[CK][CK Tile] Grouped Convolution backward weight profiler
flush cache (#5454)
## Motivation
Flush cache to get more stable results during profiling old ck and ck
tile.
## Technical Details
Flush cache before each kernel call and one more first run.
## Test Plan
test_grouped_conv_bwd_weight_tile
## Test Result
pass
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-966
[CK][CK Tile] Grouped Convolution Backward Weight set of
fixes (#5387)
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## Motivation
Grouped Convolution Backward Weight split k fixes for CK tile kernels
## Technical Details
- get k batch from kargs to get deduced k batch
- multiply zeroing size by data type size
- disable v6 (producing a incorrect results)
## Test Plan
test_grouped_convnd_bwd_weight_tile
## Test Result
Pass
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_TILE, CK_BUILDER] Add two-stage bwd weight kernels to CK
Tile profiler (#5237)
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## Motivation
PR #4797 added CK Tile bwd weight kernels to the CK Profiler. The
two-stage kernels were not supported in the initial PR. This PR adds the
the missing bwd weight two-stage kernels to the CK Profiler.
## Technical Details
Extended the CK Tile conv builder factory to build also the elementwise
ops required for the two-stage kernels. Extended the CK Builder for CK
Tile instance to accept the two-stage flag as part of the algorithm
configuration.
## Test Plan
Added units tests for CK Builder that verify the two-stage kernel
construction.
## Test Result
If CI passes, the added unit tests are passing.
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK][CK Tile] Improvements for grouped conv fwd tile
profiling (#5114)
## Motivation
Improve profiling for grouped convolution forward for better comparison
between CK and CK Tile
## Technical Details
- Include preprocessing time for ck tile
- Add flush cache for conv fwd profiler
- Switch configs to builder reflect
- Add KPerXdl deduce
- Add non-grouped ported instances
## Test Plan
test_grouped_convnd_fwd_tile
## Test Result
pass
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-786
[CK_BUILDER] Add
DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3 to CK Builder (#5284)
Add factory, InstanceTraits, and conv traits support for the WMMA V3
forward convolution kernel, enabling the CK Builder to generate and
dispatch this kernel variant used by MIOpen on gfx11/gfx12 GPUs.
## Motivation
As reported in issue #4944, MIOpen includes WMMA V3 forward convolution
kernels, so this PR adds support for those kernels similarly to other
supported kernels.
## Technical Details
This follows the same implementation as the other kernels. I added some
support for reflection, but I left a few todos since we need to
generalize our convolution traits to generalize across WMMA/MFMA and
CK/CKTile.
## Test Plan
Added faster tests to `ninja smoke-builder` that check the
instance-traits logic, and I added longer tests that instantiate
kernels, following the existing pattern in other kernals.
## Test Result
I tested all code with `ninja check-builder` on a gfx1101 build and ran
on gfx1101.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
[CK_BUILDER] Clean up ConvDescription output formatting
(#5085)
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The `ConvDescription::getDetailedDescription()` output had several
issues that made it harder to read and potentially misleading:
1. **Bug fix**: The LDS padding field was incorrectly displaying
`dst_scalar_per_vector_k1` instead of the actual `lds_padding` value
2. **Noise reduction**: Optional parameters that weren't set were
printing unhelpful messages like "Struct does not contain optional
gemm_padding argument" — these add clutter without providing value to
the reader
3. **Formatting inconsistencies**: Trailing spaces after colons (e.g.,
`"Warp Gemm parameters: "`) and a stray trailing `×` in tile dimensions
4. **Missing thread cluster lengths**: The threads per axis are not
shown.
**Changes**:
- **Fixed the LDS padding bug** by using
`traits_.a_tile_transfer.transfer_params.lds_padding` and
`traits_.b_tile_transfer.transfer_params.lds_padding` instead of
duplicating `dst_scalar_per_vector_k1`
- **Simplified optional parameter handling**: Changed from printing
"Struct does not contain..." messages to simply omitting absent optional
values. Also switched from `.value_or()` to direct dereference (`*`)
since we're already inside an `if` check
- **Cleaned up formatting**: Removed trailing spaces after colons and
the extra `×` at the end of tile dimension lists
- **Added missing thread cluster lengths**: Added X×Y×Z" display for
both A and B tile transfer sections.
