Commit Graph

41 Commits

Author SHA1 Message Date
rocking5566
0ffe956ab1 Gemm reduce max (#209)
* [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>
2022-05-19 21:56:56 -05:00
JD
cec69bc3bc Add host API (#220)
* 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>
2022-05-12 09:21:01 -05:00
Adam Osewski
712e464c4e Post PR183 review fixes. (#224)
* Suppress additional warnings for googltest.

* Rename file conv_fwd_util to conv_util.

* Update includes and ConvParams member access.

* Formatting.

* Change conv_fwd_util target to conv_util

* Fix compiler errors.

* Fix leftovers.

Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-05-10 15:41:29 -05:00
myamlak
f03a1738d9 Resolution of issue #153: Add compiler warning on comparing int and size_t (#212)
* Turning compare warnings on

* Cleaning part I

* Cleaning part II

* Explicit static_cast to ck::type_convert

* Resolving large tensor size issue.

* format

* revert change to tensor descriptor; promote lementSpaceSize to 64bit

* use integer value for GEMM test

* Review remarks

* Review remarks + issues with (un)signed arithmetic

* Format fix

* Format

* Clang-format.

* fix 2gb limit issue

Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Adam Osewski <aosewski@amd.com>
2022-05-09 15:06:49 -05:00
Chao Liu
ec7c2e912e Code refactor (#175)
* format

* improving pipeline

* fix typo

* format

* adding thread group

* adding thread group

* adding thread group

* adding gemm pipeline

* tweak

* refactor

* refactor

* add missing type convert

* refactor

* refactor

* refactor

* clean

* fix build

* refactor

* format

* clean up

* use remove_cvref_t

* clean

* clean up

* clean up

* clean up
2022-05-09 14:57:59 -05:00
Qianfeng
c77ae65d40 Update to gemm_reduce and batched_gemm_reduce (#213)
* [Experimental] Change to gemm+reduce and batched-gemm+reduce

* Use threadwise-reduce function to improve the gridwise_gemm_reduce_xdl_cshuffle kernel

* Tiny fix in device_batched_gemm_xdl.hpp

* clang-format library/src/utility/conv_fwd_util.cpp
2022-04-29 11:35:25 -05:00
Adam Osewski
1a0cd5d160 Convolution FWD profiler refactor. (#183)
* Convolution ND

* Code unification across dimensions for generating tensor descriptors.
* Example
* Instances

* Move convnd f32 instance file to comply with repo structure.

* Conv 1D tensor layouts.

* Formatting and use ReferenceConv

* Reference ConvFwd supporting 1D and 2D convolution.

* Debug printing TensorLayout name.

* Conv fwd 1D instance f32

* Refactor conv ND example.

Needed to support various conv dimensio.

Needed to support various conv dimensions

* Rename conv nd example director to prevent conflicts.

* Refactor some common utility to single file.

Plus some tests.

* Refactor GetHostTensorDescriptor + UT.

* Add 1D test case.

* Test reference convolution 1d/2d

* Remove some leftovers.

* Fix convolution example error for 1D

* Refactor test check errors utility function.

* Test Conv2D Fwd XDL

* More UT for 1D case.

* Parameterize input & weight initializers.

* Rename example to prevent conflicts.

* Split convnd instance into separate files for 1d/2d

* Address review comments.

* Fix data type for flops/gbytes calculations.

* Assign example number 11.

* 3D cases for convolution utility functions.

* 3D reference convolution.

* Add support for 3D convolution.

* Check for inputs bigger than  2GB.

* Formatting

* Support for bf16/f16/f32/i8 - conv instances + UT.

* Use check_err from test_util.hpp.

* Split convnd test into separate files for each dim.

* Fix data generation and use proper instances.

* Formatting

* Skip tensor initialization if not necessary.

* Fix CMakefiles.

* Remove redundant conv2d_fwd test.

* Lower problem size for conv3D UT.

* 3D case for convnd example.

* Remove leftovers after merge.

* Add Conv Specialization string to GetTypeString

* Skip instance causing numerical errors.

* Small fixes.

* Remove redundant includes.

* Fix namespace name error.

* Script for automatic testing and logging convolution fwd UTs

* Comment out numactl cmd.

