Commit Graph

646 Commits

Author SHA1 Message Date
bobofang
127e742e96 Add MFMA M16N16K16 and M16N16K32 methods
these two methods are default off
2025-07-28 14:54:51 -04:00
YC Lin
e866f814f9 [GEMM] remove a_col_major/b_row_majro case 2025-07-28 14:54:51 -04:00
root
bf69235cfb [GEMM] modify if-else locations 2025-07-28 14:54:51 -04:00
mhYang
ba8b5112c4 Fix AccDataType and CDataType
1. Fix AccDataType and CDataType
2. Remove indent
3. Align merge_transform for tutorial
2025-07-28 14:54:51 -04:00
mhYang
d6fd468603 Fix build error 2025-07-28 14:54:51 -04:00
root
b3986c32a6 [GEMM] disable/enable instruction scheduling 2025-07-28 14:54:51 -04:00
mhYang
42f2e21865 Fix missing message 2025-07-28 14:54:51 -04:00
mhYang
38ce4dd8c3 Fix xor transform dim. 2025-07-28 14:54:51 -04:00
Clement Lin
b03668fe8a [GEMM] Add cache-aware WG schedule and adjust block tile
113 -> 121.7 TFops
2025-07-28 14:54:51 -04:00
mhYang
39ca852330 Add LDS bank conlict solutions 2025-07-28 14:54:51 -04:00
bobofang
22147ace51 Fix add accuracy issue
2673 GB/s -> 3271 GB/s
Perf: 0.0512898 ms, 3271.06 GB/s
2025-07-28 14:54:51 -04:00
root
d7d9fdaf1b [GEMM] use mfma k8 warp gemm 2025-07-28 14:54:51 -04:00
root
1b8d7cd1b9 [GEMM] disable/enable prefetch 2025-07-28 14:54:50 -04:00
Clement Lin
6a2036015e [CK TILE] Toy example - basic gemm 2025-07-28 14:54:50 -04:00
Clement Lin
077056b32d Adjust block shape
2673 GB/s -> 3647 GB/s
2025-07-28 14:54:50 -04:00
Clement Lin
2ff691f3f2 Utilize vectorized memory access
1998.24 GB/s -> 2673 GB/s
2025-07-28 14:54:50 -04:00
Clement Lin
078b5c68a0 Adjust the size of thread block
1968.42 GB/s -> 1998.24 GB/s
2025-07-28 14:54:50 -04:00
Clement Lin
8d205a9298 [CK TILE] Toy example - basic add 2025-07-28 14:54:50 -04:00
Illia Silin
504b101da3 upgrade from clang-format-12 to clang-format-18 (#2568)
* upgrade to clang-format-18

* update to clang-format-18 in pre-commit-config
2025-07-28 11:34:07 -07:00
rocking
b36e0b029f [CK_TILE][FMHA] Uncomment all the headdim, use optdim to control (#2539)
* uncomment all the headdim, use optdim to control

* change default back to -1

* uncomment splitkv instance

* Fix typo in receipt 4 for appendkv

* support optdim for bwd, splitkv and appendkv

* Fix 192 key error

---------

Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
Co-authored-by: Andy Lugo <Andy.LugoReyes@amd.com>
2025-07-28 17:16:32 +08:00
Max Podkorytov
821cd26c13 [CK-Tile] Merge transpose examples (#2450)
* unify pipeline signature with existing example

* iwyu

* move stuff around in load-tile-transpose

* cleanups in batched transpose pipeline

* comments

* use same inputs size

* cleaner printf

* print host args

* use 64 block sides in the 37_transpose example

* roll back grid dimension size adjustment for 37_transpose example

* transpose grid for 37_transpose to unify with 35_batched_transpose

* unify grid computation logic

* make policy methods device only (since they are used only on device from the pipeline)

* more host/device attribute cleanups

* copy over problem

* move over pipeline and policy

* add switch to batched transpose api

* make the lds problem more similar to original problem

* factor out logic into traits

* factor out conditional compilation into trait parameter

* propagate pipeline to args

* unhardcode pipeline dispatch parameter

* refactor vector size

* put warp tile out of dispatch

* rename template parameter for trait

* rewrite vector size in terms of problem

* mark policy-internal struct variable as device

* factor out input distribution and thread access pattern from policies

* reword vector size

* use datatype across batched transpose pipelines, problems and kernel

* remove transpose traits from lds pipeline

* add padding to the lds pipeline *interface*

* add comment

* remove ck_tile example #37

* update cmakelists

* add test for new pipeline

* update batched transpose test

* roll back load_tile_transpose changes

* remove comments

* pack dispatch parameters into a config

* padM can be enabled

* adjust lds vector size to enable padding along N

* update test

* clean up logic

* swap m/n input vector size

* adjust perf test script

* sweep over C/W in perf test

* count both read and written bytes into bandwidth (x2 the number)

