GitLab

* Add column to image kernel

* Minor fixes for dtypes and client examples

* Disable tests for disabled dtypes

* Disable add instances functions for disabled data types

* Minor stylistic fixes

* Revert "Disable add instances functions for disabled data types"

This reverts commit 728b8695.

* Instances reduction

* Add comments in device_column_to_image_impl

* Update changelog and Copyrights

* Improve changelog

* add gridwise_multi_abd

* move element_op into RunRead

* merge element_wise op with data read

* add multiABD example

* allow packed elementwise_op

* changed example

* clean

* clean

* add is_detected

* fix

* minor fix

* add scaleAdd_vec4 example

---------
Co-authored-by: Jing Zhang <jizha@amd.com>

* Add native conversions

* Add bf8 conversions

* Add grouped conv bwd weight dl instances and new layout

* Add M and N padding

* Remove todo comment

* Enable grouped conv fwd dl k,c=1 generic instance

* Comment fixes

* Refactor f8_t to add bf8_t

* Add check_err impl for f8_t

* Update fp8 test

* Format

* Revert the fix

* Update vector_type implementation

* Add bf8 test

* Add bf8, use BitInt types

* Add bf8 conversion methods

* Update type_convert for fp8/bf8

* Add check_err fp8/bf8 support

* Add subnorm fp8 tests

* Add subnorm bf8 tests

* Fix conversion

* Add bf8 cmake bindings

* Add macros to enable build with disabled fp8/bf8

* Remove is_native method

* Update flag combination for mixed precision instances

* Add more flag checks

* Add another flag to a client example

* Add type traits, decouple f8/bf8 casting

* Clean up

* Decouple fp8 and bf8 flags

* Remove more redundant flags

* Remove leftover comments

* Redesign the DPP8 GEMM kernel to use warp-wise component

* Review: Improve error messages

* Review: Remove unnecessary empty lines

* Review: Fix M, N per thread names

* Review: Rename mfma_input_type to dpp_input_type

* Review: Fix tensor adaptor; remove unnecessary element

* Review: Remove calls to dpp_gemm's MakeCDescriptor

* Review: Add blockwise doc, change function names to include dimension names

* Review: Remove duplicated code; Move Block2CtileMap alias to the top of the file

* Review: Add __restrict__ keywords

* Review: Use MatrixPadder for padding A, B, C matrices

* Review: Remove hardcoded datatypes

* Review: Change names from FloatX to XDataType

* Review: Introduce AK0 and BK0 instead of a single K0

* Review: Remove construction of dpp_datatypes object

* Review: Rename DppInstrRunner to DppLanegroupGemm

* Add maxpool instances

* Rename index pool to max pool.

* Add maxpool bwd bf16 instances

* Add avg pool bwd instances

* Rename avgpool and maxpool to avg_pool3d and max_pool

* Add bf16 pool fwd instances

* Add max pool bwd to ckProfiler

* Add avg pool3d bwd to ckProfiler

* Add avg pool bwd test

* Fix bug of reference pool fwd (dilation)

* Fix bug of max pool bwd  (dilation and initZero)

* Support bf16 compute data type

* Force compute type be f32. Because atomicAdd only support f32

* Add max pool bwd test

* Rename folder

* Rename pool

* Add max pool bwd client example

* Add avg pool bwd client example

* Add missing workspace

* clang format

* Rename macro

* remove useless header

* remove useless layout

* Add s_nops after v_dot to avoid hazard

* Fix builtin for inner_produxt fp16

* Skip inline version to builtin

* Add comments regarding isa

* Fix comment regarding s_nop

* initial stream-k implementation with example

* fix unexpected change in err

* improve a little bit performance by reorganize pipeline.

* improve perf a little bit by swizzle block idx

* add profiler

* update example

* fix spelling

* shrink karg for streamk

* support dynamic buffer using memory coherence glc_slc bit from template

* control memory coherence while construct dynamic buffer

* update reduction for streamk(not ready yet)

* Add template parameter to make_dynamic_buffer to support amd_buffer coherence setting

* fix build issue

* fix several bug

* now result is correct, everything works (but has scratch)

* remove scratch by manually reset coordinate

* update device code

* fix a bug in final reduce

* fix something in example

* update async memset

* fix enum as camel case

* modify coherence enum name

* clean code and use atomic streamk by default

* remove unused var

* throw exception if have empty pointer

* fix format

* fix CI warning

* fix type in init

* modify CI error

* filter out on gfx10+

* restore changed example code

---------
Co-authored-by: Qianfeng Zhang <Qianfeng.Zhang@amd.com>

* 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 d16d00919c43f10759e7b4e4d112125221ed9064.

