GitLab

* Add threadwise and blockwise welford

* Rename gridwise op, prepare to add welford version

* implement welford and integrate welford into layernorm

* Take care of tail loop

* Fix buf when ThreadSliceK > 1

* Fix bug of merging of two empty set

* Rename clip to clamp

* 1. Fix type of count
2. Remove useless static_assert

* Do not inherit Reduction::Argument

* [What] replace __syncthreads() with block_sync_lds()
[Why] __syncthreads might wait both lgkmcnt(0) and vmcnt(0)

* Add y stride

* Rename.
DeviceLayernorm -> DeviceLayernormImpl
DeviceNormalization2 -> DeviceLayernorm

* Move literal ""_uz & ""_zu into namespace 'literals'

* Move namespace 'literals' as 'ck::literals'
Co-authored-by: Po-Yen, Chen <PoYen.Chen@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* initial stub for gemm_gemm_xdl_cshuffle

* set up example code

* compiles

* prevent integer overflow

* harmonize interface between ref_gemm and ref_batched_gemm

* batched_gemm_gemm

* fix example

* host tensor gen: diagonal pattern in lowest two-dimensions only

* make c descriptors containing only integral constants

* clean up

* add BlockwiseGemmXdlops_v2 while exploring an unified approach

* implement proper interface

* tidy up example

* fix compilation warnings

* coarsely controlled 2nd gemm padding

* remove rocm-cmake's hard requirement for certain revision

* clang-format

* resolve merge conflict

* fix compilation error on gfx10

* adds acc0 elementwise op to interface

* add gemm_gemm instances and tests

* avoid LDS data hazard

* fix build
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* initial stub for gemm_gemm_xdl_cshuffle

* set up example code

* compiles

* prevent integer overflow

* harmonize interface between ref_gemm and ref_batched_gemm

* batched_gemm_gemm

* fix example

* host tensor gen: diagonal pattern in lowest two-dimensions only

* make c descriptors containing only integral constants

* clean up

* add BlockwiseGemmXdlops_v2 while exploring an unified approach

* implement proper interface

* tidy up example

* fix compilation warnings

* coarsely controlled 2nd gemm padding

* remove rocm-cmake's hard requirement for certain revision

* clang-format

* resolve merge conflict

* fix compilation error on gfx10

* adds acc0 elementwise op to interface

* attention host validation

* add blockwsie softmax v1

* iteratively update softmax+gemm

* transpose both gemm0 and gemm1 xdl output so as to avoid broadcasting softmax max/sum

* add init method for easier debugging

* do away with manual thread cluster calculation

* generalize blockwise softmax interface

* row-wise softmax sum & max

* format

* rename to DeviceBatchedGemmSoftmaxGemm

* add gemm_softmax_gemm instances and tests

* comment
Co-authored-by: ltqin <letao.qin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Move literal ""_uz & ""_zu into namespace 'literals'

* Move namespace 'literals' as 'ck::literals'

* Add always_false<> util to delay symbol resolution

* Use always_false<> to prevent trying instantiate unwanted method

* Add new specializations of AddAddFastGelu::operator() method

* Add GEMM + AddAddFastGelu examples for data types: int8, bf16, fp32

* Use floating point literal to simplify code

* Remove unnecessary capture in lambda expressions

* Extract fast GeLU calculation as standalone method

* Mark methods as 'constexpr'

* Add constraint for HostTensorDescriptor templated ctors

* Simplify HostTensorDescriptor ctor calls

* Add C++23 std::size_t literal suffix

* Use _uz suffix to shorten example code

* Remove unnecessary conversion to std::array<>

* Re-order include directives

* Remove C-style casting by literal suffix

* Remove unnecessary statements in main()

* Remove unused type parameter of always_false<>

* Remove unused include directive

* Exit main() by returning meaningful value

* Use 'if constexpr' to switch example flow

* Use std::is_same_v<> to shorten example code

* Add 'inline' specifier to literal functions

* Unify output methods in example

* Move common codes into .inc file

* Add type check in type_convert<>()

* Add type_convert<float>() before computation

* Merge AddAddFastGelu method specializations

* Remove always_false<>

* Add constraint to AddAddFastGelu::operator() parameter types

* Refine parameter

* Add base class for layernorm

* Add layernorm instance

* Add layernorm to ckProfiler

* Remove redundant

* Add verification

* Fix compile error due to merge

* add conv oddC

* update example

* update example

* fix bug in example

* fix bug in group conv example

* Add int8 specialization for elementwise Add and Subtract.