* clang-format

* widen size range for perf test

* remove 64k x 64k case; it's too large for index

* remove thread tile from dispatch

* Solve merge conflict

* fix compile

* modify the transpose

* solve the test error and clang format

* Add v3 support for Groupd fwd conv+bias+clamp & ckProfiler (#2463)

* Add logging to IsSupported.

* Less casting in AddClamp

* Conv+bias+clamp instances & profiler BF16

* Fix 3D instances & run just 1x for verification.

* :Run just once for verification conv fwd.

* ckProfiler conv fwd clampwq

* Remove exec bit & formatting

* Add support for MultiD for grouped conv fwd v3.

* Enable 2Lds.

* clean

* align instances

* align instances

* profiler fixes

* Fixes

* fix

* fix

---------

Co-authored-by: Adam Osewski <root@quanta-ccs-aus-f01-19.cs-aus.dcgpu>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>

* Fixing 0ms and inf GB/s issue in img2col (#2565)

issue :
====
``` sh
$ bin/tile_example_img2col
Perf: 0 ms, inf GB/s
```

solution :
======
Problem occured because config.time_kernel is false by default.
if false, then no need to calculate perf, just print proper message

`image_to_coloumn: pass, No Perf generated due to config.time_kernel=0`

* merge with develop

* solve clang format

---------

Co-authored-by: ThomasNing <thomas.ning@amd.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
Co-authored-by: Adam Osewski <root@quanta-ccs-aus-f01-19.cs-aus.dcgpu>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
Co-authored-by: rahjain-amd <Rahul.Jain@amd.com>
2025-07-26 21:51:54 -07:00
Bartłomiej Kocot
5741edf761 Fix clang format (#2567)
* clean

* clang format fix
2025-07-25 09:54:34 -07:00
rahjain-amd
78082855d8 Fixing 0ms and inf GB/s issue in img2col (#2565)
issue :
====
``` sh
$ bin/tile_example_img2col
Perf: 0 ms, inf GB/s
```

solution :
======
Problem occured because config.time_kernel is false by default.
if false, then no need to calculate perf, just print proper message

`image_to_coloumn: pass, No Perf generated due to config.time_kernel=0`
2025-07-25 21:15:50 +05:30
Enrico Degregori
b01a27ff22 Support b_scale: (#2350)
- extend pipeline v1 and v3
 - add instances
 - add tests
 - add example

Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
2025-07-24 18:49:58 -07:00
Mateusz Ozga
b507d889c1 [CK_TILE] Introduces a new GEMM API that splits the existing basic GEMM class into multiple specialized classes. (#2520)
* Init commit new API

* apply clang-format

* PreShuffle preapring

* Apply Preshuffle condition to universal_gemm

* Fix: convert size_t to index_t

* Review changes

* Mode 100755 -> 100644

---------

Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
2025-07-24 20:39:56 +02:00
Yi DING
4338346b10 Use filename but not path to filter compilation (#2556) 2025-07-24 17:38:14 +08:00
Yashvardhan Agarwal
606b0cc947 [CK_TILE] Support for elementwise kernel (#2246)
* Elementwise kernel implementation

Co-authored-by: Sami Aario <samaario@amd.com>
Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com>
Co-authored-by: yashagar <yashagar@amd.com>

* Elementwise with generalized nDims

* Adding the n-ary input tensor feature

* Generalize dimensions on top of inputs

* Add TFLOPS + remove std usage for tuples

* 1D basecase optimization

* Cleanup code + refactoring to a common interface

* Generalize to unary and add an example

* Cleanup, refactoring and commenting

* Suggestions for LWPCK-3170: elementwise kernel improvements

* Clang-format: remod.py

* Replace InputTensorType with XDataType as the type of input_tensors

* Add Tuple::apply and use it in ElementWiseKernel::operator to call operation with the exact number of arguments in xs

* Move examples to folder 19_elementwise

* Add missing copyright headers and fix some existing ones

* Replace an assert with throw std::runtime_error in elementwise example

* Avoid reading the output by using make_static_distributed_tensor for y_tile

* Removed two unused includes

* No need to move windows to the next block when each workgroup processes a single tile

