Merge branch 'develop' into ck_host_lib

.azuredevops/rocm-ci.yml

@@ -14,6 +14,7 @@ trigger:
   branches:
     include:
     - develop
+    - amd-develop
   paths:
     exclude:
     - .github

.github/CODEOWNERS

-* @junliume @illsilin @carlushuang @aosewski @poyenc @geyyer @bartekxk
+* @junliume @illsilin @carlushuang @qianfengz @aosewski @poyenc @geyyer @bartekxk @andriy-ca @afagaj
 # Documentation files
-docs/ @ROCm/rocm-documentation @junliume @illsilin @carlushuang @aosewski @poyenc @geyyer @bartekxk
-*.md @ROCm/rocm-documentation @junliume @illsilin @carlushuang @aosewski @poyenc @geyyer @bartekxk
-*.rst @ROCm/rocm-documentation @junliume @illsilin @carlushuang @aosewski @poyenc @geyyer @bartekxk
-.readthedocs.yaml @ROCm/rocm-documentation @junliume @illsilin @carlushuang @aosewski @poyenc @geyyer @bartekxk
+docs/ @ROCm/rocm-documentation @junliume @illsilin @carlushuang @qianfengz @aosewski @poyenc @geyyer @bartekxk @andriy-ca @afagaj
+*.md @ROCm/rocm-documentation @junliume @illsilin @carlushuang @qianfengz @aosewski @poyenc @geyyer @bartekxk @andriy-ca @afagaj
+*.rst @ROCm/rocm-documentation @junliume @illsilin @carlushuang @qianfengz @aosewski @poyenc @geyyer @bartekxk @andriy-ca @afagaj
+.readthedocs.yaml @ROCm/rocm-documentation @junliume @illsilin @carlushuang @qianfengz @aosewski @poyenc @geyyer @bartekxk @andriy-ca @afagaj
 # Header directory for Doxygen documentation
-library/include/ @ROCm/rocm-documentation @junliume @illsilin @carlushuang @aosewski @poyenc @geyyer @bartekxk
+library/include/ @ROCm/rocm-documentation @junliume @illsilin @carlushuang @qianfengz @aosewski @poyenc @geyyer @bartekxk @andriy-ca @afagaj

.github/CONTRIBUTING.md

+We'd love for you to contribute to our source code!
+
+Some helpful links:
+
+- [Code of Conduct guidelines](https://www.contributor-covenant.org/version/2/1/code_of_conduct/code_of_conduct.txt)
+- [New issue guidelines](https://github.com/rocm/composable_kernel/blob/develop/.github/ISSUE_TEMPLATE.md)
+- [Submitting a pull request guidelines](https://github.com/rocm/composable_kernel/blob/develop/.github/PULL_REQUEST_TEMPLATE.md)
+- [Maintainers](https://github.com/rocm/composable_kernel/blob/develop/CONTRIBUTORS.md)
+- [General information](https://github.com/rocm/composable_kernel/blob/develop/README.md)
+- [ROCm documentation](https://rocm.docs.amd.com/en/latest/how-to/llm-fine-tuning-optimization/optimizing-with-composable-kernel.html)
\ No newline at end of file

.github/ISSUE_TEMPLATE.md

+When creating an issue, please check if a similar issue already exists.
+
+### When reporting a bug, please include:
+- [ ] A descriptive title
+- [ ] An isolated way to reproduce the behavior (preferably a docker container with a repro)
+- [ ] ROCm version, clang version, Composable Kernel commit pin
+- [ ] Environment variables
+- [ ] The behavior you expect to see, and the behavior you actually see
+
+### When requesting a feature, please include:
+- [ ] A descriptive title
+- [ ] A detailed description of the problem you are trying to solve
+- [ ] An overview of the suggested solution
+- [ ] Explanation why the solution is an improvement
\ No newline at end of file

.github/PULL_REQUEST_TEMPLATE.md

+## Proposed changes
+
+Please describe the motivation behind the pull request, whether it enables a new feature or fixes a bug. If there are associated pull requests or issues, please link them to the pull request.
+
+## Checklist
+
+Please put an `x` into the boxes that apply. You can also fill these out after creating the PR. If you're not sure, please don't hesitate to ask.
+
+- [ ] I have added tests relevant to the introduced functionality, and the unit tests are passing locally
+- [ ] I have added the test to REGRESSION_TESTS list defined at the top of CMakeLists.txt in tests/CMakeLists.txt, **IF** the test takes more than 30 seconds to run.
+- [ ] I have added inline documentation which enables the maintainers with understanding the motivation
+- [ ] I have removed the stale documentation which is no longer relevant after this pull request
+- [ ] (If this change is user-facing) I have added release notes which provide the end users with a brief summary of the improvement from this pull request
+- [ ] I have run `clang-format` on all changed files
+- [ ] Any dependent changes have been merged
+
+## Discussion
+
+If this is a relatively large or complex change, feel free to start a discussion by explaining why you chose the solution you did and what alternatives you considered
+