- **Fixed typo**: "Do Padd Gemm" → "Do Pad Gemm"
- **Fixed typo**: "scr" → "src"
- **Fixed typo**: "tensros" → "tensors"
- `ninja smoke-builder` ✓
- `ninja check-builder` ✓
The test file updates reflect the corrected expected output, which now
shows the actual `lds_padding` values (0 or 1), shows thread cluster
lenths, and omits the verbose "Struct does not contain..." lines.
**Note**: This PR follows PR #5083.
Proof of concept for removing forward declarations
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## Motivation
Currently, we forward declare CK device operation templates in
CK-Builder's reflection code:
9b168082b7/experimental/builder/include/ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_xdl_cshuffle.hpp (L13-L57)
This is mainly required to break a circular dependency in reflection.
The architecture of that is as follows:
MyDeviceOp implements GetInstanceString(). This is typically defined
directly in the class definition (no forward declaration).
GetInstanceString() calls instance_string<MyDeviceOp>()
instance_string<MyDeviceOp>() calls
InstanceTraits<MyDeviceOp>::instance_string()
InstanceTraits has a specialization for MyDeviceOp which implements
instance_string()
So order for GetInstanceString() to work properly, InstanceTraits must
already be defined. And for InstanceTraits to be defined, the device op
needs to be defined. In order to do that, we are currently using
aforementioned forward declaration.
## Technical Details
C++'s lazy template evaluation is used by calling into an as-of-yet
undefined function static member function of
`InstanceTraits<MyDeviceOp>` in `GetInstanceString()`, and then
specializing `InstanceTraits` only _after that_. The caveat here is that
both the device op itself as well as the instance traits specialization
must be in scope, otherwise there would be an undefined function error.
In practise, we can solve that either by placing the instance traits
directly into the file that defines `MyDeviceOp`, or possibly by using a
`.inc` file to keep the concerns separated.
## Test Plan
The results were verified by running the existing regression tests for
CK Builder
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_BUILDER] Simplify the TreeFormatter.
My original design wrote each line streaming, so developers had to keep
track of the indentation depth and remember when to use `writelast` for
the last element at a depth. This was a source of a lot of cosmetic
output errors, and that is likely to get more complicated as we add
optional branches.
We switch to a tree-building interface with a simple `add` method. The
only cost is that we have to defer string building, which is a good
tradeoff for our use case.
Tested with `ninja smoke-builder`.
[CK_BUILDER] Add BILINEAR and ADD_CLAMP elementwise operation
mappings to CK builder (#5026)
## Motivation
The CK kernels that MIOpen consumes use the BILINEAR and ADD_CLAMP
operations. The operation mappings in the CK Builder API need to be in
place to be able to instantiate those kernels using the builder.
## Technical Details
Add the BILINEAR and ADD_CLAMP operation mappings to the builder
## Test Plan
* Added builder tests for new helpers
## Test Result
* New tests pass locally, waiting for test run
## Submission Checklist
- [X] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_TILE] Add CK Tile bwd weight profiler
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## Motivation
To compare old CK and CK Tile, we need to extend the current CK profiler
to support running also CK Tile instance with the same API. In order to
have the same instance coverage in CK Tile compared to the old CK, I've
added code generation from old CK configurations to CK Tile instances
using the CK Builder.
## Technical Details
- The codegen python script for CK Tile fwd convs is extended to support
also bwd weight and bwd data.
- The generated instances are added to the CMake build (target
`device_grouped_conv_bwd_weight_tile_instance`s).
- A new profiler op (`grouped_conv_bwd_weight_tile`) has been added to
the CK Profiler.
[CK_BUILDER] Update developer notes in the CK Builder source
directories (#5038)
## Motivation
This PR updates the developer notes for the CK Tile builder. It captures the current state of the implementation in more detail, and frames the description around the need to have true facade.