* Only copy input tensors to the device

* Use get_warp_size to obtain warp size, and use ceiling division for grid size also for the unary example

* Adding output strides to the kernel, transposition example and update the other examples

* Changes made by remod.py

* Use default template parameter values for memory operation and coherence in a call to make_naive_tensor_view

* Move binary operations to include/ck_tile/ops/elementwise/binary_elementwise_operation.hpp

* Reuse generic reference binary/unary operation in examples + refactoring the transpose reference

* Fix comments in elementwise_example.cpp

- Refer to AMD terminology except when suggesting NVIDIA alternatives in parentheses
- ElementWiseTraits was renamed to ElementWiseShape
- Adopt suggestions made by Copilot when prompted to check for factual or typographical errors

* Simplify CMakeLists.txt and remove the unused variables this uncovers

* Rename a file and fix some copyright statements

* Changes made by script/clang-format-overwrite.sh

* Add basic unit test for ElementWiseKernel

* Remove left-over uninformative comment in apply unit test

* Changes made by clang-format-overwrite.sh

* fixup! Use default template parameter values for memory operation and coherence in a call to make_naive_tensor_view

* Clean up test_tuple_apply.cpp and test_elementwise_1d.cpp

* Use make_uniform_array_with_factory to define h_xs and d_xs_mems_owner as type std::array

* Use a DeviceMem constructor that calls get_element_space_size_in_bytes internally

* Move examples to folder 20_elementwise

* Reduced register pressure on the CK tile elementwise kernel + add 4d input example to be able benchmark against old CK

* Fix CLang formating

* Bump up the elementwise example folder number

* Elementwise: add padding + minor cleanup

* Add Vector Size inference + fix issue with wrong vectorization due to missing GuaranteedLastDimensionVectorStride setting in make_naive_tensor_view

* Add isSupportedArg to Elementwise kernel + addapt example and unit tests

* Fix clang-format on the unit test file

---------

Co-authored-by: Damien Lejeune <damien.lejeune@amd.com>
Co-authored-by: Sami Aario <samaario@amd.com>
Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com>
Co-authored-by: Aviral Goel <aviral.goel@amd.com>
2025-07-24 11:21:45 +02:00
jakpiase
6681593864 [CK_TILE] Grouped Convolution Backward Weight Kernel (#2357)
* [CK TILE] Grouped Convolution Forward Kernel

* custom vector size

* fixes

* refactor

* resolved conflicts

* rebase fixes

* fixes

* tmp

* add working support for splitk

* minor fix

* fixes

* fixes

* minor fix

* small fix

* Split K and preprocessing fixes

---------

Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
2025-07-24 10:41:35 +02:00
Illia Silin
1b6f024836 refactor fmha_bwd.py (#2546) 2025-07-23 09:09:56 -07:00
Haocong WANG
a5fdc663c8 fix async copytest bug (#2509)
* fix async copytest bug

* Add block_sync_lds_direct_load utility

* fix the s_waitcnt_imm calculation

* Improve s_waitcnt_imm calculation

* fix vmcnt shift

* add input validation and bug fix

* remove unnecessary output

* move test_copy into test

* change bit width check

* refactor macros into constexpr functions

which still get inlined

* wrap s_waitcnt api

* parameterize test

* cleanup

* cleanup fp8 stub

* add fp8 test cases; todo which input parameters are valid?

* replace n for fp8 in test cases

* add large shapes; fp8 fails again

* change input init

* test sync/async

* time the test

* clang-format test

* use float instead of bfloat to cover a 4-byte type

* fix logic - arg sections should be 'or'd

* make block_sync_lds_direct_load interface similar to old ck

* fix a few comment typos

* name common shapes

* revert the example to original logic of not waiting lds

* clang-format

---------

Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
2025-07-23 00:14:02 -07:00
Cong Ma
e62710e461 ck_tile kernel for gemm with groupwise quantized A tensor (#2473)
* ck_tile kernel for gemm with groupwise quantized A or B tensor.

This change introduces new pipelines with Intrawave scheduler and block gemm primitives that loads the scale tensor to registers to perform dequantization post MFMA on C tensor in registers.

Scale tensor data, AQ/BQ is spliced across threads in registers and not stored in LDS.

Current support is for the following combinations, but it should be fairly straightforward to extend support to more formats.

1. fp8, fp8 -> f32
2. bf8, bf8 -> f32
3. i4, fp8 -> f32
4. i4, bf8 -> f32

Group size can go down to as low as K length of underlying WarpGemm primitive.