* 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 fp8 xdl gemm

* Add example

* Use int8 intrinsics for buffer load/store

* Format

* Update cmakelists

* Add basic fp8 definitions and prn-generator

* Format

* Add fp8<->fp32 type_convert

* Format

* Split type_convert and cast_to/from_f8

* Format

* Minor fix

* Minor fix

* Move fp8 utils to a separate header

* Add elementwise ops

* Add fp8_convert_sr

* Format

* Add element op

* Eliminate magic numbers

* Split f8_convert_sr in host and device

* Format

* Add some constexpr

* Add a datatype test

* Format

* Another format

* Add fp8<->fp16 tests

* Update type_converts

* Format

* Add fp16 casting functions

* Format

* Use seed as a runtime arg

* Use element location for PRNG

* Format

* Add fp8<->fp16 to PassThrough element op

* Clean up

* Merge host and device implementations

* Add comments on rounding modes

* Remove leftover code

* Put type_converts into a separate header

* Put random number gen to a separate header

* Rearrange f8_utils' namespaces

* Refactor type_convert.hpp

* Move f8_t definition

* enable gfx941/942 targets

* fix clang format

* fix the cmake logic for multiple targets

* fix cmake syntax for looping over targets

* add gfx941/942 support for gemm_xdl instances

* Fix wrong pointer type

* Rename type trait get_unsigned_int<> to get_carrier<>

* Add 3-bytes carrier type

* Add missing __device__ specifier

* Rename template non-type parameter

* Leave the rest byte uninitialized

* Avoid invoking (host) STL algorithms

* Remove unnecessary 'inline' specifier

* Extract common logic out as helper method

* Hide dummy member function

* Add missing __device__ specifier

* Add overloaded version of __builtin_amdgcn_readfirstlane()

* Remove 'static' specifiers

* Remove more 'static' specifier

* Replace unsigne char by std::byte

* Add 'const' specifier to never changing variable

* Add 'inline' specifier to funcion definition

* Fix wrong boundar calculation logic

* Rename type trait

* Remove std:: qualifier from standard types

* Replace 'size_t' by 'unsigned'

* Use type alias to hint usage

* Replace static_for<> by ordinary 'for' loop

* Rename readfirstlane() to amd_wave_read_first_lane()

* Rename file readfirstlance.hpp as amd_wave_read_first_lane.hpp

* Reorder statements

* fix headers for gpu instances

* remove unused headers

---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* Add TypeConvert class and start refactoring

* Refactor TypeConvert as a struct

* Get back to template functions type_convert

* Add a type_convert_bf16_rtn, set rtz as default

* Clean up

* Add UnaryConvertPrecision struct for high-precision workloads

* Format

* Update type_convert to UnaryConvert on threadwise level

* Update UnaryConvertPrecision

* Format

* Fix chmod

* Add a flag to pick converion method

* Format

* Remove the added flag

* Merge elementwise op with type conversion

* Move type_convert to elemwise op, update the op

* Update type_convert_precision -> bf16_convert_rtn

* Clean up

* Update comments

* Update the CK_WORKAROUND_DENORM_FIX flag handling

* Update the unneeded op to work but warn user

* Remove the message

* Use a PassThrough instead of ConvertBF16RTN to calcaulate reference

* Format

* Add missing include

* enable gfx940

* switch between intrinsic mfma routines on mi100/200 and mi300

* fix mfma_int8 on MI300

* disable 2 int8 examples on MI300

* Update cmake-ck-dev.sh

* restore gitignore file

* modify Jenkinsfile to the internal repo

---------
Co-authored-by: Jing Zhang <jizha@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* Rename to proper naming

* Add example of groupnorm + swish

* Extract duplicate code in example

* Add groupnorm + swish instances

* Ractor instance generation, split into multiple cpp file

* Add external api and client example

* Refine profiler message

* Use ck math version of exp

* Refine problem size in example

* Add host version of exp

* Add type_convert implementations for bf16

* Add the fix for conv_fwd

* Add the fix for conv_bwd_data

* Add the fix for conv_bwd_weight

* Format

* Format

* Another format

* Add a macro to use workaround on MI200 only

* Format

---------
Co-authored-by: Rosty Geyyer <rosty.geyyer@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* Rename file. Prepare to support another activation

* Add comment for quantization

* Extract out_elementop

* Add tanh example

* Add conv + bias + tanh quantization instance

* Add missing parameter

* Refine cmake

* Add external api and client example

* Extract variable in example

* Fix the comment

---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* rtn in ternary way

* Check both flags to preserve NaN

* Format

* Rearrange flag1

* Apply suggestions from code review
Co-authored-by: Ronan Keryell <ronan@keryell.fr>

