Copied from the llvm-project LLVM_PARALLEL_*_JOBS
Concurrent linking can break the build as well as having too many
compile jobs for the avaiable memory. These options allow the user
to fine tune the build to fit within their machines memory
constraints.
An example use on linux is
COMPILE_JOBS=`cat /proc/cpuinfo | grep -m 1 'cpu cores' | awk '{ print $4 }'`
if [ ${COMPILE_JOBS}x = x ]; then
COMPILE_JOBS=1
fi
BUILD_MEM=4
MEM_KB=0
MEM_KB=`cat /proc/meminfo | grep MemTotal | awk '{ print $2 }'`
MEM_MB=`eval "expr ${MEM_KB} / 1024"`
MEM_GB=`eval "expr ${MEM_MB} / 1024"`
COMPILE_JOBS_MEM=`eval "expr 1 + ${MEM_GB} / ${BUILD_MEM}"`
if [ "$COMPILE_JOBS_MEM" -lt "$COMPILE_JOBS" ]; then
COMPILE_JOBS=$COMPILE_JOBS_MEM
fi
LINK_MEM=32
LINK_JOBS=`eval "expr 1 + ${MEM_GB} / ${LINK_MEM}"`
cmake -G Ninja -DCK_PARALLEL_LINK_JOBS=$LINK_JOBS
-DCK_PARALLEL_COMPILE_JOBS=$COMPILE_JOBS
Signed-off-by: Tom Rix <trix@redhat.com>
* disabling some fp8 gemm instances to reduce build time
* disable fp8 gemm instances to reduce build time
* remove the unused variable
* build fp8 gemm default and padded instances separately
* fix include pathsc
Current implementation of IsSupported method in contraction ops does not cover a lot of possible cases in which ScalarPerVector cannot really be used to read A, B or D, or write E.
This PR extends both the regular and multiABD contraction ops with improved checks and also adds new instances with smaller values of ScalarPerVector to support instances that are not supported by other instances.
This PR introduces support for double buffering in LDS into GEMM kernels that use direct load instructions.
Direct loads now use inline asm instead of intrinsics. Usage of intrinsics results in compiler adding additional waitcnt instructions what breaks possible load/compute overlap in case of double buffering.
Usage of inline asm results in the need to use sched_barrier in order to make sure that compiler cannot incorrectly reschedule instructions since it does not know the data dependencies between global->LDS and LDS->registers.
* added working example for 5D input using 1D kernel
* example with 5D input tensor and 2d kernel - not working: issues with arguments
* added updated version of 3d device op - changed descriptors/dims
* added example file to check kernel
* fixed descriptor and isSupportedArgument stride problem
* added and modified kernel for 3d - updated tids/loop
* adding some more 5d example files
* fixed some issues
* changes made for testing
* working version: fixed error in stride for A, still a bit inefficient
* cleaned up formatting/comments
* updating formatting
* more formatting fixes
* fixing cmake, adding back gpu targets in cmake script
* adding client example
* added instances for client example
* fixed errors in client example
* implemented client ex with device_elementwise.hpp and device_elementwise_3d_impl.hpp
* removed extra files
* minor formatting and naming fixes
* adding test files and profiler
* fixing minor error
* minor fix
* removed unneccesary comments, renamed files
* updated instance list for client example, added different layout example
* removing instances
* fixed error in instance generation
* remove comments
* update profiler and client example tensor layouts
* fixed errors in test/profiler
* updated vector dim access to enable vector load
* updated test/profiler files
* updated example with 1d kernel
* updating profiler
* renamed files
* disabled device op for MI300
* skip elementwise_permute_2d on gfx94x
* Update CMakeLists.txt
* fixing CMake - disabling some GPU targets
---------
Co-authored-by: Jing Zhang <jizha@amd.com>
Co-authored-by: Jing Zhang <jizhan@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* spolit the static library into several
* update lib paths and fix client example
* do not use device_mha_operarions for client examples
* use appropriate libs to link to client examples
* remove the gpu/transpose path from the list
* try fixing clinet examples 3,4,9
* add necessary libs for client examples
* fix the layernorm client example
* fix the client examples 23 and 24
* fix typo
* add interface library and refresh clang format
* Add basic support for direct loads from global to LDS
* Clean the code and comments