CMakeLists.txt

@@ -97,11 +97,22 @@ if(DL_KERNELS)
     add_definitions(-DDL_KERNELS)
     set(CK_ENABLE_DL_KERNELS "ON")
 endif()
+if(DPP_KERNELS)
+    add_definitions(-DDPP_KERNELS)
+    set(CK_ENABLE_DPP_KERNELS "ON")
+endif()
 option(CK_USE_CODEGEN "Enable codegen library" OFF)
 if(CK_USE_CODEGEN)
    add_definitions(-DCK_USE_CODEGEN)
 endif()
 
+option(CK_TIME_KERNEL "Enable kernel time tracking" ON)
+if(CK_TIME_KERNEL)
+    add_definitions(-DCK_TIME_KERNEL=1)
+else()
+    add_definitions(-DCK_TIME_KERNEL=0)
+endif()
+
 include(getopt)
 
 # CK version file to record release version as well as git commit hash
@@ -183,18 +194,38 @@ message("Building CK for the following targets: ${SUPPORTED_GPU_TARGETS}")
 if (SUPPORTED_GPU_TARGETS MATCHES "gfx9")
     message("Enabling XDL instances")
     add_definitions(-DCK_USE_XDL)
+    set(CK_USE_XDL "ON")
 endif()
-if (SUPPORTED_GPU_TARGETS MATCHES "gfx94")
-    message("Enabling FP8 gemms in ckProfiler")
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx94" OR SUPPORTED_GPU_TARGETS MATCHES "gfx95")
+    message("Enabling FP8 gemms on native architectures")
     add_definitions(-DCK_USE_GFX94)
+    set(CK_USE_GFX94 "ON")
+endif()
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx95")
+	add_definitions(-DCK_USE_AMD_MFMA_GFX950)
 endif()
 if (SUPPORTED_GPU_TARGETS MATCHES "gfx11" OR SUPPORTED_GPU_TARGETS MATCHES "gfx12")
     message("Enabling WMMA instances")
     add_definitions(-DCK_USE_WMMA)
+    set(CK_USE_WMMA "ON")
 endif()
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx12" OR SUPPORTED_GPU_TARGETS MATCHES "gfx950")
+    add_definitions(-DCK_USE_OCP_FP8)
+    set(CK_USE_OCP_FP8 "ON")
+endif()
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx90a" OR SUPPORTED_GPU_TARGETS MATCHES "gfx94")
+    add_definitions(-DCK_USE_FNUZ_FP8)
+    set(CK_USE_FNUZ_FP8 "ON")
+endif()
+if (SUPPORTED_GPU_TARGETS MATCHES "gfx950")
+    add_definitions(-DCK_USE_NATIVE_MX_SUPPORT)
+    set(CK_USE_NATIVE_MX_SUPPORT "ON")
+endif()
+
 option(CK_USE_FP8_ON_UNSUPPORTED_ARCH "Enable FP8 GEMM instances on older architectures" OFF)
 if(CK_USE_FP8_ON_UNSUPPORTED_ARCH AND (SUPPORTED_GPU_TARGETS MATCHES "gfx90a" OR SUPPORTED_GPU_TARGETS MATCHES "gfx908"))
     add_definitions(-DCK_USE_FP8_ON_UNSUPPORTED_ARCH)
+    set(CK_USE_FP8_ON_UNSUPPORTED_ARCH "ON")
 endif()
 
 # CK config file to record supported datatypes, etc.
@@ -516,7 +547,13 @@ if("${CMAKE_CXX_COMPILER_ID}" STREQUAL "GNU" AND CMAKE_CXX_COMPILER_VERSION VERS
     add_compile_options(-fdiagnostics-color=always)
 endif()
 
+# make check runs the entire set of examples and tests
 add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR})
+# make smoke runs the tests and examples that runs within 30 seconds on gfx90a
+add_custom_target(smoke COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR} -L "SMOKE_TEST")
+# make regression runs the tests and examples that runs for more 30 seconds on gfx90a
+add_custom_target(regression COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR} -L "REGRESSION_TEST")
+
 
 file(GLOB_RECURSE INSTANCE_FILES "${PROJECT_SOURCE_DIR}/*/device_*_instance.cpp")
 file(GLOB dir_list RELATIVE ${PROJECT_SOURCE_DIR}/library/src/tensor_operation_instance/gpu ${PROJECT_SOURCE_DIR}/library/src/tensor_operation_instance/gpu/*)