* CGEMM examples bf16, fp32, int8

* Add convert reference output to CDataType.

* Skip BF16 data type during testing.

* Lower K value to get rid of accumulation error.

* Fix merge artifact.

* Fix changed function name: GetElementSpaceSize()

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

* convnd_fwd fp16 example

* update example

* update example

* update instance

* updating refernce conv

* update reference conv

* update conv fwd profiler

* update conv 1d and 3d instance

* update include path

* clean

* update profiler for conv bwd data and weight

* update conv bwd weight

* clean

* update conv example

* update profiler for conv bwd weight

* update ckprofiler for conv bwd data

* fix reference conv bwd data bug; update conv bwd data test

* update examples

* fix initialization issue

* update test for conv fwd

* clean

* clean

* remove test case too sensitive to error threshhold

* fix test

* clean

* fix build

* adding conv multiple d

* adding conv multiple D

* add matrix padder

* add gemm padding to convnd

* adding group conv

* update gemm multi-d

* refactor

* refactor

* refactor

* clean

* clean

* refactor

* refactor

* reorg

* add ds

* add bias

* clean

* add G

* adding group

* adding group

* adding group

* update Tensor

* clean

* update example

* update DeviceGemmMultipleD_Xdl_CShuffle

* update conv bwd-data and bwd-weight

* upate contraction example

* update gemm and batch gemm with e permute

* fix example build

* instance for grouped conv1d

* update example

* adding group conv instance

* update gemm bilinear instance

* update gemm+add+add+fastgelu instance

* update profiler

* update profiler

* update test

* update test and client example

* clean

* add grouped conv into profiler

* update profiler

* clean

* add test grouped conv, update all conv test to gtest

* update test

* add verify flag and update scripts

* replace old check_error function with the new check_err

* fix syntax

* remove blank spaces

* remove empty line

* add check_err for tensors

* fix syntax

* replace tensors with vectors in check_err calls

* fix syntax

* remove blank spaces

* fix syntax

* add new line at end of file

* disable conv2d_bwd_weight test, add gpu check

* set check_gpu using export

* check GPU using runShell

* add definition of runShell

* fix script syntax

* reduce the number of threads, add full qa option

* run processing scripts in bash

* fix the branch and host names in performance scripts, add chronos

* replace parameterizedCron with cron

* archive the perf log files

* try to fix git call

* pass branch and host names as arguments into scripts

* fix script arguments

* fix script arguments

* process results on master

* fix pipeline

* add definition of gpu_arch

* run processing scripts in docker

* fix the brackets

* add agent master for the processing stage

* get rid of show_node_info call on master

* try using mici label instead of master, disable MI100 tests for now

* fix syntax

* simplify container for results processing

* remove node(master) from the process_results stage

* put all stages in original order

* change the agent label from master to mici for gfx908

* replace gridwise_v2r3 with multiD

* adjust parameters

* add instances

* fixed test_grouped_gemm

* fix standalone softmax race condition around blockwise reduction

* fixed ci

* fixed comment: remove redundant workspace

* use instanceFactory

* add test layout

* add empty Ds

* add bias example

* use array

* sperate examples
Co-authored-by: Anthony Chang <ac.chang@outlook.com>

* Implement layernorm kernel and deviceOp

* verify gpu kernel with host code

* 1. Separate gamma aand beta from affine
2. Check if argument is valid

* clean

* Sync the naming

* Support sweep once mode if we can put k dimension data inside one block

* [What] Get length from upper length.
[Why] if we get length directly, we may get length after padding.

* We only use one block in K dimension.
Hence, we can simplify the indexing of global R/W.

* Use 1d descriptor for gamma and beta

* Add accElementwiseOp

* Extract layernorm host code

* Support different YVectorDim in GridwiseLayernorm

* Rename XSrcVectorDim to XYSrcVectorDim. Because we use same parameter in deviceOp

* Gamma and beta can share the VGPR.

