GitLab

* reopen masking att instance due to CI is upgraded

* re-enable instances previously failed on 9110

* enable ksize-kpadding pair validity test

* add non-masked attention+permute test; expose masking boolean to attention kernel handles

* disable bench

* fix test

* move files

* bulk rename batched_gemm_masking_scale_softmax_gemm_permute to batched_gemm_softmax_gemm_permute

* format

* amend rename

* disable bench in test

* add mask/no-mask test for non-permute attention kernels

* disable broken kernel instance

* example working

add non-permuted problem statement

evaluating whether overhead comes from permutation or the extra kernel arg

* interface for bias addition without implementing it

* test and profiler running

* tidy

* mask type determined by enum class

* unify example code

* move masking specialization to its own header

* align formats

* extract helper functions

* experiment merging dims for attn w/ permute; shows perf parity with attn wo/ permute

* add tensor specialization to template args

since tensor spec packed shows perf parity when permutation isn't needed

remove redundant template args

comment on 'packed' tensor specialization

* grouped attention with input/output permute example

* format

* clean up

* refactor acc0 tile visitor

* fused attention client example

* format
Co-authored-by: shaojiewang <wsjmessi@163.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* reopen masking att instance due to CI is upgraded

* re-enable instances previously failed on 9110

* enable ksize-kpadding pair validity test

* add non-masked attention+permute test; expose masking boolean to attention kernel handles

* disable bench

* fix test

* move files

* bulk rename batched_gemm_masking_scale_softmax_gemm_permute to batched_gemm_softmax_gemm_permute

* format

* amend rename

* disable bench in test

* add mask/no-mask test for non-permute attention kernels

* disable broken kernel instance

* example working

add non-permuted problem statement

evaluating whether overhead comes from permutation or the extra kernel arg

* interface for bias addition without implementing it

* test and profiler running

* tidy

* mask type determined by enum class

* unify example code

* move masking specialization to its own header

* align formats

* extract helper functions

* experiment merging dims for attn w/ permute; shows perf parity with attn wo/ permute

* add tensor specialization to template args

since tensor spec packed shows perf parity when permutation isn't needed

remove redundant template args

comment on 'packed' tensor specialization

* grouped attention with input/output permute example

* format

* clean up

* refactor acc0 tile visitor
Co-authored-by: shaojiewang <wsjmessi@163.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Fix for lwpck-425, update BlockTransferSrcVectorDim

* Revert "Fix for lwpck-425, update BlockTransferSrcVectorDim"

This reverts commit fd24e280e28ff238b452cfdde58a988affd46461.

* Add Batched Gemm int8 test, expect it to fail

* Format

* Re-add the fix

* prototype

4 layouts

fix default stride

all problem sizes

tidy

move file

update build script

restore old file

fix build

* refactor standalone test to use gemm test harness

* simplify gemm test

* update build script

* remove redundant

* early return when cmd arg doesn't match

* tidy

* report failure when result not validated

* tidy

* Apply suggestions from code review
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>

* Simplify the macros for declaring and defining the add_device_reduce_instance_xxxx() instances

* Change the types of lengths and strides from std::vector to std::array for the reduction device interfaces

* Remove DeviceSoftmaxImpl's depending on DeviceReduceMultiblock

* Split the cpp and hpp files for reduction instances to enable more parallel compiling

* Remove the using of macros for declaring reduction instances and instance references

* Update to add_device_reduce_instance_xxxx templated functions

* Use ReduceOperation+InElementwiseOp+AccElementwiseOp to repace the ReduceOpId in defining add_reduce_instance_xxxx() templates

* Change return format

This reverts commit efbcc6ed.

* add fused addition lyernorm

* add fused addition lyernorm

* changed CMakelist

* removed annotates

* modified descriptor of C

* fixed bug in gridwise add layernorm

* format the files

* modified name from add&layernorm into elementwise&layernorm

* created fused elementwise layernorm branch

* change input into tuple type

* add sweep once to reduce load & read of C from global memory

* modified Argument api

* modified way to malloc c in global memory

* changed gamma and beta to m_k_desc

* fixed bug when sweep once and move CDataType when define device level struct

* add src dim for gamma and beta

* implement optimization for coalesced

* delete a annotation line

* fixed some bug to meet the requirements of ck

* add bandwidth computing in example, and fixed the time unit

* move device_elementwise_layernorm_impl.hpp into device/impl

* fixed bug in device_elementwise_layernorm_impl.hpp

* changed name from layernorm into normalization

* clang-format the changed files

* changed the names

* moved immidiate results into lds, it become faster in non-sweeponce cases

* changed naming of C into X to make the defination more clear

* changed naming in example

* add tests for elementwise normalization

* move example_elementwise_layernorm_blockwise into folder 44_elementwise_normalization