* Add support for fp16
* Add comments
* Add check for thread cluster lengths
* Align non-direct-load fp16 example
* Small fixes
* Extend IsSupported to check for supported GPU gens
* Build examples only on the supported HW
* Do not throw when instance not supported in 04 example
* Review: Apply review suggestions
* Review: small fix
* Review: small fix
* Introduce multiABD api and deprecate multiD
* Replace multiD with multiABD
* Mark structures as deprecated
* Change doxygen deprecated to note to avoid warnings
* adding files for F32 example
* adding functioning implementation with scalar multiplication and unary operator support
* added fp 16 type check in unary square
* updating scalar multiplication as an operator
* functioning version with scalar operator
* changing strides for col major
* updated column major implementation
* working column major implementation
* cleaned up comments, rearranged/renamed files
* Support multi AB for grouped conv fwd xdl
* Add instances
* Add client example
* Add example
* Add interface test
* Minor fixes
Minor fixes
Minor fixes
* Comment fixes
* Fixes
* Reference fix
* Test xdl fixes
* Improve multi_ab interface test
* added working example for 5D input using 1D kernel
* example with 5D input tensor and 2d kernel - not working: issues with arguments
* added updated version of 3d device op - changed descriptors/dims
* added example file to check kernel
* fixed descriptor and isSupportedArgument stride problem
* added and modified kernel for 3d - updated tids/loop
* adding some more 5d example files
* fixed some issues
* changes made for testing
* working version: fixed error in stride for A, still a bit inefficient
* cleaned up formatting/comments
* updating formatting
* more formatting fixes
* fixing cmake, adding back gpu targets in cmake script
* adding client example
* added instances for client example
* fixed errors in client example
* implemented client ex with device_elementwise.hpp and device_elementwise_3d_impl.hpp
* removed extra files
* minor formatting and naming fixes
* adding test files and profiler
* fixing minor error
* minor fix
* removed unneccesary comments, renamed files
* updated instance list for client example, added different layout example
* removing instances
* fixed error in instance generation
* remove comments
* update profiler and client example tensor layouts
* fixed errors in test/profiler
* updated vector dim access to enable vector load
* updated test/profiler files
* updated example with 1d kernel
* updating profiler
* renamed files
---------
Co-authored-by: Jing Zhang <jizha@amd.com>
* Rename folder
* Add layernorm 4d fwd example
* Rename original layernorm example
* Add layernorm 4d f16 test
* Add layernorm4d_fwd client example
* Support layernorm4D in ckProfiler
* Rename groupnorm to groupnorm fwd in example
* Rename layernorm and group fwd in test
* Rename normalization to normalization_fwd (instances)
* Add fwd to DeviceNormalization
* Rename external api header
* Rename folder, because we can also add bwd in this folder
* Add fwd in layernorm and groupnorm (profiler
* Fix compile error
---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
* add compute type check for fp16 in forward convolution instances
* Add compute type check for default compute types
---------
Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
* Add support for mixed precision in contraction scale and bilinear (#936)
* Extract common functionality to separate files
* Reference contraction: Remove incorrect consts from type_converts
* Reference contraction: Add missing type_convert for dst value
* Reference contraction: Fix incorrect order of B matrix dimensions
* Add support for mixed precision in contraction scale and bilinear
* Move using statements from instances to a common file
* Move using statements from examples to a common file
* Fix the order of B matrix dimensions across examples and profiler
* Fix the computation of error threshold
* Make ComputeDataType an optional argument
* Include possible DataType -> ComputeDataType casting error in the threshold
* Remove commented code
* Make the ComputeDataType an optional argument in instance
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