* Refine weights initalization and relax rtol for fp16

* Move test_util.hpp to check_err.hpp

* Refine weights initalization and relax rtol for fp16

* Refactor common part of test conv utils.

* Move utility function to single common place.

* Add additional common functions to utility.

* Refactor convnd_fwd_xdl examples.

* Remove redundant files.
* Unify structure.

* Add constructor to ConvParams.

* And add input parameters validation.

* Modify conv examples to use single utility file.

* Remove check_error from host_tensor.hpp

* Get rid of check_indices function.

* Remove bf16_to_f32 function overload for scalars.

* Fix namespace.

* Add half_float::half for check_err.

* Fix conv params size in UT.

* Fix weights initialization for int8.

* Fix weights initialization for int8.

* Add type_convert when store output in ref conv 1D.

* Get back old conv2d_fwd_xdl operation.

* Silence conv debug print.

* format

* clean

* clean

* Fix merge.

* Fix namespace for check_err

* Formatting.

* Fix merge artifacts.

* Remove deleted header.

* Fix some includes and use ck::utils::check_err.

* Remove unused check_indices restored by previous merge.

* Fix namespaces after merge.

* Fix compilation error.

* Small fixes.

* Use common functions.
* Fix filename
* Fix namespaces.

* Fix merge artifact - retrieve removed by accident fun.

* Fix ConvForwardSpecialization.

* Working example of OpInstanceRunEngine for conv2dfwd UT.

* Adhere to coding style rules.

* Formatting and adhere to coding style rules.

* Fix merge artifacts.

* Utility for collecting conv fwd instances.

+ Plus commmon part for parsing cmdline params.

* Refactor FillUniform because of segfault for int8_t.

* Naming convention.

* Elegant version of device mem allocation.

* Use OpInstanceRunEngine in conv fwd nd tests.

* Multiple refinements.

* conditional init
* don't run reference op if not provided.

* Use OpInstanceRunEngine for ckProfiler conv_fwd

* Refactor common tensor fill function to separate file.

* Clean up unused functions.

* Support different init methods.

* Create CMake target for conv_fwd_util.

* Add header for profile_convnd_fwd.cpp

* Fix CMakefiles to link with conv_fwd_util where needed.

* Fix some clutter.

Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-04-21 17:39:39 -05:00
Qianfeng
c1ef73192e Use ck::half_t for Host Reduction (#195)
* Add math functions for host

* Change to host reduction to use ck::math:

* Remove the using of half_float::half and half.hpp from reduction example/profiler/ctest
2022-04-20 22:09:26 -05:00
Jianfeng Yan
ac0d806650 Fix typo in batched gemm profiler (#176)
* forgot passing BatchedCount in some profiler_batched_gemm

* delete default BatchCount
2022-04-07 13:17:15 -05:00
Adam Osewski
abf4bdb9a9 Common forward convolution utility refactor. (#141)
* Convolution ND

* Code unification across dimensions for generating tensor descriptors.
* Example
* Instances

* Move convnd f32 instance file to comply with repo structure.

* Conv 1D tensor layouts.

* Formatting and use ReferenceConv

* Reference ConvFwd supporting 1D and 2D convolution.

* Debug printing TensorLayout name.

* Conv fwd 1D instance f32

* Refactor conv ND example.

Needed to support various conv dimensio.

Needed to support various conv dimensions

* Rename conv nd example director to prevent conflicts.

* Refactor some common utility to single file.

Plus some tests.

* Refactor GetHostTensorDescriptor + UT.

* Add 1D test case.

* Test reference convolution 1d/2d

* Remove some leftovers.

* Fix convolution example error for 1D

* Refactor test check errors utility function.

* Test Conv2D Fwd XDL

* More UT for 1D case.

* Parameterize input & weight initializers.

* Rename example to prevent conflicts.

* Split convnd instance into separate files for 1d/2d

* Address review comments.

* Fix data type for flops/gbytes calculations.

* Assign example number 11.

* 3D cases for convolution utility functions.

* 3D reference convolution.

* Add support for 3D convolution.

* Check for inputs bigger than  2GB.

* Formatting

* Support for bf16/f16/f32/i8 - conv instances + UT.

* Use check_err from test_util.hpp.

* Split convnd test into separate files for each dim.