CONTRIBUTORS.md

+[Back to the main page](./README.md)
 # Composable Kernel Developers and Contributors
 
 This is the list of developers and contributors to Composable Kernel library

Dockerfile

-FROM ubuntu:20.04
+FROM ubuntu:22.04
 ARG DEBIAN_FRONTEND=noninteractive
-ARG ROCMVERSION=6.2
+ARG ROCMVERSION=6.3
 ARG compiler_version=""
 ARG compiler_commit=""
 ARG CK_SCCACHE=""
-
-RUN set -xe
-
 ARG DEB_ROCM_REPO=http://repo.radeon.com/rocm/apt/.apt_$ROCMVERSION/
-RUN useradd -rm -d /home/jenkins -s /bin/bash -u 1004 jenkins
-# Add rocm repository
-RUN chmod 1777 /tmp
-RUN apt-get update
-RUN apt-get install -y --allow-unauthenticated apt-utils wget gnupg2 curl
-
 ENV APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn
-RUN curl -fsSL https://repo.radeon.com/rocm/rocm.gpg.key | gpg --dearmor -o /etc/apt/trusted.gpg.d/rocm-keyring.gpg
 
-RUN if [ "$ROCMVERSION" != "6.3" ]; then \
-        sh -c "wget https://repo.radeon.com/amdgpu-install/$ROCMVERSION/ubuntu/focal/amdgpu-install_6.2.60200-1_all.deb  --no-check-certificate" && \
-        apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ./amdgpu-install_6.2.60200-1_all.deb && \
+# Add rocm repository
+RUN set -xe && \
+    useradd -rm -d /home/jenkins -s /bin/bash -u 1004 jenkins && \
+    apt-get update && apt-get install -y --allow-unauthenticated apt-utils wget gnupg2 curl && \
+    curl -fsSL https://repo.radeon.com/rocm/rocm.gpg.key | gpg --dearmor -o /etc/apt/trusted.gpg.d/rocm-keyring.gpg
+
+RUN if [ "$ROCMVERSION" != "6.4" ]; then \
+        sh -c "wget https://repo.radeon.com/amdgpu-install/$ROCMVERSION/ubuntu/focal/amdgpu-install_6.3.60300-1_all.deb  --no-check-certificate" && \
+        apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ./amdgpu-install_6.3.60300-1_all.deb && \
         wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add - && \
         sh -c "echo deb [arch=amd64 signed-by=/etc/apt/trusted.gpg.d/rocm-keyring.gpg] $DEB_ROCM_REPO focal main > /etc/apt/sources.list.d/rocm.list" && \
         sh -c 'echo deb [arch=amd64 signed-by=/etc/apt/trusted.gpg.d/rocm-keyring.gpg] https://repo.radeon.com/amdgpu/$ROCMVERSION/ubuntu focal main > /etc/apt/sources.list.d/amdgpu.list'; \
-    elif [ "$ROCMVERSION" = "6.3" ] && [ "$compiler_version" = "rc1" ]; then \
-        sh -c "wget http://artifactory-cdn.amd.com/artifactory/list/amdgpu-deb/amdgpu-install-internal_6.3-20.04-1_all.deb --no-check-certificate" && \
-        apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install dialog libpopt0 rsync && DEBIAN_FRONTEND=noninteractive apt-get install ./amdgpu-install-internal_6.3-20.04-1_all.deb && \
-        sh -c 'echo deb [arch=amd64 trusted=yes] http://compute-artifactory.amd.com/artifactory/list/rocm-release-archive-20.04-deb/ 6.3 rel-20 > /etc/apt/sources.list.d/rocm-build.list' && \
-        amdgpu-repo --amdgpu-build=2074281; \
     fi
 
-RUN sh -c "echo deb http://mirrors.kernel.org/ubuntu focal main universe | tee -a /etc/apt/sources.list"
-RUN amdgpu-install -y --usecase=rocm --no-dkms
+RUN sh -c "echo deb http://mirrors.kernel.org/ubuntu focal main universe | tee -a /etc/apt/sources.list" && \
+    amdgpu-install -y --usecase=rocm --no-dkms
 
