* allow building CK for specific data types
* add CI build and test stage on Naiv3x without some int8 instances
* add missing gemm fp16 instances
* add the changes to the missed cmake file
* add empty lines at end of source files
* Do not build quantization client example on navi3 in CI
* disable batched_gemm_multi_d_int8 instances with DTYPES
* disable device_conv2d_bwd_data_instance with DTYPES
* fix ckprofiler for conv_bwd_data for int8
* properly isolate the conv_bwd_data int8 instances
* remove empty line
* Use dim 0 as faster dim for writing mean/var/count workspace in batchnorm multiblock method [performance]
* Add CountDataType as template parameter in blockwise_welford
* Add utility/get_shift.hpp
* Add BatchNorm multiblock single-kernel implementation
* Add smem inline assembly based implementation of gms_init/gms_barrier/gms_reset for gfx90a
* Renaming in device_batchnorm_forward_impl.hpp
* Tiny fix in the batchnorm_fwd profiler
* Revert "Add smem inline assembly based implementation of gms_init/gms_barrier/gms_reset for gfx90a"
This reverts commit d16d00919c.
* Use the old two-kernel batchnorm multiblock method for gfx1030
* Use the old two-kernel batchnorm multiblock method for gfx908
* use the single-kernel batchnorm multiblock method only for gfx90a
* Remove get_wave_id() from utility/get_id.hpp since it is not used
* Set true for testing running mean/variance and saving mean/invvariance in the examples
* Fix to copy-right words
* Remove un-needed including in utility/get_id.hpp
* Add comments to workgroup_synchronization.hpp
* Remove un-used codes in gridwise_multiblock_batchnorm_forward.hpp
* Renaming in the kernels
* Remove un-used kernel file
* Add NumReduceDim template parameter to DeviceSoftmax and Softmax client API to simplify instances collecting
* Move the generic kernel instance to be the first of the instance list for elementwise op of normalization
* Add GetGenericInstance() interface for DeviceOperationInstanceFactory class of DeviceSoftmax
* Add testing of GetGenericInstance() in client_example of Softmax
* Revert "Add testing of GetGenericInstance() in client_example of Softmax"
This reverts commit f629cd9a93.
* Revert "Add GetGenericInstance() interface for DeviceOperationInstanceFactory class of DeviceSoftmax"
This reverts commit a9f0d000eb.
* Support generic kernel instance to be the first instance returned by GetInstances() for GroupNorm
* Move generic kernel instance to separate tuple for elementwise op of normalization
* Remove un-used files for softmax instance
* Store generic kernel instance to separate tuple for softmax
* Add IsSupported checking for generic instance to client example of softmax
* Replace the get_device_normalize_from_mean_meansquare_instances() by the DeviceOperationInstanceFactory class for elementwise-normalization
* clang-format fix
* Remove int8 from softmax instances
---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* Expand the base class of pool2d, prepare to share base class with pool3d
* Add pool3d device op
* Add pool3d f16 example
* Refactor the base class. implement generic pooling in the future
* clang format
* get original index in max pooling
* Add outputindex to base class
* Fix dimension
* Add pooling instance
* Use indexType instead
* Remove useless header
* Extract IndexDataType to template
* Extract pooling reference code
* clang format
* clang format
* Fix typo
* Add tensor stride
* Add missing header
* Add index stride and output stride
* Refine naming
* Add type to base class
* Rename file
* Use proper size
* Fix typo
* Refine naming
* Modify the argument into vector.
* Add max pool profiler
* Refine naming
* Support f32 pool
* Fix typo
* Add avg pool2d fwd in profiler
* clang format
* Rename AccDatatype to ComputeDatatype
* Fix init
* test pool
* Extract variable
* Add client example
* Check the pooling dim
* clang format
* Connect argv and arg_parser
* Add found check
* Remove useless header
* Refine naming
* Adjust the order of device_pool_fwd
* Add contraction profiler and tests
* Build and style fixes
* Allow to use any elementwise operator for ref_contraction
* Introduce profile_contraction_scale and profile_contraction_bilinear
* Make ref_contraction generic and extend interface tests
* Stylistic minor fixes
* Extend test_contraction_interface
* Grouped gemm + Gelu instances.