* Fix data generation and use proper instances.

* Formatting

* Skip tensor initialization if not necessary.

* Fix CMakefiles.

* Remove redundant conv2d_fwd test.

* Lower problem size for conv3D UT.

* 3D case for convnd example.

* Remove leftovers after merge.

* Add Conv Specialization string to GetTypeString

* Skip instance causing numerical errors.

* Small fixes.

* Remove redundant includes.

* Fix namespace name error.

* Script for automatic testing and logging convolution fwd UTs

* Comment out numactl cmd.

* Refine weights initalization and relax rtol for fp16

* Move test_util.hpp to check_err.hpp

* Refine weights initalization and relax rtol for fp16

* Refactor common part of test conv utils.

* Move utility function to single common place.

* Add additional common functions to utility.

* Refactor convnd_fwd_xdl examples.

* Remove redundant files.
* Unify structure.

* Add constructor to ConvParams.

* And add input parameters validation.

* Modify conv examples to use single utility file.

* Remove check_error from host_tensor.hpp

* Get rid of check_indices function.

* Remove bf16_to_f32 function overload for scalars.

* Fix namespace.

* Add half_float::half for check_err.

* Fix conv params size in UT.

* Fix weights initialization for int8.

* Fix weights initialization for int8.

* Add type_convert when store output in ref conv 1D.

* Get back old conv2d_fwd_xdl operation.

* Silence conv debug print.

* format

* clean

* clean

* Fix merge.

* Fix namespace for check_err

* Formatting.

* Fix merge artifacts.

* Remove deleted header.

* Fix some includes and use ck::utils::check_err.

* Remove unused check_indices restored by previous merge.

* Fix namespaces after merge.

* Fix compilation error.

* Small fixes.

* Use common functions.
* Fix filename
* Fix namespaces.

* Fix merge artifact - retrieve removed by accident fun.

* Fix ConvForwardSpecialization.

* Adhere to coding style rules.

* Fix merge artifacts.

Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-04-05 15:16:59 -05:00
ltqin
6717168c18 Patch for bwd data comments (#174)
* change function name and way to set input zero

* change enable if
2022-04-04 20:33:53 -05:00
ltqin
781cacd2e6 NHWC Conv2d Bwd weight fp16 ckprofiler and test (#166)
* change backward weight name

* start add bwd weight lib and profiler

* change tuning paramter

* change output info

* add bwd weight test

* change test info

* using conv_util

* change wgt to weight

* add }

* add fp32
2022-04-04 20:32:00 -05:00
ltqin
c0e95f6204 Patch for bwd data #134 (#168)
* remove switch for NDimSpatial

* change in, out and wei name

* rename reference thumb function name

* remove test
2022-03-31 12:34:18 -05:00
Chao Liu
cd167e492a Compile for gfx908 and gfx90a (#130)
* adding compilation for multiple targets

* fix build

* clean

* update Jekinsfile

* update readme

* update Jenkins

* use ck::half_t instead of ushort for bf16

* rename enum classes

* clean

* rename

* clean
2022-03-31 12:33:34 -05:00
Anthony Chang
f015c77687 use single threaded tensor generator (#161) 2022-03-30 22:28:30 -05:00
Jianfeng Yan
c8f3acf9c0 batched_gemm: use profiler in ctest (#163) 2022-03-30 21:32:49 -05:00
Jianfeng Yan
34c661e71c Batched gemm and reduction (#156)
* adding batched_gemm_and_reduction

* batched_gemm_reduce works with bactch_count=1

* fix a bug in grid_size; batched_gemm_reduce works for batch_count > 1

* adding profiler for batched_gemm_fp16

* fixed a bug in declaration of d1 and d0; both example and profiler work

* clang-format

* cleanup

* batched_gemm_reduce: add test

* minor change

* fixed some typo in function names
2022-03-30 11:21:18 -05:00
ltqin
0536f2b312 Unified implementation of 1d/2d/3d conv bwd-data. fp32/fp16/bfp16/int8 (#134)
* start convnd bwd data