* move test_elementwise_layernorm_fp16 into new folder

* move elementwise_normalization_instances into a new folder

* add more tests in test_elementwise_layernorm_fp16.cpp

* added some corner cases in test

* fixed method to compute lds size for matrix X

* changed name of 44_elementwise_normalization into 45_elementwise_normalization

* modified some comments

* modified some other confused comments

* reduce redundant tests in test_elementwise_layernorm_fp16.cpp

* adding tensor_permutation example folder

* fixed formatting

* adding tensor_permutation example folder

* fixed formatting

* changed deviceelementwise parameters for outscalar

* removed .swo file

* updated folder/file name

* changed function call in verification for better consistency with hostelementwist parameters

* formatted again

* fixed shape in verification function call

* changed verification function call, added definition for nhwc

* added elementwise permute example

* updated CMakeLists file in folder

* Delete CmakeLists.txt

* Delete tensor_permute.cpp

* first version of 2d gridwise_elementwise kernel

* temporary fix for stride problem

* formatting

* format

* changed directory name

* Delete gridwise_elementwise_2d.hpp

* Delete CMakeLists.txt

* Delete extra file

* delete extra file

* got rid of extraneous code

* added 2d device elementwise file

* deleted accidently added file

* update

* stride values generalized with equations

* updated stride for output matrix

* Update CMakeLists.txt

* removed extraneous commented code

* removed shape_nchw vector, replaced with GetLength for each dimension

* changed vector load in kernel call

* removed extra space in CMake

* Move kernel implementation files under impl directory.

* Update examples paths.

* Update device kernel impl include paths.

* Update tensor operation instances include paths.

* Update profiler and tests include paths.

* Clang-format

* Update include paths for batched gemm reduce

* Refactor UnitTest ConvNDBwdWeight.

* Refactor fwd and bwd data convND UT.

* Fix used test macro.

* Fix include path.

* Fix include paths.

* Fix include paths in profiler and tests.

* Fix include paths.
Co-authored-by: Adam Osewski <aosewski@amd.com>

* Fix bug of profiler for layernorm

* 1. Rename layernorm into normalization
2. Decouple softmax from normalization

* clang-format

Co-authored-by: Adam Osewski <aosewski@amd.com>

* start split k

* add base device class

* add example after merge develop

* add gridwise gemm

* add b matrix split k

* split=1

* change name for kb

* not bias result right

* bias only add once

* fix register spill

* regular code

* add fp32 example

* fix for 64bit index

* fix CheckValidity of gridwise

* run branch once a day, with release and staging compilers

* add GetDockerImage in Clang stage

* apply the new triggers to the develop branch

* use another instance to check the efficiency

* optimize group layer norm

* 1. coalesce load/store data for gridwise layer norm welford. 2. move a sqrt and divison into a outer static loop

* add more instances to layernorm

* add 2 more test cases

* remove ignore in generating tuple of vector
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* update cmake script