There is no functional change, only better alignment of developer notes with the current code.
This doc clearly explains the current technical debt: that we have created many facades that expose
the implementation details. There is an expanded section on reflection that explains how unified
reflection will help clarify the unified builder design.
Additional changes are just better accounting for the current state of the code, including previously
undocumented operations. A few typos and cosmetic issues are cleaned up, too.
[CK_BUILDER] ck builder conv transfer fix
## Motivation
This PR fixes how CK Builder is validating transfer vector size and adds
proper validation for LDS transfer vector size as well.
## Changes:
* [__source vector dim__] -- Before this PR the data transfer validation
logic didn't allow to set the source vectorized dimension to 1. However
there are CK instances that are doing this when the group merging is
used. This is used only for
`DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle` kernel.
* [__valid vector size__] -- Before this PR the validation logic
concerned only single instruction maximum vector size. However our
buffer loading logic has implemented support for loading more values
through multiple buffer instructions. This again was discovered to be
used in some of the convolution instances. Thus this behavior was
reflected in validation logic.
* [__valid LDS vector size__] -- Before this PR the LDS vector size
validation was done in the same way as VMEM. This PR adds proper LDS
vector size validation based on the available LDS instruction sizes.
## Test Plan
Run CK BUILDER conv fwd factories tests
## Test Result
All CK BUILDER conv fwd factories work (except DL one & ck tile since
they're not yet added now)
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_Builder] added bwd data kernels to builder factory
(#4582)
This PR adds bwd data wmma and xdl kernels to the ck builder, their
instance and conv traits as well as tests for the above.
[CK] Small improvements for grouped conv backward weight
(#4872)
## Motivation
Improvements for CK Tile convolution builder run function and atol/rtol
calculations.
## Technical Details
- Add preprocessing function for wrw when k_batch is larger than 1 for
builder run function
- Divide num acums by number of groups to get real number of accums
## Test Plan
CI wrw tests
## Test Result
pending
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-783
[CK][CK TILE] Improve oob check
## Motivation
Improve OOB checks. Remove permutes which have been generated by thread
buffer zero clear. at now in assembly there is only condmask instead of
permute + condmask.
Change number of KPack for generated instances
## Technical Details
Remove permute instructions from assembly
## Test Plan
test_grouped_convnd_fwd_tile
## Test Result
passed
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_BUILDER] Fix two staging-compiler errors in CK builder
code (#4598)
This PR fixes two compiler warnings that report as errors with the
latest compiler:
1. In tensor descriptor, the `operator[]` accessor needs a
`[[clang::lifetimebound]]` attribute.
2. In the unit tests for device buffer, there is a test that explicitly
checks for an error on a pointer that went out of scope, so it needs a
to disable `-Wlifetime-safety-permissive` in the test code.
I ran the CK `smoke-builder` tests with the staging compiler to verify.
[CK_BUILDER] Move some smoke tests that require GPU
Since the CK builder is focused on compile time logic, let's keep the
`smoke-builder` target CPU-only so that it can be ran without a CPU.
Alternatively, we could define a `smoke-cpu-builder` or some special
subtarget, but it's probably simpler to just stick to CPU for this. (My
thinking is that in general GPU testing will be heavier than the smoke
tests. Further, the GPU testing code will likely move outside of the
builder once builder code is moved out of experimental.)
This PR clarifies that CPU-only intention for `smoke-builder` and moves
some GPU testing code to `smoke-regression`.
[CK][CK TILE] Add has hot loop check for pipeline v1
## Motivation
Add has hot loop check for pipeline v1 (v1 basic and v1 basic async).
Enable more tests which have been fixed by this change.
## Technical Details
Hot loop has been executed without num loop check.
## Test Plan
test_grouped_convnd_fwd_tile
## Test Result
Passed
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-651
AICK-663
[CK][CK Tile] Temporary disable grouped conv fwd tile comp
async instances (#4457)
## Motivation
[CK][CK Tile] Temporary disable grouped conv fwd tile comp async
instances due to the failures
## Technical Details
disable configs to not comple these instances
## Test Plan
test_grouped_convnd_fwd_Tile
## Test Result
pending
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK] CK Tile grouped convolution direct load
## Motivation
CK Tile grouped convolution forward direct load support.