* add 3d laoyout name

* add conv1d reference

* add con3d reference

* finished example client code

* conv1d kernel finished

* fix input error

* add conv3d

* add 3d layout in conv_utils.hpp

* fix sepecial check

* addconvnd lib

* add test for bwd data

* finished test

* add check slice length

* convnd bwd data start

* profiler can be compiled

* fix some bug

* set input to zero

* modify readme for example

* fix test_convnd_bwd_data bug

* test_convnd_bwd_data parameter desc

* workaround for 1d

* workaroud for 2d

* change init value

* workaround for 3d int8

* fix init value bug

* remove workaround

* fix acc data type

* add int32

* change select function to template

* tilda to tilde

* remove int32 instance

* fix commit for device hpp

* fix comments for profiler

* using profile imp to test

* add pass verification

* fix conv2d reference

* fix conflict

* remove double batched_gemm

* fix exampel conv2d data and test convnd

* format

* change conv2d_bwd_data return value

* remove repeat = 1

* remove conv bwd data

Co-authored-by: ltqin <letaoqin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-03-29 10:52:25 -05:00
zjing14
12f4cfce96 fixed alloc mem size (#145) 2022-03-23 22:19:38 -05:00
Chao Liu
f95267f166 Gemm+Reduce Fusion (#128)
* add gridwise gemm v4r1

* rename

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* use sfc in shuffling

* remove hardcode

* remove hardcode

* refactor

* fix build

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* format

* clean

* adding gemm+reduce

* adding profiler for gemm+reduce

* adding gemm+reduce profiler

* fix build

* clean up

* gemm+reduce

* fix build

* update DeviceGemm_Xdl_CShuffle; update enum to enum class

* clean up

* add test for gemm+reduce

* clean up

* refactor

* fix build

* fix build
2022-03-23 22:18:42 -05:00
Jianfeng Yan
d91f9f119c Batched gemm bf16 (#142)
* add bf16 for batched gemm

* batched_gemm_bf16 works

* recover accidently changed files
2022-03-22 18:18:43 -05:00
zjing14
716f1c7fb1 Grouped GEMM for fp16 (#126)
* init of grouped_gemm

* 2 gemm test

* perf test

* clean

* wrap desc into a struct

* test cast static_arr to pointer

* add ptr to GemmDesc

* add grouped gemm profiler

* fixed mem issue with unique_ptr

* clean

* clean

* finished ckprofiler

* Update README.md

* readme

* fixed readme

* add example

* improve code

* fixed comments: reserve, seperate ptr and gemm_shapes

* merge group and non-group

* fixed comments: replace push_back with emplace_back to avoid copy constructor

* fixed comments: unified blk2ctile; add test

* ci fix

* fixed ci

* fixed ci

* fixed ci
2022-03-22 18:18:18 -05:00
Qianfeng
9a8ee8a39a Reduction for int8 and bfloat16 (#125)
* Use thread cluster descriptor and explicit M_K 2d descriptor to simply Blockwise Reduction

* Change by replacing ReduceDims by NumReduceDims as Device Reduce interface template parameter

* Rename the folder name for the pool2d and reduce examples

* Update to reduction test scripts

* Add Readme for pool2d_fwd and reduce_blockwise examples

* Add support for int8_t reduction (ADD/AVG, MIN/MAX/AMAX)

* Tiny fix in reduce profiler and tiny update in reduce testing scripts

* Tiny fix in testing script profile_reduce_no_index.sh

* Tiny fix in testing script profile_reduce_no_index.sh

* Add support for bfp16 reduction (using bhalf_t = ushort)

* Tiny fix in amd_buffer_addressing.hpp

* Tiny change in script/profile_reduce_with_index.sh

* Use AccDataType for Beta value and use element_wise::PassThrough

* Use type_convert for type converting in host layer reduction

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming all NumReduceDims to NumReduceDim

* Fix the leaked type_convert in ThreadwiseTensorSliceTransfer_v2

* Update to testing scripts to add bf16 support

* added more static_assert

* Remove buggy tunable configurations defined in device_reduce_instance_xxx.hpp

* Add static_assert to give compile-time warning for incorrect thread slice-size/vector-size configurations

* minor change

* Refine and fix (in GetWorkspaceSizeInBytes of MultiBlockPartialReduce) to make int8 completely pass