* update readme

* Update README.md

* add citation

* add images

* Update README.md

* update

* Update README.md

* Update CONTRIBUTORS.md

* Update README.md

* Update CITATION.cff

* Update README.md

* Update CITATION.cff

* update doc

* Update CONTRIBUTORS.md

* Update LICENSE

* update

* update cmake script

* update readme

* Update README.md

* add citation

* add images

* Update README.md

* update

* Update README.md

* Update CONTRIBUTORS.md

* Update README.md

* Update CITATION.cff

* Update README.md

* Update CITATION.cff

* update doc

* Update CONTRIBUTORS.md

* Update LICENSE

* update cmake script

* update readme

* Update README.md

* add citation

* add images

* Update README.md

* update

* Update README.md

* Update CONTRIBUTORS.md

* Update README.md

* Update CITATION.cff

* Update README.md

* Update CITATION.cff

* enable ccache and decouple it from MIOpen ccache use

* fix the ccache check script

* use another method to get server name

* fix syntax

* add quotes around the server name variable

* use check_host as function

* change syntax

* fix syntax

* test if server name is parsed correctly

* try different syntax

* check the env var value

* test new check node function

* add ROCMVERSION parameter and fix script syntax

* fix script syntax

* add missing instances of rocm version

* install ccache in the docker image

* do not check GPU in clang format stage, clean up old code

* update defaults and clean up

* add an option to select specific compiler commit

* change the logic of forcing building a docker

* add check for compiler commit in dockerfile

* compiler check syntax fix

* change compiler selection logic

* fix the new compiler build issue

* set new compiler as default, update dev-requirements

* fix jenkins syntax

* fix docker syntax

* get rid of hipcc.pl editing in jenkinsfile

* fix the hipcc.pl in both places

* try to fix the 10738 compiler linking bug

* fix syntax

* use dockerhub to store images

* use newer amd-stg-open commit as default

* fix device instance library to add all instances

* remove cppcheck from requirements.txt
Co-authored-by: Jun Liu <Liu.Jun@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* fix

* fix

* add instance

* replace obsolete offload-arch flags with GPU_TARGETS

* fix a build error for client app

* replace commma with semicolon in GPU_TARGETS

* build CK only once, use deb package in all subsequent stages

* update jenkins file

* change prefix for build_CK stage

* update writing deb metadata to control file

* update ubuntu source for docker, script syntax for deb package metadata

* try different way to create deb metadata

* clean up DEBIAN before creating one

* fix the CI folder names, fix splitK qa

* use correct docker in all stages, separate tests for splitK verification and performance

* clean old comments, change dir before packaging

* use different package syntax

* change packaging syntax

* package with cmake

* remove unnecessary build prefix

* get rid of unnecessary paths

* change paths during unpacking

* change script syntax while unpacking

* get rid of unneccesary steps

* get rid of comments in the scripts

* use double quotes for scripts

* add ccache during build, try dpkg -x

* pull and install each package separately

* use full package names

* try to use stashing for packages

* change stash/unstash syntax

* move unstash out of shell, run tests on any gpu node

* unpack each package separately

* try re-using existing workspace

* merge the build and test stages, only stash ckProfiler

* merge the build and test stages, only stash zipped ckProfiler

* fix syntax

* add GPU check before build and test, rename docker to usual name

* fix build

* fix build

* add lower triangle bmm

* init code for tile skipping

* functionality right with lower triangle mask

* add decoder lower triangular mask calculation

* use 7*13 group

* fix n2 compute error

* attention with lower triangle mask with tile skipping

* add template to distinguish masking kernel

* rename template and remove default template value

* remove lower triangle gemm reference struct

* add some comments on example

* add 10 instance for masking bmm + scale + softmax + bmm + permute kernels

* add test

* add test file

* add gtest for bmm masking scale softmax bmm permute

* clang-format

* fix compile error

* check lef bottom corner for tile skipping

* fix error: check left bottom corner for tile skipping

* add k padding

* add test and instance for MNK padding

* passing a mask struct

* fix instances

* delete used comments

* format
Co-authored-by: danyao12 <yaodan@dc-smc-13.amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Add groupnorm example by layernorm
1.  Reference is not ready
2. shape of gamma and beta need to be fix

* Let shape of gamma and beta can be same as x

* Modify test, instance and client example

* [What] Fix bug of layernorm for greater than 2 dimension.
[Why] We need to get upper length from merge transform instead of embed transform.

* Add reference for groupnorm

* Fuse sigmoid after groupnorm

* [What] Rename original layernorm into layernorm2d
[Why] Prepare to add groupnorm using layernorm5d

* clang-format

* Add groupnorm test

* Refine error message

* Add groupnorm ckProfiler

* Test groupnorm kernel from device_instance

* update example

* upadte profiler

* Fix test naming

* Fix argc number

* Move descriptor and sweeponce to argument for quick debugging
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Add example folder for 'DeviceElementwise'

* Re-structure example files

* Move common parts into common.hpp

* Use more strict input

* Add more helper methods in 'DeviceElementwise'

* Use more specific method to write example

* Allow specify problem through command line argument

* Allow specify problem 'axes' through command line argument

* Add check to template type argument

* Add transpose_shape() to generalize shape permute

* Generalize transpose utility functions

* Use better name for tensor indices

* Add checks in helper functions

* Remove debug messages

* Refine error message for check_err()

* Generalize variable naming in example code

* Add device op 'DevicePermute'

This device op is clone of 'DeviceElementwise'

* Use 'DevicePermute' device op in example

* Remove 'elementwise' from identifiers

* Remove 'elementwise' from file paths

* Remove base class of 'DevicePermute'