## Technical Details
Basic pipeline for direct load and new instances for forward for v1 and
v4 pipelines.
## Test Plan
test_grouped_convnd_fwd_tile
## Test Result
CI pending
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-130
[CK_TILE] Add support and tests for V6 pipeline in conv fwd
(#4357)
Added support for conv v6 pipeline in ck tile's convolution forward
kernel. CK Tile v6 pipeline is the equivalent to old ck's V5 pipeline
and should be faster than other pipelines for some cases. This PR also
adds tests inside profiler that's currently inside experimental
directory, so now we should be able to detect regressions easier.
Force merging because I verified this fix manually:
git checkout develop
git pull
ninja smoke-builder (failed to build, as expected)
git checkout rvoetter/ckb-fix
ninja smoke-builder (passed!)
* ck-builder: tensor copy function
This function copies one tensor to another, so that the memory
layout can be changed between them.
* ck-builder: fix ck::bhalf literals
These types don't work properly.
* ck-builder: abstract compare_elements in gpu_verification.hpp and make builder use it
This reduces the amount of duplicated code a bit.
* ck-builder: add flat tensor iterator
This "iterator" type pretends to be a pointer, useful for passing
tensors to functions expecting pointer-like types.
* ck-builder: integrate validation with ck gpu verification
By templating the gpu_verify function over iterators, we can use
the new FlatTensorIterator to adapt the function to multi-
dimensional tensors without changing either implementation
too much.
* ck-builder: add check_by_accumulations
This changes the gpu_verification.hpp code to also accept "iterator"
types for the relevant gpu_verify and gpu_reduce_max functions.
* ck: fix test_gpu_verification GenerateRandomData for bhalf
is_integer_it<bhalf_t> yields true, but it is not actually
an integer.
* ck: make gpu_verification kernels be proper persistent kernels
Previously these were using a hardcoded value for the grid size. This
commit changes that so that the grid size is automatically derived
from the kernel's occupancy and the number of multiprocessors on
the GPU.
* ck: clean up gpu_verification.hpp using block_reduce
This implements a small generic block reduce function, and rewrites
the rest of gpu_verification.hpp using that function to clean it up
a bit.
* ck-builder: doc typos
* ck-builder: update testing readme with validation interface.
* ck-builder: rebase fixes + review comments
* ck-builder: fix device integer generation with float types
Passing bfloat here causes a nans due to type_convert performing
a bitcast.
* ck: another bhalf_t bug
CK expects that int-generation with ck::bhalf_t yields bhalf integers,
not unsigned integers. This makes the logic of FillUniformRandInteger
compatible with GeneratorTensor_2<InDataType>, however idiotic that
may be.
* added reflection for conv_fwd_multiple_d_wmma_cshuffle.hpp
* added reflection for device_grouped_conv_bwd_weight_xdl_cshuffle
* added reflection for device_grouped_conv_bwd_weight_xdl_cshuffle v3
* added reflection of max_transpose parameters
* fix printing of std optional parameters
* fix use of undefined ck::index
* added conv traits for device_grouped_conv_bwd_weight_multiple_d_xdl_cshuffle
* added xdl two stage instance to reflection
* added additional variables
* added reflection for grouped_conv_bwd_weight_multiple_d_wmma_cshuffle, _v3, grouped_conv_two_stage_wmma_cshuffle_v3,
* added reflection for device_grouped_conv_bwd_weigh_wmma_cshuffle_v3
* added reflection for bwd_weight_wmma_cshuffle
* added comments back in
* add printed output for optional parameters
* update README
* fix typo
* added num_gemm_k_prefetch_stage and small fixes
* modified test string due to reflection of new parameter
---------
Co-authored-by: Kevin Abraham <kevin.abraham@streamhpc.com>
* ck-builder: restructure testing conv
In order to prepare for bwd of conv testing, this commit moves some
files and types around so that we can reuse ckt::Args for both forward
and backwards convolution.