* Add test for fp32 and fp16

* Fix bug of concurrency and add test case which may fail orignally

* Propagate NaN for layernorm
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* add conv1d/3d bwd weight instances

* add profiler code

* adding contraction

* add contraction example

* update examle

* update example

* format

* update readme

* clean header

* clean header

* contraction with multiple D

* rename

* fix naming issue; add instances for contraction+bilinear

* change assumed virtual layout of contraction; add client example

* update example

* update

* contraction+scale

* use type_convert

* rename

* refactor

* update example

* update example

* gemm bilinear

* clean

* update

* dump lds content in appropriate precision type

* add squared add reduction op; allows sq sum

* initial stub from regular gemm impl

* layernorm example code & host verification

* initial layernorm implementation

* tidy up

* make C0 precision type consistent with C

* clang-tidy and additional comments

* tighten up example code

* account for extra flops/bytes from normalization

* clang-format

* c0 bias/beta/gamma now have its own precision type

* AccElemOp for gemm outputs prior to feeding to layernorm

* update workgroup mapping

* rename kernel template param to reflect its dual use

* use LDS mem pool for reduction workspace

* change cshuffle precision type to f16; clean up

* clang-format

* correct naming

* explicit cast

* fully implemented gemm + bias + activation + add + norm

* activation in correct order

* reflect reduction API's recent change

* amend

* clean up; add comment

* keep up with recent changes in reduction API

* format

* resolve merge conflicts
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* interface for GEMM and GEMM+add+add+fastgelu

* rename namespace

* instance factory

* fix build

* fix build; add GEMM client example

* clean

* use 'sweep once' softmax kernel where applicable

* threadwise copy's dst buffer can specify invalid element value

* add int8 in/out float compute softmax support

give a bit of leeway for int absolute tolerance as there's a single data point of all test cases showing off-by-1 error

* format

* softmax inherits DeviceNormalization

* softmax profiler stub

* tighten up reference softmax interface

* example prints tensor dimension

* add fp32 to softmax profiler

* rename header

* hook with ckProfiler

* format

* resolve merge conflict

* resolve merge conflicts

* update normalization profiler help string

* resolve conflict

* typo

* remove residual

* softmax profiler: address feedback

* test for mixed precision input/output

* fully qualify ck::math::isnan

* add comment for device normalization interface

* revise wording

* constness for alpha/beta scaler pointer

* Extract base class for elementwise

* Refactor interface of DeviceGemmReduce. Do not use tuple in interface

* [What] Rename d into reduce in gemm + reduction related code
[Why] Prepare to add d term for add

* Unify base class of gemm + reduce and gemm + bias + add + reduce

* 1. Rename gemm_bias_add_reduce for external api
 2. Refine cmake

* Add normalize device operation

* [What] Reorder the argument
[Why] Because d0 is also the input of c.

* Add type string

* Add example of gemm_bias_add_layernorm  via external api

* Refactor example code

* clang-format

* Fix compile error

* clang-format

* Add external api for gemm_add_add_layernorm and normalize

* Add client example

* clang-format

* add client example

* clean

* clean

* reorg

* clean up profiler

* reorg

* clea

* fix profiler

* function for getinstances

* update client example

* update client example

* update client example

* update

* update example

* update Jenkins file

* update cmake

* update Jenkins

* Switch to standard ROCm packaging

* Revert .gitignore changes

* install new rocm-cmake version

* update readme
Co-authored-by: illsilin <Illia.Silin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* ad gelu and fast_gelu

* added GeLU and fast GeLU

* clean up

* add gemm+fastgelu example

* add gemm+gelu instances

* update profiler

* clean up

* clean up

* adding gemm+bias+activation

* clean

* adding bias

* clean

* adding gemm multiple d

* debugging

* add gemm bias add fastgelu

* rename, clean

* refactoring; add readme

* refactor

* refactor

* refactor

* refactor

* refactor

* refactor

* fix

* fix

* update example

* update example

* rename

* update example

* add ckProfiler

* clean

* clean

* clean

* clean

* add client app example

* update readme

* delete obselete files

* remove old client app

* delete old file

* cleaning

* clean

* remove half

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path for all examples

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* revert client app example

* clean build

* fix build

* temporary disable client test on Jenkins

* clean

* clean

* clean

* UniforFill with integer values.

* Log tested instance type string.

* Add UT for all convolution specializations.

* debugging conv

* Fix dangling reference bug.

* Small refinements.

* Fix call to error checking function.

* Small refinements to tests.

* Configure error tolerance
* Change problem size.
* Remove OddC case from types that do not support it.

* Add helper traits for AccumulatorDataType.

* Print first 5 errs in check_err for integral types.

* Rename FillUniform to FillUniformDistribution

* Refactor

* Do not use typed tests.
* Instead use plain fixture class with templatized member functions.
* Initialize tensors with integer values.