---------
Co-authored-by: Rosty Geyyer <rosty.geyyer@amd.com>
Co-authored-by: Rostyslav Geyyer <46627076+geyyer@users.noreply.github.com>
Co-authored-by: Ronan Keryell <ronan@keryell.fr>

* Add conv perlayer quantization

* Add gemm_dlops quantization

* Support int8 for innerproduct

* Refine gemm dlops int8 kernel parameter

* Support gfx908(MI100) and gfx90a(MI200)

* clang-format

* Rename example number

* Support different layout for d tensor

* Add conv dlops perchannel quantization example

* Move to example 40

* Extract the common code for different platform (dlops and xdlops)

* Move ot subfolder. Prepare to add other op of quantization

* Refine the quantization instance library

* Add conv dl instances and client example

* Remove unnecessary type

* Add gemm quantization instance

* Add external api and client example

* Refine num_bytes

* Separete different layout to different cpp

* Add more xdl instances

* Revert "Remove unnecessary type"

This reverts commit 820869182f6a8f62b2c9004101ba6bf76b96be14.

* Remove CShuffleDataType in dlops
Let acc and CShuffleDataType be the same in xdlops

---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* Change gridwise gemm mD blockwise gemm to naive

* RRR Gemm fix

* Fix RCR gemm bug

* Isolate wmma instructions

* Update amd_inline_asm.hpp

* Update amd_wmma.hpp

* Update amd_wmma.hpp

* fix syntax and update Jenkinsfile

---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Co-authored-by: illsilin <Illia.Silin@amd.com>

Co-authored-by: zjing14 <zhangjing14@gmail.com>

* Sync the order of type string with template parameter

* Add more instances

* Check the vector size and remove redundant var

* Extract var to static, prepare to separate sweep once kernel

* Separate sweeponce flow and optimize the flow

* 1. Rename AccDatatype in normalization to computeData
2. Rename AccElementwiseOperation to YElementwiseOperation in normalization

* Remove useless code

* Update naive variance kernel

* Refine string

* Fix typo

* Support naive variance for device_normalization

* Check the blocksize

* Share the VGPR of x and y

* Share the VGPR of gamma and beta

* Add more instances

* Support fp16 sqrt for experiment

* Add CHANGELOG

* Fix typo

* clang-format

* 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

* wavelet gemm programming model support for CK

* GEMM pipeline update for wavelet progrmmaing model

* Updated wavelet programming pipeline

* fixes for global-write for math-wave

* fixed bug in global writes

* Updated comments for better readability

* fixed clang format errors

* added block_lds without barrier sync

* clean

* clean

* clean

* clean

* refactor

* 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

* Add comment depicting B2C mapping pattern.

* Formatting & comments.

* Comparison with custom B2C mapping pattern.

* Example for wavelet gemm.

* Add wavelet to Gemm standalone test.

* Remove debug code.

* Remove dangling #endif directive.

Co-authored-by: root <Raman Jana>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Anthony Chang <ac.chang@outlook.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>

* Change to the DeviceReduce base class template to include all problem description information

* Add external api for reduction

* Add client example to test the reduction external api

* Spelling correction

* Re-implement the host_reduction to follow the DeviceReduce base API format

* Change the reduce profiler to call the external API for collecting device instances

* Rename reduce client example directory from 08_reduce to 12_reduce

* Remove (void) before the functional call

* Tiny update in reduce client example

* Tiny update in profile_reduce_impl.hpp

* Rename the reduce client example directory
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>

* wmma_op + unit test

* add arch limitation to wmma test

* change arch limitation

* Refactor + Add all type unit test(int4 compile failed)

* Add f32_16x16x16_bf16 unit test

* tempsave

* tempsave

* tempsave

* runtime bug, cannot find symbol

* workaround for incorrect HIP warpSize return value

* debugging

* tempsave

* Correctness OK, waiting for optimization

* Tidy up + format

* temp save

* temp save, reproduce the v_bfi_b32 issue

* add inline asm for wmmaop test

* tidy up

* clean some debug purpose code

* discard some codes

* clang format

* clang format

* compiler issue fixed + increase tile size

* Let cmath included when compiling host codes in math_v2.hpp

* Remove including of cmath in device_base.hpp and device_permute.hpp

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

* wmma_op + unit test

* add arch limitation to wmma test

* change arch limitation

* Refactor + Add all type unit test(int4 compile failed)

* Add f32_16x16x16_bf16 unit test

* Remote int4 related

* delete deprecated test
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>