* ck-builder: decouple fwd_ck.hpp and fwd_reference.hpp from fwd.hpp
This will allow us to more easily include fwd.hpp from backwards
definitions, which is required for initializing bwd values.
* ck-builder: fix layout of test_ckb_conv_bwd_weight_xdl_cshuffle_v3
Turns out that the supplied layout isn't actually supported...
* ck-builder: ck and reference conv integration for bwd weight
* ck-builder: ck bwd weight execution test
* ck-builder: ckt::run support for ck-tile bwd weight
* ck-builder: ck tile bwd weight execution test
* ck-builder: extra debug printing in MatchesReference
* ck-builder: make ckt::run return RunResult
This type is more convenient than std::tuple, as it will allow us to
use google test matchers with this in the future.
* ck-builder: RunResult matcher
Using EXPECT_THAT(..., SuccessfulRun()) will generate a check and a nice error
message about how and why running an algorithm failed.
* ck-builder: doc fixes
* ck-builder: add missing headers
* ck-builder: remove SPATIAL_DIM parameter from ConvTensorLayouts
This information is already in the SIGNATURE, so its pointless to pass it
separately. This streamlines the interface of those functions a bit. Also
touches up the style of those files in general.
* ck-builder: implement reference conv using old ck
The old ck implementation is more featureful and better tested.
* ck-builder: replace test_reference_execution reference with old ck
This strips out the ck-tile gpu reference implementation completely.
* ck-builder: clean up test_reference_execution
- Remove unneccesary messages
- Replace EXPECT_TRUE(true) with EXPECT_NO_THROW()
* Rename member variable to better reflect its actuall meaning.
* Add transfer checks for conv fwd xdl.
* Validate tensor layouts & vector size conv fwd v3.
* Add combined transfer concepts.
* Add transfer concepts for conv fwd factories.
* Fix clang format
* Add helper instruction to get max mem vector instruction width.
* Apply review comments.
* Rename thread cluster access(->arrange) order concept
* FIx merge artifacts.
* Add generic access order limits into block transfer concept.
* Factor helpers out of conv_traits.hpp
* Create a non-templated conv_traits struct
* Migrate to new instance-specific instance_to_conv_traits functions
* Clean up reflection concepts
* Clean up ConvTraits helpers
* Update testing for convolution traits
This is a lot of cleanup on tests to have verbose coverage of feature
extraction, explicit tests for each supported device kernel, and
simple, readable test code.
* Address reviewer comments and resolve merge conflict
This is mostly adjustments to enum values so that the docs align correctly with the current code.
Also updated the calendar scope of the project to extend through March 2026.
* Add placeholder test.
* Initial conv bwd weight factory.
* Conv builder test refactoring.
* Add missing pieces to bwd weight factory.
* Improve compile time erros message when no matching factory is found.
* Use amcro to ensure automatic macthing between concepts are their string representations.
* Improve compile time diagnostics.
* Small improvements.
* Improve missing member/wrong type compile-time errors.
* Improve compile time diagnostics.
* Concept bug fixes.
* Remove debug assert.
* Update algorithm signature diagnostics.
* Factory bug fixes.
* First functional version of bwd weight conv factory.
* Refactor handing of GEMM-K batch template parameter in conv bwd weight factory.
* Concept improvements.
* Improve concept diagnostics.
* Introduve a common size type for concepts.
* Update compiletime diagnostics to use the size type.
* Update conv specialization enum.
* Fix fwd conv builder tests.
* Fix smoke tests.
* Separate bwd weigth and bwd data tests into separate targets.
* Clean-up CK Tile builder tests.
* Add bwd weight XDL CShuffle V3 factory.
* Build conv bwd weigth v3 instances successfully.
* Add instance traits for DeviceGroupedConvBwdWeight_Xdl_CShuffleV3.
* Test fix.
* Add instance traits for bwd weight algorithms.
* Add unit tests for instance strings.
* Build new instance traits unit tests but exclude WMMA for now.
* Added factory for DeviceGroupedConvBwdWeightTwoStage_Xdl_CShuffle.