* Refine test instances.

* Properly set accumulator data type.
* Add another "big" instance.

* Refactor convolution tests.

* Revert "debugging conv"

This reverts commit b109516455631ff8fd6dce99cf7c14bf8e323ebb.

* Add pragma once + format + small refinement.

* Fix some unwanted changes.

* Clang-format

* Fix profile_convnd to use renamed tensor initializer.

* Add instances for ConvFWDND kernel case 2D

* Helpers to get ConvNDFwd 2D instances.

* Refactoring.

* Remove "small block" instance as it was generating compiler errors.
* Remove default template parameters values.

* Refine and fix test.

* Fix problem with default template parameter types.
* Adjust error thresholds for floating point values test.
* Use integer values initialization for instances test.
* Add tests for ConvNDFwd 2D case.

* Remove AccumulatorDataType type trait.

* Update unit-tests.

* Remove operator<< overload.

* Unlock conv1d/3d nd fwd instances.

* Enable skipping calculating reference using flag.

* Fix number of channels for first ResNet50 layer.

* Clang-format.
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* initial stub for standalone softmax

* start device_softmax_mk_to_mk as a wrapper to device_reduce_mk_to_m

* host softmax validates

* compiles; to implement beta scaling

* use NaN trick to efficiently ignore OOB values during sum of exponentials

* freeload device_reduce's utility functions

* clean up interface

* adding prior value (beta scaling)

* remove restriction related to perf considerations

* apply clang-format

* clean; disable diagnostics

* resolve conflicts

* add exp wrapper

* honor HostTensorDesc interface; allow implicit cast from different vector<T> type

* test softmax for fp16/fp32

* update readme

* amend commit NaN trick

* remove redundant param added during development

* format

* replace ScalarDataType with AccDataType

* separate out test programs by precision type

* move softmax sample code to its own folder

* format

* keep up with recent changes in reduction API

* remove extra header

* ad gelu and fast_gelu

* added GeLU and fast GeLU

* clean up

* add gemm+fastgelu example

* add gemm+gelu instances

* update profiler

* clean up

* clean up

* adding gemm+bias+activation

* clean

* adding bias

* clean

* adding gemm multiple d

* debugging

* add gemm bias add fastgelu

* rename, clean

* refactoring; add readme

* refactor

* refactor

* refactor

* refactor

* refactor

* refactor

* fix

* fix

* update example

* update example

* rename

* update example

* add ckProfiler

* clean

* clean

* clean

* clean

* add comment

* use type_convert

* clean

* clean element wise op

* Remove template from Reducton operation classes and add template to their operator() and GetIdentityValue() interfaces

* Change to unary elementwise operators and the reduce_unary_operator (class for mapping) and dependent variations in all host layers

* Remove the data type template parameter from reduce_binary_operator (class for mapping) and dependent variations in host layers

* Add InMemoryDataOperatonSupportedOnDataType to check the matching between data type and InMemoryDataOperation

* Use struct-scope operator template instantiation for binary and unary element-wise operations

* Change a few more elementwise operations to use template for operator()

* Tiny correction in Normalize operator

* Add static_assert to check the data type appliability for some reduction accumulator and element-wise operatons

* Correction in some examples with regard to using ReduceAccDataType

* Use static_assert for UnaryDivide

* Update to merged codes to use Element-wise operations and Reduction Accumulator operations correctly

* Tiny fix with regard to SetWorkSpacePointer()

* Copy "gemm reduce" to "gemm bias add reduce"

* Implement gemm bias add reduction

* Fix compiler error due to merge from develop

* Add tensor operation for gemm + bias + add + reduce

* Add gemm_bais_add_reduce to ckProfiler

* Add c1 functor

* Refine type

* Use reduceAccDataType instead of explicitly float

* Change to use check_err()

* Do relu in float32 instead of bhalf_t. Because bhalf_t is unsigned

* Refactor relu. using type_trait instead of overloading

* Rename DxsReduceAccElementwiseOperation to DxsReduceAccElementwiseOperation

* Fix denominator

* Refine nameing

* Fix denominator  in host

* Remove useless include header

* Use AccDataType

* Fix static_cast order

* Refine type

* [What] Remove tuple type in the base class
[Why] External api depend on base class. if base class has relationship with type, we will need many class for different type

* Use the unified naming for math functions on host and HIP kernel

* Corresponding change/simplification in reduction host/profiler/examples due to unified math functions renaming

* Renaming GetReductionZeroVal() to GetIdentityValue()

* Tiny renaming in profile_reduce_impl.hpp

* More renaming in profile_reduce_impl.hpp

* Replace zeroVal by identiyVal

* Remove ck_ prefix in the naming of ck::math provided functions

* Reference CGEMM + test stub

* Format.