For Gemm problems with quantized B tensor, this change also introduces preliminary support for flatmm pipeline which loads B tensor directly into registers.

* [Block Scale Gemm] Only run gemm quant examples on __gfx94__

- Only run gemm quant examples on __gfx94__ for usage of
  `v_cvt_pk_fp8_f32`
- Format the code

* [Block Scale Gemm] Remove Bquant Gemm BlockScale

This cleanup is in preparation for future development of bquant. By
isolating Aquant-related code, we can streamline the codebase and make
it easier to add and maintain bquant functionality in subsequent
updates.

* [Block Scale Gemm] Format code with clang-format-12

The latest clang-format (v19) in ROCm 7.0 generate different result than
clang-format-12 which is used in CK CI.

Format code with clang-format-12 for consistency.

* [Block Scale Gemm] Split the k direction loop

- Split the k direction loop in block_universal_gemm_as_quant_bs_cr.hpp
   to make the logic clearer.
- Disable C transposition.

* [Block Scale Gemm] Move block scale gemm example to 38_block_scale_gemm

* [Block Scale Gemm] Update copyright

* test

* Add TailHandler

* Move TileDistributionEncodingPatternAQ

* Refactor

* refactor

* fix bug

* fix bug

* help solve the PR comment

* Format the code

* [Block Scale Gemm] Add unit tests

* [Block Scale Gemm] Add support to 16x16x32 MFMA

- Add support to 16x16x32 MFMA
- Fix a bug when exchange data crossing lanes

---------

Co-authored-by: Vijay Krishnamoorthy <vjkrish@meta.com>
Co-authored-by: Cong MA <congma13@ctr2-alola-ctrl-01.amd.com>
Co-authored-by: ThomasNing <thomas.ning@amd.com>
2025-07-23 00:10:16 -07:00
Linjun-AMD
095393276a h_dim256 fmha use async_qr pipeline (#2510) 2025-07-18 09:59:38 +08:00
slippedJim
05b65d0c7c update (#2519) 2025-07-17 15:24:19 +08:00
Yi DING
f1d8ad2818 [CK_TILE] Use read_tr in universal gemm (#2436)
* Use read_tr in universal gemm

* Enable all instances back

* Revert example37 changes

* Resolve comments

* resolve comments 2

* Fix assertion msg

* fix the gemm basic

* change index_t to bool for preshuffle variable

* Solve the comment

---------

Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
Co-authored-by: AviralGoelAMD <aviral.goel@amd.com>
2025-07-16 23:56:22 -07:00
Khushbu Agarwal
579bd73435 Fixing numerical error, and interchange preshuffle configs to match with flatmm (#2515) 2025-07-16 22:33:03 -07:00
linqunAMD
fbd9f32abe [CK][CONV] Support NCHW in class DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1 (#2459)
1. Port NCHW support from ConvFwd (#2375) to conv bwd data
2. Add new instance device_grouped_conv_bwd_data_xdl_f16_nchw_instances for nchw

Co-authored-by: azhuang <anzhong.huang@amd.com>
2025-07-17 08:19:57 +08:00
linqunAMD
6e76b82059 Fix build errors on windows (#2456)
* Fix build errors on windows

* correct clang format

---------

Co-authored-by: Lin, Qun <Quentin.Lin+amdeng@amd.com>
2025-07-16 07:58:23 -07:00
MHYangAMD
3499fe67ff [CK_TILE] Enhance RMSNorm Accuracy: New Pipeline Pass for Selectable Implementation (#2409)
* Add Rmsnorm2dFwdPipelineModelSensitiveT5Pass

* Update rmsnorm2d_fwd_pipeline_model_sensitive_pass

1.  Add BlockReduce2dTreeCrossWarpSync

* Add Rmsnorm2dFusedModelSensitiveEnum

* Update patch

1. Reverse generate.py
2. Remove comment in generate.py
3. Update tree cross warp reduce

* Refactor RMSNorm model enum and introduce T5-like option

* Update the n stage for cross warp reduce

* Add new cmdline option in RMSNorm for new pipeline testing

---------

Co-authored-by: Clement Lin <clement.lin@amd.com>
Co-authored-by: ClementLinCF <162283536+ClementLinCF@users.noreply.github.com>
2025-07-16 14:05:26 +08:00
rahjain-amd
6b09f0823e add missing condition for bf16 (#2502)
Without this DataType = unknown -
``` sh
Run Flatmm kernel with DataType = unknown M =1280 N =16384 K =1024 StrideA =1024 StrideB =1024 StrideC =16384 : 0.228837 ms, 187.687 TFlops, 341.374 GB/s,
```

after this change
```sh
Run Flatmm kernel with DataType = bf16 M =1280 N =16384 K =1024 StrideA =1024 StrideB =1024 StrideC =16384 : 0.227029 ms, 189.181 TFlops, 344.092 GB/s,
```
2025-07-15 21:25:56 +05:30
carlushuang
cfe211cc60 [CK_TILE] moe sorting optimize local_token (#2469)
* fix bug in loops that need use local tokens to compute