* Conv bwd weight DL factory.
* Final implementation for bwd weight DL factory.
* Add test for creating DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle instance.
* Add factory for DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle
* Treat ref algorithm the same way as real algorithms in the dispatcher.
* Refactor large tensor support and WMMA configuration.
* Add factory and tests for DeviceGroupedConvBwdWeight_Wmma_CShuffleV3.
* Update Readme.
* Fix WMMA bwd weight tests.
* Added factory and tests for DeviceGroupedConvBwdWeightTwoStage_Wmma_CShuffleV3.
* Factory and tests for DeviceGroupedConvBwdWeight_Wmma_CShuffle.
* Dispatching for DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffle.
* Add factory for DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3
* Fix DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3 factory and compute types for input and output tensor in bwd weigth convs.
* Fix fwd factories after refactoring.
* clang-format
* Move compile-time diagnostics to a separate branch.
* Fix ref algorithm dispatching.
* Fix smoke tests.
* clang-format
* Fix factory for regular WMMA conv bwd weight.
* Clarify builder Readme.
* Remove obsolete test file.
* Fix test after merge.
* clang-format
* Remove the C++26 extensions.
* Unify conv elementwise ops and layout definitions for fwd and bwd directions.
* Remove old layout and elementwise ops.
* Unify handling of conv tensor types between fwd and bwd directions.
* Unify block transfer for fwd and bwd directions. Rename ThreadSliceDim to ThreadClusterRank.
* Make BlockTransferDescriptor concept parametrized. Introduce a common TileTransferParameters concept for conv algorithms.
* clang-format
---------
Co-authored-by: Ville Pietilä <>
This adds some utilities to automatically generate UniqueInputs,
UniqueOutputs, alloc_inputs, alloc_outputs, and validate, based
on a Inputs::reflect() and Outputs::reflect().
* ck-builder: make toString to_string
We are using snake case for CK-Builder
* ck-builder: add debug.hpp with tensor descriptor printing function
This adds some initial functionality to debug.hpp, a header which will
be used to house some debug utilities.
* ck-builder: abstract nd-iteration
Abstracting this makes it easier to test, clearer, and allows us to
use it elsewhere (such as in debug.hpp soon)
* ck-builder: tensor printing
* ck-builder: rename INT32 to I32
This makes it more in line with the other data type definitions.
Our concept-base conversions are fragile and too complex. We want to refactor to straightforward functions
for each intance trace class template. This change adds unit test coverage to make that refactoring safer.
* ck-builder: explicitly delete forward declarations
Before, these functions were seen as a forward declaration for an existing function.
If no actual implementation overload could be found, these would be selected and
a linker error or warning would be generated. By marking these functions as explicitly
deleted, they incorrect invocations are generated as compile error instead.
* ck-builder: ckt::run plumbing for reference conv
This implements the ckt::run plumbing for the reference convolution
implementation and sets up the first complete end-to-end test.
* ck-builder: make validation system check for all-zeros
When both the actual and reference output are both all zero bits,
there is probably something wrong in the test framework.
* ck-builder: proper implementation+tests for TensorDescriptor::is_packed
* ck-builder: fix typos
This pull request builds on #3267 by proving the "validation" infrastructure, the means to compare a set of `Outputs`.
The design of the validation infrastructure is relatively straight forward:
- Each SIGNATURE should come with a `validate()` implementation, which should be implemented in a similar way that the other functions/types from `testing.hpp` are implemented.
- `validate()` returns a `ValidationReport`, which is a structure that keeps all relevant information about comparing the tensors from two `Outputs`. Note that crucially, `validate()` should not do any reporting by itself. Rather, glue logic should be implemented by the user to turn `ValidationReport` into a relevant error message.
- You can see this clue code for CK-Builder itself in `testing_utils.hpp`, its `MatchesReference()`. This functionality is relatively barebones right now, it will be expanded upon in a different PR to keep the scope of this one down.
The comparison is done on the GPU (using an atomic for now), to keep tests relatively quick. Some notable items from this PR:
- To help compare the tensors and with writing tests, I've written a generic function `tensor_foreach` which invokes a callback on every element of a tensor.