* Device Instance Factory for GroupedGemm+Gelu
* Client example
* Rangify fill helper functions.
* Fix name clash.
* Profiler for grouped_gemm+gelu
* No need to use full namespace name.
* Add check for MRaw divisible by vector load.
* Ugly fix for big errors.
* Add grouped_gemm+gelu to profiler CMakelists.
* Store in argument additional info.
* Information about Mraw, Nraw, Kraw values.
* Use FastGelu instead of Gelu.
* Change client ex to use FastGelu
* Remove relaxed error precision.
* Remove duplicate output elementwise-op
---------
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* Add gemm + layernorm instance
* Add ckProfiler
* Add test
* Add client example
* Detect if user forger to set the workrspace
* Use literal in the example
* [What] use builtin function for sqrt
[Why] compiler will not use v_sqrt_f64_e64 if we use ::sqrt()
* check gemm vaildity in IsSupportedArgument
* Add more testcases
* Merge duplicated folder in client example
* Print more infomation
* Use better kernel parameter for MS problem size
* clang format
* Add constexpr for if condition and remove redundant include
* Remove cstdlib and add constexpr
* File renaming and class renaming for device element-wise operation
* Add batchnorm-infer instances, external API and client example
* Add batchnorm-infer profiler module and gtests
* Remove file device_elementwise_extension.hpp and move NormalizeInInfer operation to element_wise_operation.hpp
* Remove the using of class aliasing for DeviceElementwiseForBatchNormInfer
* Rename class and file due to conflict from device_elementwise_2d.hpp
* Fix namespace in batcnnorm_infer_nhwc client example
* Use double as alpha/beta values type in reduce device op api
* Use double as alpha/beta values type in softmax device op api
* Use double as alpha/beta values type in multiple-reduce device op api
* Use double as epsilon value type in normalization/elementwise-normalization device op api
* Re-structure ckProfiler source files
* Rename profiler.cpp to main.cpp
* Modularize ckProfiler operations
* Add description for profiler operations
* Use longer name to avoid name collision
* Use macro to delay expansion
* Use std::move() to avoid object copying
* Prohibit users from calling dtor
* Use macro to eliminate redundant code
* Make friend function hidden
* Add missing include directive <iostream>
* Fix wrong include directives
* Remove int8 from batchnorm-forward instances since it is not needed for forward training and could fail test
Co-authored-by: Qianfeng Zhang <Qianfeng.Zhang@amd.com>
* Refine the device batchnorm-backward base API templates and data type assignments
* Remove duplicated kernel file
* Add batchnorm backward instances and external API
* Add batchnorm-backward profiler and tests
* Add client example which uses batchnorm backward external API
* Merge test/batchnorm_fwd and test/batchnorm_bwd into one directory
* Loose the threshold for batchnorm-backward check_err()
* Update to device_batchnorm_forward base class to include all template parameters for problem description
* Add batchnorm forward instances and external api
* Add batchnorm forward profiler module which uses the external api
* Add some comments in batchnorm_forward example to explain the dimensions in lengths[]
* Replace the reference_batchnorm_forward_nhwc_c by generic reference_batchnorm_forward
* Improvement to the batchnorm infer base API
* Add batchnorm forward client example which shows using the batchnorm forward external API
* Add test for batchnorm forward
* Tuning the batchnorm profiler initialized values and error threshold
* Add support for bhalf_t in instances/external api/tests
* Add support for int8_t in instances/external api/tests
* Add support for double in instances/external api/tests
* Let ScaleDataType and BiasDataType be same as XDataType and YDataType when creating instances
* Checking before running best instance in batchnorm_fwd_nhwc client example
* Add checking for YElementwiseOp in batchnorm_forward external API
* Add more types in batchnorm forward profiler
* Add more test lengths
Co-authored-by: rocking5566 <ChunYu.Lai@amd.com>
* Remove redundant CMake setting
* Extract common code from files
* Rename folder 'convnd' to 'conv'
* Use std::array<> to accept compile-time kwnown # of arguments
* Fix compilation error of tuning parameter
* In example, use same setting as unit-test
* Remove no-longer used include directive
* Add interface for grouped conv bwd weight
* Add group support for conv bwd weight
* Add grouped conv bwd weight example
* Use group parameter in example
* Rename example folder
* Remove non-grouped version example source files
* Rename device op template
* Add group support to convolution backward weight
* Remove debug messages
* Use smaller group size in example
* Use named variable as loop terminate condition
* Prettify example output message
* Enlarge used grid size
* Allow real grid size exceeds expected grid size
* Rename interface file
* Add client example for grouped conv2d bwd weight
* Fix wrong include directive
* Rename client example folder
* Add reduction across all dims cases.