* Let 'DevicePermute' inherit from 'BaseOperator'

* Add simple type traits to validate device op type

* Add static_assert() to check type constraints

* Create 'DevicePermuteBase' to generate methods

* Use indirect base type to generate methods

* Remove 'is_device_op<>' type traits

* Only accept single-input-single-output for 'DervicePermute'

* Simplify 'DevicePermute' interface

* Re-format 'DeviceElementwise'

* Use CRTP to generate overridden virtual method

* Remove unnecessary include directives

* Distinguish input & output shape in 'DevicePermute'

* Passing 'axes' to 'DevicePermute'

* Use more reasonable return value for Invoker::Run()

* Add 'GridwisePermute' kernel

This kernel is a clone of 'GridwiseElementwise_1D'

* Remove no-longer used type argument

* Check if input/output shape meet the requirement

* Remove no-longer used method

* Remove never-entered-if-clause

* Change problem description for 'DevicePermute'

* Transform descriptor into 3 dimensions

* Add debug code the verify result

* Add comment to indicate template argument location

* Add N/H/WPerBlock template parameter to 'DevicePermute'

* Rename 'GridwisePermute' to 'GridwiseCopy'

* Check tensor descriptor dimensions in 'GridwiseElementwise_1D'

* Add missing include directive

* Add 'BlockSize' parameter to 'DevicePermute'

* Remove no-longer used method

* Add 'BlockToTileMap' for 'GridwiseCopy'

* Use the normal Block2TileMap convention

* Rename 'BlockToTileMap' as 'Block2TileMap'

* Fix most of compilation errors

* Let 'Block2TileMap' map block to 2d coordinate

* Allow data transfer in 'GridwiseCopy'

* Fix wrong output descriptor for 2nd blockwise copy

* Rename 'GridwiseCopy' as 'GridwisePermute'

* Remove '1d' in identifiers

* Remove commented-out codes

* Remove 'MPerThread' template parameter

* Seperate template parameters

* Unify variable namming convention

* Use more verbose way to create expressions

* Add template parameter 'InBlockLdsExtraW'

* Release the constraint on In/OutGridDesc

* Use date type directly as template argument

* Re-arrange template arguments for blockwise copy

* Remove no-longer used template parameters

* Embed layout in the variable names

* Add GridwisePermute::CheckValidity()

* Extract local types as template parameters

* Rename local type alias

* Add more template parameters (vector width related)

* Calculate new SrcVectorDim/DstVectorDim after merge descriptor dimensions

* Fill tensor values start from 1

* Re-formate example code

* Avoid too-large block id

* Add comment

* Make sure 'SrcVectorDim' is not same as 'DstVectorDim'

* Add check for the 'VectorDim' & 'ScalarPerVector' template params

* Let 'DstVectorDim' equals 'SrcVectorDim' after transpose out grid desc

* Remove no-longer used template parameter 'NPerBlock'

* Fix wrong descriptor creation logics

* Specify problem in each examples

* Use better example name

* Add new example 'example_permute_NxHxW_fp32'

* Add example for demonstrating bundle multiple elems in tensor

* Add support to permute multiple elements together

* Change the default problem size

* Add span<> class template

* Use span<> to generalize check_err() interface

* Fix ambiguous ctor call

* Avoid create necessary objects

* Use helper functions to simplify example code

* Add example for 4xfp16 permute

* Disable failed-to-compile example

* Add check for the NUM_ELEMS_IN_BUNDLE

* Remove redundant parameter in helper lambda function

* Add check for the input tensor type's byte-size

* Check scalar-per-vector with padded length

* Use more verbose name to avoid name collision

* Use fixed 'VectorDim' & 'ScalarPerVector' for LDS

* Embed shape info in name of descriptor constructor

* Rename example folder '36_permute' into '37_permute'

* Avoid using too-large LDS in kernel code

* Remove redundant example

* Usw switch() to group similar codes

* Add const to the span<> type arguement

* Simply initialize tensor with floating point values

* Use fp16 as data type in all examples

* Enlarge tensor size in example

* Enalrge N-dim in example

* Add check for the bundled type in example

* Use more stricter error threshold

* Remove global load/store loop in kernel code

* Measure execution time by default

* Use faster device op config for example 'NxHxW_fp16'

* Use faster device op config for example '1xHxW_fp16'

* Use faster device op config for example 'HxWx4_fp16'