* Tiny renaming in gridwise_2d_reduction_multiblock_partial_reduce.hpp

* Tiny fix in script/profile_reduce_no_index.sh

* Refine in DeviceReduce layer with regard to using NumInvariantDim/NumReduceDim or InvariantDims/ReduceDims

* Generic renaming in host reduction and DeviceReduce layer

* Add support for 4-d all dimension reduction in the profiler and add_device_reduce_xxx instances

* Use multi-thread and simplification for host Reduction implementation

* Add ctest for reduction

* Update to clarify the using of data init method in produce_reduce/example_reduce/test_reduce/

* Update to the reduce CTest executables to enable default testing behavior when no command argument

* Renaming

Co-authored-by: Jianfeng yan <jfyan008@gmail.com>
2022-03-22 14:35:14 -05:00
Jianfeng Yan
cb87b049de refactored deviceBatchedGemm; removed GridwiseBatchedGemm; added fp32 and int8 to profiler (#120)
changed long_index_t to index_t when computing memory offset

uncomment other ops in profiler

added test for batched_gemm
2022-03-21 16:45:14 -05:00
rocking5566
485ea46a40 Gemm_c_shuffle (4 layouts) X (fp32 bf16 int8) (#131)
* [What] Separate fixpoint gemm from gemm example
[Why] let example of gemm_int8 be pure gemm.
[What]
1. Add gemm_requant_relu_requant,
2. Let CDataType be int32 in pure gemm, because no one use int8 CDataType. It is also part of gemm_requant_relu_requant

* Fix path

* Revise cmakelist due to merge develop

* Add gemm fp16 test

* Extract PrepareGemmTensor

* Extract TestGemm

* Add test for different layout

* Add 4 layouts of shuffle version of fp32

* Add 4 layouts of shuffle version of int8

* Add 4 layouts of shuffle version of bf16

* replace all DeviceGemmPtr_ with DeviceGemmNoOpPtr to fit naming convension

* Add test for non-shuffle verstion of gemm

* Fix typo

* Print kernel information

* Add rest of the fp32 kernel to the test

* 1. Add rest of the fp16 device iop.
2. Mark the invalid device operation

Co-authored-by: rocking <chunylai@amd.com>
2022-03-21 15:59:51 -05:00
ltqin
b51808d7a5 Fix conv2d bwd data bug when filter is 1x1 and stride = 2 (#132)
* fix bwd data filter1strid2 bug

* fichangeshort to ck::bhalf_t

* reset input to zero

Co-authored-by: ltqin <letaoqin@amd.com>
2022-03-21 10:53:23 -05:00
Qianfeng
827301d95a Pr82 followup (#115)
* Use thread cluster descriptor and explicit M_K 2d descriptor to simply Blockwise Reduction

* Change by replacing ReduceDims by NumReduceDims as Device Reduce interface template parameter

* Rename the folder name for the pool2d and reduce examples

* Update to reduction test scripts

* Add Readme for pool2d_fwd and reduce_blockwise examples

* Tiny fix in reduce profiler and tiny update in reduce testing scripts

* Tiny fix in testing script profile_reduce_no_index.sh

* Tiny change in script/profile_reduce_with_index.sh

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming all NumReduceDims to NumReduceDim
2022-03-10 10:14:43 -06:00
Qianfeng
e17c0d8008 Reduction in Composable Kernel (#82)
* Initial adding of generic reduction

* Initial adding of generic reduction ...

* Updates to make compiling done

* clang-format all files

* clang-format some files again

* Renaming in profiler/include/profile_reduce.hpp

* Updates and make BlockWise cases passed

* Updates and make ThreadWise and MultiBlockTwoCall cases passed

* Remove the support for MUL and NORM1 reduceOp from the profiler and the device instances

* Change to replace the dim0_max_vector_size/dim1_max_vector_size template argument in the device reduce classes