- For that it was useful that the `TensorDescriptor` has a rank which is known at compile-time, so I've changed the implementation of `TensorDescriptor` for that. I felt like it was a better approach than keeping it dynamic, for multiple reasons:
- This is C++ and we should use static typing where possible and useful. This way, we don't have to implement runtime assertions about the tensor rank.
- We know already know the rank of tensors statically, as it can be derived from the SIGNATURE.
- It simpifies the implementation of `tensor_foreach` and other comparison code.
- There are a lot of new tests for validating the validation implementation, validating validation validation tests (Only 3 recursive levels though...). For a few of those functions, I felt like it would be useful to expose them to the user.
- Doc comments everywhere.
* initial poc
* factor out common parts in operator()
* cv4
* rest of the universal gemm pipelines
* fix test
* remove boilerplate from tile engine
* fix example
* fix example
* format
* fix tests build for gemm
* remove base pipeline codegen from gemm instance builder
* unify v3 logic with the rest of universal gemm pipelines
* fix build for multi abd test
* fix test gemm multi d
* fix build for weight preshuffle
* fix grouped gemm test
* fix grouped gemm multi d test
* fix grouped gemm preshuffle
* fix grouped gemm example except for quant
* fix gemm preshuffle
* fix splitk 2 stage example
* fix batched gemm example
* fix multid example
* fix multiabd example
* fix batched gemm test
* fixup
* fix examples build
* fix grouped gemm test build
* fix smoke builder
* hacky poc
* fix tile engine
* kill the lambda
* maybe fix test build
* more fixes
* clang-format
* save temp
* clang-format
* mostly fix examples
* clang-format
* remove dead code
* more cleanup
* fix fmha bwd build (default epilogue set/add appears to be broken)
* fix default epilogue tests but not correctness
* clang-format
* fix bquant
* clang-format
* cleanup dead code
* rearrange make windows for readability
* restore changes to IsSupportedArgument
* fix smoke-builder
* clang-format
* fixup rename class
* build fixes
* clang-format
* fix builder
* fixup
* remove set from builder tests
* fix test
* clang-format
* re-refactor the kernels
* clang-format
* fix header license
* remove memory operation from conv bwd test
* clang-format
* clang-format example,include
* clang-format test
* build fixes
* clang-format
* solve compilation error
* fix the CI
* solve compilation error
* clang format
* solve merge conflict
* solve merge conflict
* solve the gfx11 error
* solve test error
* moar build fixes
* remove AtomicAddRequiresKBatchGreaterThanOne test since the property is removed from the kernel scope
---------
Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
Added instance traits for the following bwd weight conv algorithms
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3
DeviceGroupedConvBwdWeight_Wmma_CShuffleV3
DeviceGroupedConvBwdWeight_Wmma_CShuffle
DeviceGroupedConvBwdWeight_TwoStage_Xdl_CShuffle
DeviceGroupedConvBwdWeight_TwoStage_Wmma_CShuffleV3
DeviceGroupedConvBwdWeight_DL
DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle
DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3
Added also unit tests for instance traits of those bwd weigth algorithms that are currently exposed by the narrow CK build for MIOpen.
---------
Co-authored-by: Ville Pietilä <>
* [CK_BUILDER] Integrate GPU reference as ConvAlgorithm
Add GPU reference as a ConvAlgorithm specialization, enabling:
- Unified Builder API for reference and optimized kernels
- Future ckProfiler integration for validation
- First step toward numerical validation in Builder tests
Changes:
- Add ConvAlgorithmSpecialization::REFERENCE enum
- Add ConvAlgorithm_Reference struct
- Add IsReferenceAlgorithm concept
- Create 3 reference factories (Forward, BwdData, BwdWeight)
- Wire into conv_dispatcher
- Add proof-of-concept test (passing)
Test result: Can instantiate reference through Builder API
* Add GPU reference execution tests
- Reference kernel executes through Builder (459ms)
- Both reference and optimized can instantiate
- Tests passing
Next: Implement utilities for comparison
* Optimized Builder kernel execution works
- MakeArgument pattern implemented
- Builder-generated kernel executes successfully
- Tests passing (451ms execution)
Next: Add comparison
* VALIDATION COMPLETE: Builder == Reference
Builder-generated kernel output matches GPU reference!