* Incomplete simple implementation

* Library instances

* Sketch of tests

* Test fixes.

* Example added

* Cosmetics

* Add elementwise operation kernel and example

* Add comment

* Add template argument of dim . Prepare to support multiple dimension

* Rename example

* Support 1 dimension

* Add static assert

* Add comment

* Second auxiliary buffer added

* Extract pad

* Remove redundant argument

* Support any dimension for elementwise operation

* Remove line

* Let it be the multiple number of CU

* Move thread per block to the parameter of constructor

* Consuming binary ops to do A+B / A-B

* Fix + cosmetics + bf16 test commented out temporarily

* Format

* Enabling bf16 test

* Revert "Enabling bf16 test"

This reverts commit f497e2ba.

* Fix + test reenabled

* fix build

* Revert "fix build"

This reverts commit d7310238

.

* post PR #235 merge fix

* amend

* Single workspace for cgemm + helper

* Perf calc fix

* Review remarks: static_cast

* Review remarks: binary ops templated

* Cleaning

* Removal of instances and their tests

* Review remarks from aosew addressed

* Review remark: unnecessary attribute

* Post-merge fixes

* Restrict 4gemm to PassThrough + bug fix

* Review remarks

* update licence

* change cgemm example to fp16
Co-authored-by: rocking <chunylai@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Anthony Chang <ac.chang@outlook.com>

* Implement reduction meand and reduction square mean

* Refine file name

* Add reduce mean and square mean

* Fix parameter name

* Add normalize device op (not implement invoker::run())

* Remove epislon

* Refine deviceop

* Add 5ary elementwise for normalization

* Add layernorm example

* layerNorm verication

* Fix compiler error due to merge from develop

* Fix typo

* Fix compile error

* Refine naming

* [What] Suport non pointer for invoker and argument
[Why] Snyc coding style with gemm

* Refine folder name

* Refine class name

* Evaluate perf of the kernel

* Fix compile error

* [What] Refine perf evaluation in example of gemm + reduction
[Why] evaluation of gemm + reduction may cause verification fail. Because evaluation will not initial global memory

* clang-format

* add intrin_mfma_f64_16x16x4f64

* add example

* gemm reference add double data type

* chang init data

* fix M N PerXdlops

* fix ifdef

* add comparsion config

* add conv fwd example

* format log out

* change rc matrix egister layout

* reorganize example

* reorganize example 2

* format,because merge develop

* fix call impl adding acc data type

* lost ;

* add compiler warning

* change example tunning parameters

* add test for fp64

* add instance

* add test/gemm/gemm_fp64.cpp

* fix get name issue

* remove some tunning parameter

* fix conflict

* format

* use integer value for GEMM test

* add acc data type

* remove typeid because fp16

* fix streamconfig etc bug from merging develop

* format

* remove test_gemm_xdl_fp64

* add AccDataType

* AccDataType problem
Co-authored-by: qinletao <letaoqin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* start adding navi21 GEMM

* navi_gemm_km_kn_mn_fp32 compiles and passes one test.

* rename variables and functions in gridwise_gemm_dlops_v1r3

* add other 3 layouts; format instance

* adding more tuning parameters

add tuning parameters for other 3 layouts

* add gemm_dlops_f16

* tmp

* add dependence of DeviceGemm::IsSupportedArg() on arch

* minor changes

* minor changes

* minor changes

* minor changes

* minor changes

* minor changes

* minor changes

* push gemm_dlops into profiler

* minor changes

* if using xdl or dlops is moved into profiler_gemm_impl

* minor changes

* minor changes

* remove is_xdl from profile_gemm_impl

* make IsSupportedArg dependent on arch for other device_gemm

* minor changes

* minor changes

* fix a bug in f_generate_tensor_value

* add 64x64x64 for gemm_dlops_int8

* add 64x64x64 for gemm_dlops_int8

* comment out 3 layouts in gemm_dlops_int8; add 32x32x32 for gemm_dlops_int8; init A values to 1