* format

* adding pooling

* added max and average pooling

* comment out cout and kernel timing

* Tiny simplification in profiler/reduce_profiler.cpp

* Add example for reduce_blockwise

* Tiny updates

* Change to pass the ElementWiseOp from device layer to kernel

* Fix the vectorDim and vectorSize in Device layer

* Enable vector load on both dim0 and dim1 for Threadwise method

* Tiny updates

* Change to let the user to pass the preUnaryOp and posUnaryOp

* Make pooling example work

* split device_reduce_instance into two libraries

* Tiny update

* Replace nanPropaOpt enum by boolean propagate_nan

* Simplification in DeviceReduce layer codes

* update build

* Change to clarify the difference between ck::half_t and half_float::half

* Renaming in all the reduction codes

* Add VectorSize as template parameter for device layer

* Add BetaIsZero as kernel template and as AccDataType for alpha

* print

* Small updates for pooling

* Updates for host_generic_reduction for reference

* Update to make AVG pooling pass

* Update to make MAX pooling with indices output pass

* fix

* add OutDst vector store to threadwise reduction and pooling

* tweak

* turn off check_indices that caused build issue

* refactor pooling

* clean up

* turn off check_indices for building issue for php-compiler

* add more tile size for odd C

* tweak conv for odd C

* update script

* clean up elementwise op

* add hack in reduction_operator.hpp to avoid compile error. To fix it, need to use element_wise_op in reduction op

* Add OutVectorSize as device and kernel tunable, also update to Elementwise Operations

* Move reduce operator mapping to host layer file reduction_operator_mapping.hpp from reduction_operator.hpp

* Change to the unary operators

* Move the definitions of unary operations to element_wise_operation.hpp

* re-org files

* Refine in device interfaces and multiblock kernels

* Split the reduction configurations into instances for specific methods

* Update in getTypeString() of device pool2d

* Renaming in host and kernel

* Tiny update in profiler/src/profiler.cpp

* Uncomment in device_operation/CMakeLists.txt to enable the building of all operations

* Make check_indices a templated function to remove some linking issue

* Renaming in the profiler reduce module

* Add support for double Reduction (but disable MultiblockAtomicAdd for double)

* Tiny correction of literal string

* Rename DevicePoolFwd to DevicePool2dFwd

* Split device_reduce_instance_xxx.cpp files according to the data types to speed up compiling

* Add comments for lists of configurations, lists of instances and references of add_reduce_instances_xxx

* Remove un-used header file gridwise_generic_reduction_wrapper_common.hpp

* Renaming and refining in the Reduction codes

* Tiny change in the unary operators

* Renaming symbols and files

* Renaming symbols in the kernels

* Move kernel kernel_set_buffer_value to separate file

* Add IndexDataType template parameter for kernels and use int32_t as index data type in device layer

* Tiny update in the kernels

* Remove definition of sqrtf()/isnan()/abs() for half_t due to some ADL issue

* Simplify a helper function in device layer

* Tiny adjustment in testing data initialization

* Renaming in kernel/device/host

* Add two testing scripts for reduction

* Refine the Unary operators in element_wise_operation.hpp

* Update in the reduce profiler module

* Update to the reduction testing scripts

* reduce compile parallelism

* change CI docker to rocm5.0

* remove unused variables

* fix build

Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-03-05 16:46:51 -06:00
rocking5566
7e9a9d32c7 [Bf16 & int8] [example & ckprofiler] (#100)
* Add int8 of mk_nk_mn to the ckProfiler

* Add example of int8 gemm

* Fix typo, use ushort instead of half_t for bfloat16

* replace ushortXXX_t to bhalfXXX_t

* rename ushort to bhalf_t

* Add bf16 example

* Add bf16 gemm to ckProfiler

* Fix alignment

* Fix typo

* Add unit test for gemm_xdl int8

* Add gemm_xdl fp32 unit test

* Add gemm_xdl bf16 unit test

* fix build

* fix build issue due to merge conflict

* Fix build

* Fix build error

Co-authored-by: rocking <chunylai@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-03-04 15:56:44 -06:00
ltqin
c254e5abd2 NHWC conv 2d: bwd fp32/fp16/bfp16/int8, Device level tuning and host API (#92)
* start conv2d bwd api