* Remove cmd arg parsing logics

* Rename functions

* Extract bundle permutation logic out

* Simplify permute bundle example

* Add Tensor<>::GetElementSpaceSizeInBytes()

* Add Tensor<>::data()

* Use new methods to simplify code

* Use type alias to replace duplicated code

* Use existing method to shorten code

* Allow FillUniformDistribution accept range arugment

* Intialize random values in range

* Add Tensor<>::size()

* Use more meaningful names in permute bundle example

* Use more meaningful names in permute element examples

* Use rangified copy() to copy elements

* Use function return value directly to eliminate variables

* Add to_array() conversion tool to eliminate more variables

* Add Tensor<>::AsSpan<>() to create view of tensor values

* Use AsSpan() to shorten check_err() calls

* Remove no-longer-used 'using' directives

* Move 'using' directive to proper code position

* Remove redudant variables

* Remove useless static_assert()

* Add check for range types

* Declare variable right before first use

* Move long return type as tailing return type

* Add BaseInvokerCRTP<> class template to generate method

* Create new base type for 'DervicePermute' implementations

* Move 'NumDim' template param to the first

* Rename 'DevicePermute' to 'DevicePermuteImpl'

* Add 'noexcept' specifier to CRTP generated method

* Move 'Block2TileMap' definition into 'GridwisePermute'

* Use type alias to reduce code

* Unify naming style in 'DevicePermute'

* Add comments in 'GridwisePermute'

* Rename permute example folder

* Use std::cerr to report error

* Use larger shape in examples

* Rename '38_permute' to '39_permute'

* Make sure we use unsigned type for shape & indices

* Remove opt-ed out assertion

* Remove template BaseInvokerCRTP<>

* sanity check

* add attribution

* add irrgular k tile size for batched attention

* format

* grouped attn without batch validates; now move toward grouped batched attn

* grouped batched attention

* working

* remove debug logging

clean up

clean up

* reintroduce g_ prefix back to host tensor variables

* format

* rename file

* restore old file

* rename

* consolidate padded/non-padded attention example

* harmonize padding specialization in attn examples

* init commit of convnd bwd data

* begin compiling example

* have a first version that produce a right result

* refine device level launch kernel code

* add more instances in example and get right results

* clang-format

* format example file

* add more instances

* fix instances

* adding conv_bwd_data multile_d

* adding conv_bwd_data multile_d

* adding conv_bwd multiple d

* adding conv_bwd multiple d

* adding conv_bwd multiple d

* refactor

* refactor

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* refactor

* update conv fwd's bias impl

* refactor

* reorg file

* clean up cmake

* clean

* clean

* clean
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* refactor

* start

* add device gemm file

* add BatchStrideD0

* add stridd0

* add gridwise file

* add d0 parameters to gridwise gemm

* add c layout transformer

* add d0 threadwise copy

* init kernel

* init kernel

* regular code

* nm desc put to out

* kernel parameter can not use reference

* host add bias+gelu

* run right for bias+gelu

* change AddFastGelu into another file

* interface add d1 bias parameters

* add d1 parameter to argument

* add d1 parameter to gridwise

* first all code,not verify

* gelu change to relu and GetElementSpaceSize bug

* add instance

* start add to ckprofiler

* ckprofiler finish code

* change input parameter for ckProfiler

* fix host bias+gelu bug

* show help for ckProfiler

* fix bug for lunch kernel ignore parametes

* add pad and fix about bug

* mutiple d0

* add dynamic d0_element_op

* change profiler and  instance to mutiple d0

* example have 2 d0

* remove some comments not using

* change 2 d0 have self  parameters

* change d element_op name

* change class name(multiple_d)

* fix bug

* fix bug that don't find file

* update profiler

* refactor

* update profiler

* clean

* revert example change

* add gon layout

* optimize parameter for gno

* add gon to gemm+gemm

* change helping input parameters

* change to GemmPadder_v2

* using ForEach

* fix gb_per_sec
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
Co-authored-by: ltqin <letaoqin@amd.com>

* upgrade the OS and ROCM versions in CK docker

* add cxx flags to link code with rocm5.2 and ck-9110 compiler

* rename the docker image

* run ONNX gemms using init=1

* add gridwise/device sparse embedding

* update code

* update code

* remove useless makefile

* code fix

* workable

* work properly

* emb add

* add more instance

* format

* remove useless code

* fix format

* fix clang-tidy

* clean

* fix a compile error
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Chao Liu <lc.roy86@gmail.com>