* fix

* start fixing tuning parameters

* monir

* minor changes

* minor changes

* minor changes

* fixing

* adding example

* adding example

* adding example

* add gemm fp32 example

* clean up

* use 128x128x16 as MNK tile in navi21 gemm example

* bug fix

* fix test

* use new block c tile

* clean

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

* Tiny fix in dynamic_buffer.hpp to support vectorized AtomicAdd for double type

* Update to host layer and host reduction

* Merge and remove reduction kernels

* Merge and remove reduction device interfaces and update pooling device interface

* Merge and remove useless reduction device instances

* Update to reduction profiler and reduction ctests

* Update to reduction and pooling examples and add one reduction example

* Change to reduction examples to let them testable by ctest

* Add explicit pass checking for reduction and pooling examples

* Explicit assignment of tensor shapes in example reduce_blockwise_two_call

* Use atomic_add to repace atomicAdd and add atomic_add for double type

* Add reduce ctest support for double data type

* Replace to_int_vector() by using c++ std::vector::assign()

* Keep DeviceReduceThreadWise separated from DeviceReduceBlockWise

* Merge DeviceReduceBlockWise and DeviceReduceMultiBlockAtomicAdd into DeviceReduceMultiBlock

* Add GetAtomicOperationZeroValue() support for AtomicMax

* Tiny change to reduce example README.md

* Fix some tiny issues due to branch merging

* Revoke previous change in dynamic_buffer.hpp and add atomic_add for double2_t

* Add reduce multiblock_atomic_add instances for fp64 to verify vectorized atomic_add on fp64

* Renaming

* Clean the header includings in device_reduce instances header files

* enable example of conv 1d/3d for bwd weight

* make bf16 kernel do not use atomic add

* using new gridwise gemm for bwd weight on convnd bwd weight
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Use vector constructor instead

* Fix typo

* Move blockSize to the MakeArgumentPointer

* Fix naming

* Fix clang format

* remove blockSize from DeviceBinaryElementwise::Argument()
Co-authored-by: rocking <chunylai@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* [What] Rename the example
[Why] Prepare to add unary reduction

* Add global oparation to the parameter

* Add atomicmax

* Fix compile error

* Support atomicMax (hip library)

* Rename the reduction example

* Fix target name

* use p_d1_grid as the indicator directly

* Prevent performance issue. Let passthrough handle it.

* Implement the function template the specialize the float2

* No need to separate into two lines

* Remove empty line

* add comment

* Fix compile error due to merge from develop

* make the implementation of atomic_max / atomic_add explicit for each datatype

* Refine typo

* For future CI test

* Fix compiler error in ckProfiler

* Merge commit 'de2769e3a6695b38a20529261273ddc5cdaab2fe'

* simply use remove_pointer

* Rename type and var

* Refine example

* Modify reducemax example

* Fix bug in reduction

* Change initialize range

* Implement F64 version of atomicMax

* Move reduction  code together

* Add buffer atomic_max

* Fix coding style by clang-format

* Integrate new api of DeviceGemmReduce_Xdl_CShuffle

* Integrate Batch gemm reduction

* Fix example

* fix example

* clean up

* Fix batch gemm tensor operation

* Fix coding style

* Fix template augument

* Fix clang format

* Keep flexible of different stride for each D tensor

* Fix compile error for ckProfiler

* Fix typo

* [What] Fix naming
[Why] Prepare to add out elementop

* Add DoutElementOp
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: rocking <chunylai@amd.com>

* Add elementwise operation kernel and example

* Add comment

* Add template argument of dim . Prepare to support multiple dimension

* Rename example

* Support 1 dimension

* Add static assert

* Add comment

* Extract pad

* Remove redundant argument

* Support any dimension for elementwise operation

* Remove line

* Let it be the multiple number of CU

* Move thread per block to the parameter of constructor

* rename threadPerBlock with blockSize

* Support double

* rename kernel function name

* remove redundant include header

* Refine type

* Need to the final dimension

* Refine variable name

* Refine type

* Use index_t instead of int in API
Co-authored-by: rocking <chunylai@amd.com>

* Add host API

* manually rebase on develop

* clean

* manually rebase on develop

* exclude tests from all target

* address review comments

* update client app name

* fix missing lib name

* clang-format update

* refactor

* refactor

* refactor

* refactor

* refactor

* fix test issue

* refactor

* refactor

* refactor

* upate cmake and readme
Co-authored-by: Chao Liu <chao.liu2@amd.com>