* host softmax: handle all reduce
* Test cases when reduced dim is not innermost axis.
* Fix syntax.
* Test non innermost dim for fp32 and int8
* Group test suites wrt NumReduceDim.
* Additionally test failing cases.
* Throw error when Rank or NumReduceDims doesn't match arguments.
* Check reducedDims has correct values
* Move don't reuse DeviceReduceMultiblock IsSupportedArgument method.
Instead implement own. (in fact just get rid of one check to enable
reduction across inner dimensions).
* Reorganize unit tests to better cover use scenarios.
* Test input validation
* Test reduction of inner dimensions with custom op instances.
* Refactor fp32 and int8 unit tests.
* Fix FP32 instance template parameters.
* Add more instances.
* Instances with InSrcVectorDim=0.
* Do not initialize and copy data when arg not supported.
* ckProfiler Softmax use instance factory.
* Refactor device softmax IsSupported.
* Additionally add non-polymorphic api functions
* Split softmax instances into multiple files.
* Fix profiler.
* Reorganize tests to reuse profiler and cover edge cases.
* Clang-format
* I8 Softmax instances along with UT.
* Reuse type alias definitions from instance factory header.
* Clean included headers
* Fix variable names.
* Add missing checks in Argument constructor.
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Anthony Chang <ac.chang@outlook.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>
* 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
* 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 b109516455.
* 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>
* 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
* 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
* modify ckProfiler_gemm output
* fix syntax
* change ckProfiler output and return 0
* fix syntax
* output datatype
* fix syntax
* output datatype in another way
* fix syntax
* fix syntax
* test return values of ckProfiler
* add layout info and tests, make sure ckprofiler returns 0
* fix syntax
* change layout output
* fix syntax
* fix syntax again
* update script to process perf results
* rearrange jenkins stages
* fix typo
* add python packages to Docker file
* adding setuptools-rust package
* modify parsing for new test parameters
* test db credentials on jenkins
* fix syntax
* update python script to handle incomplete lines
* ungrade python to 3.8 and write the gemm_params table
* add sqlalchemy package to docker
* move perf data processing to master node
* move the master node inside a steps region
* add new stage for result processing
* move results processing to separate stage
* reduce number of tests to speedup debugging
* pass config to processPerfResults stage
* run script on master in a docker container
* replace show_node_info
* try loading docker on master node again
* use ansible node instead of master
* get rid of pymysql package
* try ssh connection using paramiko
* put back pymysql
* put the perf data processing back on the gpu node
* put back artifact definition
* archive the perf_log before parsing
* clean up jenkinsfile, fix parsing
* fix typo
* enable all perf tests
* put all stages in original order, finalize script
* fix gpu_arch version
* update parsing script
* remove obsolete file causing merge conflict
* 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>
