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Groenenboomj/fixes causal #575

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Add support for causal masking false and some testing changes:
-- backwards kernel support for bf16
-- backwards benchmark

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LGTM

micmelesse and others added 11 commits July 17, 2024 05:04
Add Perf Kernels

This is a combination of 2 commits.

Add Perf Kernels

Add Perf Kernels

This is a combination of 6 commits.

add perf-kernels

fix formating issues

fix unused variables and other bugs

fix other issues

remove scripts

save

check changes

format

save

save

try

pre-commit check

save
Change all block pointers to tensor pointers

Block pointers are for nvidia TMAs. They are useful for regular loads as well but not well supported.

Also cleaned up some code I came across along the way and updated comment at the top.
Add support for layouts commonly used by users.

Add option for varlen / thd layout to specify equal context lengths for all batches. Also often used by users.
* remove on push for Integration Tests

* rename

* add post merge test

* save

* dtype params

* skip bad config

* fix more stuff
Increase CI timeout
Couple of FA optimizations

Set SM scale multiplication to a constexpr. Minor asm improvement.

Changed acc scaling to adjust for softmax division to
multiplication with reciprocal. ~10% perf improvement.

---------

Co-authored-by: Michael Melesse <[email protected]>
* streamk v0.1

* remove unused variable

* fix format issues

* add README

* fix format issue

* change num_sms to num_cus
* Add explicit multiply-reduce GEMM kernel

* Remove `SPLIT_K` argument from kernel

* Remove `GROUP_SIZE_M` argument from kernel

* Remove conditional call to `tl.dot` from kernel

* Remove table with performance data from README
@groenenboomj groenenboomj reopened this Aug 12, 2024
@groenenboomj groenenboomj changed the base branch from triton-mlir to main_perf August 12, 2024 16:42
@@ -1259,99 +1261,93 @@ def test_op_varlen_mqa_fwd(Z, HQ, HK, N_CTX, D_HEAD, causal, dtype=torch.float16
#(1, 16, 8192, 63),
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We should test seqlens that are small so 1, 2, 4, 16, 32, 64, 128, 256, etc ...

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6 participants