* support extra chain local_token

* update

* update

* refine some main

* update

* support dispatch_policy

* fix 15 example
2025-07-15 09:42:18 +08:00
Andriy Roshchenko
518dc21ae8 MX GEMM - FP6 Support in GEMM MX v3 Pipeline (#2481)
* Add GEMM MX BF6 example

* Fix BF6 type_convert

* Add type_convert for bf16x6

* Add compare operator to f4x2_pk_t

* Update README for 67_gemm_microscaling

* Fix host tensor initialization with integer values for FP8
2025-07-11 13:07:05 -06:00
Khushbu Agarwal
d239b91fd5 Merge flatmm Operator with universal gemm (#2434)
* Initial commit

* Adding new tile partitioner to flatmm

* intermediate changes

* debugging kernels

* Updating flatmm example to universal gemm example

* updated flatmm kernel to run via gemmKernel

* update universal gemm to incorporate flatmm

* debug

* Fix flatmm call

* Fixing other kernels and tests for API changes

* clang formatted

* fixing gemm tests

* added test for flatmm and simplify kernel arguments

* adding flatmm test

* fix test for flatmm

* simplify gemm kernel with flatmm

* remove flatmm related files

* addressing review comments and code clean up

* resolving empty file

* resolving empty file

* clang formatted

* addressing review comments

* enable persistent kernel for flatmm

* reverted the removed files for flatmm

* reverted the removed files for flatmm

* changed flatmm to weightPReshuffle; removed the _1 added in teh faltmm example

* some more renames

* clang formatted
2025-07-11 08:27:55 -07:00
Andres Lugo
aadeffde18 Update FMHA recipe for Pytorch SDPA integration (#2480)
* Add receipts in splitk and appendk

* remove grouped

* Remove logits

---------

Co-authored-by: Max Podkorytov <4273004+tenpercent@users.noreply.github.com>
2025-07-10 09:00:23 -07:00
Illia Silin
d9b37c7121 Fix blockscale fp8 gemm examples (#2476)
* fix blockscale fp8 gemm examples

* refactor the compiler flags

* fix hip version calculation
2025-07-10 07:12:13 -07:00
Po Yen Chen
ad9863fe05 [CK_TILE] Low CU utilization optimization for fMHA fwd kernels (#2402)
* Wrap tile size mapping as class method

* Warp pipeline generating as class method

* Add constraint as kernel dispatching criteria

* Support mutltiple tile size for a (hdim, hdim_v) combination

* Use smaller tile size if CU utilization is low

* Use integar as the key of the tile size map

* Fix type error

* Simply override parent class method return value

* Add attribute to eliminate warnging

* Allow using environment variables to turn on/off custom factory

* Unify param naming style

* Add missing HIP runtime include directive

* Fix os.environ.get() usage
2025-07-09 22:01:33 +08:00
Haocong WANG
5557eadce6 [CK TILE] Fix FA build filter (#2369)
* Fix for fwd/bwd kernel build filter

* fix bwd code

* cmake depends & bwd filter order fix

* revert unexpected reformat

* Avoid change fmha bwd filter order for downstream compatibility

* Revert unexpected changes

---------

Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
Co-authored-by: Ding, Yi <yi.ding@amd.com>
2025-07-08 10:42:07 +08:00
Thomas Ning
f240ae3248 Enable Async Copy for MI355 (#2425)
* add for async load builtin