Test: Validate_Optimized_vs_Reference_Forward_2D_FP16
Result: PASS ✓
This proves CK Builder generates correct code!
* Update to new Builder API
All tests passing
* Rename test file for clarity
test_builder_kernel_execution -> test_builder_kernel_validation
* Add all 3 directions support
- Forward, Backward Data, Backward Weight
- All reference factories working
- Dispatcher wired for all directions
- 9 tests passing
Tests:
- test_reference_execution: 3 tests (all directions)
- test_optimized_execution: 3 tests (all directions)
- test_builder_kernel_validation: 3 tests (fwd validated, bwd placeholders)
* Add backward direction support
- Backward data and weight dispatcher wiring
- Fix factories for new API
- All 3 directions tested
- 9 tests passing
* Refactor: Change IsReferenceAlgorithm from concept to consteval function
Address review feedback: Use consteval function in dispatcher instead of
concept, matching the pattern for other algorithms (Tile, XDL, WMMA, DL).
- Remove IsReferenceAlgorithm concept from conv_algorithm_concepts.hpp
- Add IsReferenceAlgorithm() consteval function to conv_dispatcher.hpp
- Update dispatcher to use function call: IsReferenceAlgorithm<T>()
- Remove redundant algorithm checks from reference factory requires clauses
All tests passing (9/9).
* Move Tile algorithm check outside direction block to support all directions
* Implement MakeInvokerPointer interface and add random input validation
- Implement full Argument/Invoker structs for old CK interface (not just nullptr)
- Refactor with reference_common.hpp to reduce code duplication
- Add random input validation tests: Builder vs direct GPU reference (all directions)
- Fix layout: GNHWC -> NHWGC to match reference kernel expectations
- All 12 tests pass with IDENTICAL results on random input
* Move ConvAlgorithm_Reference to test/impl/conv_algorithm_types.hpp
Keep types.hpp for data types only (enums), move algorithm descriptors
to conv_algorithm_types.hpp as suggested by review.
* Add static_assert to ensure reference factories only accept PassThrough operations
Reference implementation doesn't support fused elementwise operations.
Add compile-time validation to fail early with clear error message if
non-PassThrough operations are specified on input, weight, or output.
* Add InstanceTraits support for reference kernels
- Store SIGNATURE/ALGORITHM/VERSION in Instance for reflection
- Create shared ReferenceCommonTraits base for common properties
- Add 3 direction-specific InstanceTraits specializations in one file
- Include data type and layouts in instance_string output
* Remove optimized kernel validation tests from reference-only branch
* Use existing layout helper and organize reference tests
Use LayoutToCK from conv_tensor_layout.hpp and move reference InstanceTraits
test to validation folder.
* Merge develop branch
Fix DataType switch for new mixed precision types.
* Fix comment spacing for CI
* Convert IsReferenceAlgorithm from function to concept
* Add reference tests to CI smoke tests
* Consolidate 3 reference factories into single unified factory
---------
Co-authored-by: Ville Pietilä <188998872+vpietila-amd@users.noreply.github.com>
* reinstate conv_signature_utils.hpp
* added tests for elementwise operation getters
* add tests for getDataType functions
* added test for no data type specified
---------
Co-authored-by: Kevin Abraham <kevin.abraham@streamhpc.com>
Refactors the way the number of XDL (matrix multiply-accumulate) instructions per wave is calculated and used in the grouped convolution forward implementations, especially to better support WMMA (Wave Matrix Multiply-Accumulate) instructions and 16x16 tiles.
The changes use MXdlPerWave instead of NXdlPerWave to increase number of waves per M dim.
We have some metaprogramming helper functions that only exist to throw an error at build time. These should have the [[noreturn]] attribute, which is now required in our CI builds.