* kernel running

* add bwd reference

* change to no shuffle

* fix bwd reference

* pass verification

* add Filter1x1Stride1Pad0 and start testing

* change some tuning parameter

* fix test error

* add fp16 tuning parameter

* add bf16 tuning parameter

* add int8 tuning parameters

* change fp32 tuning parameter

* add bwd to profiler

* fix bug for bwd profiler

* fix ckProfiler bug

* change conv2d_bwd_xdl to fp16

* fix bug in comments

* fix precompile id

* fix enum conv name

* chage _bwd_ to _bwd_data_

* change conv2d_bwd example id

* bwd to bwd data

* fix prehead

* fix MakeDefaultBlock2CTileMap ,import form merge develop

* format bwd instance

* bwd to bwd data

* change name bwd to bwd data

* change name bwd to bwd data in example

* formate code

* change conv2d bwd data id in example

* rewrite readme for example

* fix CalculateMagicNumbers about div zero

* add workaround CK_WORKAROUND_SWDEV_325164

* change test_conf2d_bwd_data show info

* format

* fix bug for workaround:CK_WORKAROUND_SWDEV_325164

* formate tuning parameters

* formate tuning parameters again

* formate tuning parameters 3

* formate tuning parameters 4

* remove add function template

* format

* update comment

Co-authored-by: ltqin <letaoqin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-03-04 00:08:26 -06:00
zjing14
e221d11e51 Split k f16 (#97)
* init for splitk f16

* a working prototype

* debug

* perf debug

* update example

* instances for mk kn

* add instances for all layers

* clean

* clean

* add tuning

* format

* add mn_padding into irregular tile

* clean

Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-02-25 01:19:37 -06:00
Chao Liu
22d438ae9e Add gridwise GEMM pipeline (#89)
* clean up

* add mutilple thread scratch to ThreadwiseTensorSliceTransfer_v3r1

* add 2 stage prefetch

* add more sanity check into transform_tensor_descriptor

* tweak

* enabling 2 stage prefetch to exsiting gridwise gemm; tweak

* enabling 2 stage prefetch to exsiting gridwise gemm

* move gridwise gemm pipeline in class; clean up

* add some irregular tile size

* update CalculateHasMainK0BlockLoop for multi-stage-prefetch

* refactor gridwise gemm pipeline class
2022-02-23 17:23:49 -06:00
rocking5566
19c5d6e651 Gemm alpha beta profiler (fp32 & fp16) (#91)
* [What] Refactor verification of gemm alpha_beta, move to reference operation
[Why] Sync with other verification

* Profile mk_nk for gemm bias 2d

* Support bias 2d with mn * kn in profiler

* Support bias 2d with km*kn and km*nk in profiler

* Support fp32 bias 2d in profiler

* format

* format

Co-authored-by: rocking <chunylai@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-02-21 11:35:21 -06:00
ltqin
880fbee957 NHWC conv 2d: fwd bfp16/int8, Device level tuning and host API (#73)
* add fwd bf16 conv

* change tunning parametor

* add int8 for conv fwd

* remove comments

* change tunning parametor for int8

* change init int8 example

* add test for conv2d fwd

* change device operation file pos because merge develop

* fwd int8 use reference

* test_conv_fwd use reference

* add braket for if statement

* rename fwd example name

* remove StaticBufferOfVectorTypeV2

* tweak example

Co-authored-by: ltqin <letaoqin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
2022-02-11 20:06:40 -06:00
zjing14
b53e9d08ed Batched GEMM for fp16 (#79)
* prepare host for batched_gemm

* init commit of batched kernels

* fixed

* refine transform with freeze

* m/n padding

* fixed a bug; clean

* add small tiles

* clean

* clean code

* clean code

* add nt, tn, tt layout

* add missing file

* use StaticBufferTupleOfVector instead

* add reference_batched_gemm

* fixed a macro
2022-02-11 09:36:52 -06:00
Chao Liu
823657ed12 GEMM+Bias+ReLU+Add (#76)
* tweak conv for odd C

* update script

* clean up elementwise op

* fix build

* clean up

* added example for gemm+bias+relu+add

* added example for gemm+bias+relu

* add profiler for gemm_s_shuffle; re-org files

* add profiler

* fix build

* clean up

* clean up

* clean up

* fix build
2022-02-06 22:32:47 -06:00
ltqin
4be7f0198e add split-k GEMM (#59)
* add DeviceGemmSplitKXdl

