paged_kv_cache`
([#588](#588))
([e15f7c9](e15f7c9))
* improve parallelism in RoPE with pos_ids
([#609](#609))
([ff05155](ff05155))
* improve plan performance by using non-blocking memcpy
([#547](#547))
([41ebe6d](41ebe6d))
* reduce the read and write of shared memory in the
FusedAddRMSNormKernel
([#592](#592))
([2043ca2](2043ca2))
* reduce total_num_tiles_q by one
([#644](#644))
([553ace5](553ace5))
* remove unnecessary contiguous operation in block sparse attention
([#561](#561))
([7a7ad46](7a7ad46))
* speedup jit compilation of prefill attention kernels
([#632](#632))
([a059586](a059586))
* use cuda-core implemention for io-bound block-sparse attention
([#560](#560))
([3fbf028](3fbf028))

---
This PR was generated with [Release
Please](https://github.com/googleapis/release-please). See
[documentation](https://github.com/googleapis/release-please#release-please).

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Zihao Ye <expye@outlook.com>
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