* add async load api

* fix some compiling errors

* fix a compiling error

* fix some compiling errors

* add a pipeline which copies from v4

* add a new pipeline for async load

* fix some compiling errors

* add async load tests

* fix some issues in async load

* fix

* fix async inline assembly

* fix async inline assembly

* add ignore header file

* comment some not gfx950 codes

* comment some not gfx950 codes

* fix a error

* update async load apis

* fix lds descriptor

* fix a compiling error

* fix some compiling errors

* fix a descriptor issue

* update lds descriptor

* change async pipeline's tile distribution pattern from thread to warp

* fix clang format

* update async policy

* fix a CRTP issue

* fix a typo error

* change lds layout

* fix some sync issues

* improve codes

* delete the async test

* fix a commented format issue

* avoid compiling device functions when compile host

* make gemm run

* add the copy kernel support

* finish the feature

* Address comment

* add the support for buffer_builtin

* solved the merging problem

* Comment Addressed

---------

Co-authored-by: joye <joye@amd.com>
Co-authored-by: joyeamd <John.Ye@amd.com>
2025-07-07 10:08:49 -07:00
Andriy Roshchenko
054f85ab7c MX GEMM - FP6 Example (#2419)
Adds support for MX FP6 data type in MX GEMM block pipeline version v1.
Provides an example of MX FP6 GEMM algorithm.

---------

Co-authored-by: OscarXu <huaiguxu@amd.com>
Co-authored-by: aska-0096 <haocwang@amd.com>
Co-authored-by: mtgu0705 <mtgu@amd.com>
Co-authored-by: Your Name <you@example.com>
Co-authored-by: lalala-sh <Jiaxing.Wen@amd.com>
Co-authored-by: valarLip <340077269@qq.com>
Co-authored-by: Ding, Yi <yi.ding@amd.com>
Co-authored-by: feifei14119 <feiw@amd.com>
Co-authored-by: Lin, Qun <qlin@amd.com>
Co-authored-by: joye <joye@amd.com>
2025-07-07 10:33:26 -06:00
rahjain-amd
ad593c286f Fixing Debug build (#2404)
Failed to build `tile_example_fmha_bwd` due to below error

```
/home/rahjain/src/composable_kernel/example/ck_tile/01_fmha/fmha_bwd.cpp:358:30: error: comparison of integers of different signs: 'size_type' (aka 'unsigned long') and 'ck_tile::index_t' (aka 'int') [-Werror,-Wsign-compare]
  358 |         assert(slopes.size() == nhead);
      |                ~~~~~~~~~~~~~ ^  ~~~~~
/usr/include/assert.h:103:27: note: expanded from macro 'assert'
  103 |      (static_cast <bool> (expr)                                         \
      |                           ^~~~
/home/rahjain/src/composable_kernel/example/ck_tile/01_fmha/fmha_bwd.cpp:989:16: note: in instantiation of function template specialization 'run<FmhaBwdFp16>' requested here
  989 |         return run<FmhaBwdFp16>(arg_parser) ? 0 : -2;
      |                ^
/home/rahjain/src/composable_kernel/example/ck_tile/01_fmha/fmha_bwd.cpp:358:30: error: comparison of integers of different signs: 'size_type' (aka 'unsigned long') and 'ck_tile::index_t' (aka 'int') [-Werror,-Wsign-compare]
  358 |         assert(slopes.size() == nhead);
      |                ~~~~~~~~~~~~~ ^  ~~~~~
/usr/include/assert.h:103:27: note: expanded from macro 'assert'
  103 |      (static_cast <bool> (expr)                                         \
      |                           ^~~~
/home/rahjain/src/composable_kernel/example/ck_tile/01_fmha/fmha_bwd.cpp:993:16: note: in instantiation of function template specialization 'run<FmhaBwdBf16>' requested here
  993 |         return run<FmhaBwdBf16>(arg_parser) ? 0 : -2;
      |                ^
2 errors generated when compiling for gfx942.
```

Fixed with proper cast
2025-07-07 14:46:22 +05:30
ltqin
9f4c5d7372 ck tile pagedkv prefill (#2405)
* add prefetching physical block id for pagedkv

* start add pagedkv prefill

* rename pipeline

* add kernel for pagedkv

* add an init version pagedkv prefill

* fix redefine issue

* add struct BlockFmhaFwdPagedKVPipelineProblem and fmha_fwd_pagedkv_args

* generate dispatch code

* add body generating code

* comipling pass

* remove dropout from pagedkv

* set lse to false in generating code

* start changing qr kernel to pagedkv

* init version of  kernerl with pagedkv

* change names of file that are generated

* chang host validation for pagedkv prefill

* using iglp to change blockgemm

* add kernel files to op head file

* show parameters

* rewrite print parameter fun

* add fwd

* remove default parameter of GridSize

* format

* fix nhead issue and add seqlen_k_ptr to batch mode

* format code

* remove no-longer used code

* format

* fix some comments

---------

Co-authored-by: ltqin <letaoqin@amd.com>
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
2025-07-07 16:16:54 +08:00