* add file device_gemm_splitk_xdl.hpp

* set c matrix zero

* using atomic

* add all tuning parameter to f32 mkkn

* grid size change to 720

* add tunning parameter for NT

* add tunning parameter for TN

* add tunning parameter for TT

* add m=96tunning parameter

* add lost config

* add element wise operation

* fixed MPerBlock=96

* remove marco for slpitk swtich

* add test

* add new line at the end of device_gemm_xdl_instance.hpp

* remove step hack

* seperate split-k instance files

* add tunning parameters

* change disired grid size to parameters

* remove slice length

* add desiredgridsize parameter to ckProfiler

* add losting file device_gemm_xdl_splitk_instance.hpp

* change desired gride size to kbatch

* format

* format

* clean up

* add selection of device_instances

* clean code

* fix build issue

Co-authored-by: ltqin <letaoqin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Jing Zhang <jizhan@amd.com>
2022-02-02 22:47:27 -06:00
Chao Liu
acbd7bd7c5 Fusion Conv+Bias+ReLU(+Add) (#62)
* fix relu

* clean up

* clean up

* adding 1x1 conv

* adding 1x1 conv

* added 1x1 conv

* refactor

* refactor

* refactor

* added profiler for conv+bias+relu+add

* clean up

* adding conv+bias+relu

* adding conv+bias+relu

* added conv+bias+relu

* Update README.md

* update cpu verification

* adding c shuffle

* update static_tensor for dealing with invalid element

* adding c shuffle

* debugging

* fix bug

* convert to fp16 before shuffle

* shuffle more than one M/NRepeat

* clean up

* remove coordinate step hack from GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v3r1

* clean up

* remove coordinate step hack from all gridwise gemm xdl

* clean up coordinate step hack

* clean up coordinate step hack

* ThreadwiseTensorSliceTransfer_v3r2 support pointwise op on both src and dst

* adding output shuffle in conv+bias+relu+add

* update

* added conv+bias+relu+add with c shuffle

* added conv+bias+relu+add with c shuffle

* fix forward_sweep bugs in threadwise copy

* clean up

* refactor

* clean up

* clean up

* added conv_c_shuffle+bias_relu

* clean up

* added conv+bias+relu+atomic_add

* clean up

* clean up

* clean up

* clean up

* clean up

* clean up

* misc fixes; add 1x1 specialization

* clean up

* delete unused device op

* clean up

* add support for odd C value
2021-12-26 07:43:42 -07:00
Chao Liu
41cdd3801a GEMM/Conv+BiasAdd+ReLU+Add (#55)
* gemm+activation

* move C pointwise operation into threadwise copy

* add pointwise operation to A/B matrix

* update ckProfiler

* adding bias add

* adding bias add

* adding bias add

* added bias add; worked around compiler issues

* clean up

* clean up

* Update README.md

* Update README.md

* Update README.md

* clean up

* add conv_xdl example

* adding conv_xdl_bias_relu_add example

* add conv+bias+relu+add, but has register spill issue

* tweak

* tweak

* refactor

* Update README.md

update readme for example/2_gemm_xdl_bias_relu_add

* clean up

* Update README.md

update readme for example/3_conv_xdl

* Update README.md
2021-12-02 20:07:37 -06:00
zjing14
0a66c54e95 fixed multiple definition issue of bfp16/fp32 conversion function when building ckProfiler (#51)
* fixed bfloat16 issues

* refactor type_convert

Co-authored-by: Chao Liu <chao.liu2@amd.com>
2021-11-16 15:44:17 -06:00
Chao Liu
e823d518cb ckProfiler and device-level XDL GEMM operator (#48)
* add DeviceGemmXdl

* update script

* fix naming issue

* fix comment

* output HostTensorDescriptor

* rename

* padded GEMM for fwd v4r4r4 nhwc

* refactor

* refactor

* refactor

* adding ckProfiler

* adding ckProfiler

* refactor

* fix tuning parameter bug

* add more gemm instances

* add more fp16 GEMM instances

* fix profiler driver

* fix bug in tuning parameter

* add fp32 gemm instances

* small fix

* refactor

* rename

* refactor gemm profiler; adding DeviceConv and conv profiler

* refactor

* fix

* add conv profiler

* refactor

* adding more GEMM and Conv instance

* Create README.md

Add build instruction for ckProfiler

* Create README.md

Add Readme for gemm_xdl example

* Update README.md

Remove build instruction from top most folder

* Update README.md

* clean up
2021-11-14 11:28:32 -06:00