 ## Sccache binary built from source for ROCm, only install if CK_SCCACHE is defined
 ARG SCCACHE_REPO_URL=http://compute-artifactory.amd.com/artifactory/rocm-generic-experimental/rocm-sccache
@@ -57,6 +48,7 @@ RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-
     libnuma-dev \
     libpthread-stubs0-dev \
     llvm-amdgpu \
+    mpich \
     net-tools \
     pkg-config \
     python \
@@ -72,72 +64,52 @@ RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-
     nano \
     zlib1g-dev \
     zip \
+    libzstd-dev \
     openssh-server \
     clang-format-12 \
     kmod && \
     apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
+    rm -rf /var/lib/apt/lists/* && \
+    rm -rf amdgpu-install* && \
+# Remove unnecessary rocm components that take a lot of space
+    apt-get remove -y rocblas rocfft rocsparse composablekernel-dev hipblaslt
 
-# hipTensor requires rocm-llvm-dev for rocm versions > 6.0.1
-RUN if [ "$ROCMVERSION" = "6.1" ]; then \
-        sh -c "apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated rocm-llvm-dev"; \
-    fi
 # Update the cmake to version 3.27.5
-RUN pip install --upgrade cmake==3.27.5
-
+RUN pip install --upgrade cmake==3.27.5 && \
 #Install latest ccache
-RUN git clone https://github.com/ccache/ccache.git && \
-    cd ccache && mkdir build && cd build && cmake .. && make install
-
+    git clone https://github.com/ccache/ccache.git && \
+    cd ccache && mkdir build && cd build && cmake .. && make install && \
 #Install ninja build tracing tools
-RUN wget -qO /usr/local/bin/ninja.gz https://github.com/ninja-build/ninja/releases/latest/download/ninja-linux.zip
-RUN gunzip /usr/local/bin/ninja.gz
-RUN chmod a+x /usr/local/bin/ninja
-RUN git clone https://github.com/nico/ninjatracing.git
-
+    cd / && \
+    wget -qO /usr/local/bin/ninja.gz https://github.com/ninja-build/ninja/releases/latest/download/ninja-linux.zip && \
+    gunzip /usr/local/bin/ninja.gz && \
+    chmod a+x /usr/local/bin/ninja && \
+    git clone https://github.com/nico/ninjatracing.git && \
 #Install latest cppcheck
-RUN git clone https://github.com/danmar/cppcheck.git && \
-    cd cppcheck && mkdir build && cd build && cmake .. && cmake --build .
-WORKDIR /
-
-# Setup ubsan environment to printstacktrace
-RUN ln -s /usr/bin/llvm-symbolizer-3.8 /usr/local/bin/llvm-symbolizer
-ENV UBSAN_OPTIONS=print_stacktrace=1
-
+    git clone https://github.com/danmar/cppcheck.git && \
+    cd cppcheck && mkdir build && cd build && cmake .. && cmake --build . && \
+    cd / && \
 # Install an init system
-RUN wget https://github.com/Yelp/dumb-init/releases/download/v1.2.0/dumb-init_1.2.0_amd64.deb
-RUN dpkg -i dumb-init_*.deb && rm dumb-init_*.deb
-
-ARG PREFIX=/opt/rocm
+    wget https://github.com/Yelp/dumb-init/releases/download/v1.2.0/dumb-init_1.2.0_amd64.deb && \
+    dpkg -i dumb-init_*.deb && rm dumb-init_*.deb && \
 # Install packages for processing the performance results
-RUN pip3 install --upgrade pip
-RUN pip3 install sqlalchemy==1.4.46
-RUN pip3 install pymysql
-RUN pip3 install pandas==2.0.3
-RUN pip3 install setuptools-rust
-RUN pip3 install sshtunnel==0.4.0
-# Setup ubsan environment to printstacktrace
-ENV UBSAN_OPTIONS=print_stacktrace=1
-
-ENV LC_ALL=C.UTF-8
-ENV LANG=C.UTF-8
-RUN groupadd -f render
-
+    pip3 install --upgrade pip && \
+    pip3 install --upgrade pytest sqlalchemy==2.0.36 pymysql pandas==2.2.3 setuptools-rust setuptools>=75 sshtunnel==0.4.0 && \
+# Add render group
+    groupadd -f render && \
 # Install the new rocm-cmake version
-RUN git clone -b master https://github.com/ROCm/rocm-cmake.git  && \
+    git clone -b master https://github.com/ROCm/rocm-cmake.git  && \
     cd rocm-cmake && mkdir build && cd build && \
     cmake  .. && cmake --build . && cmake --build . --target install
 
 WORKDIR /
-
+# Add alternative compilers, if necessary
 ENV compiler_version=$compiler_version
 ENV compiler_commit=$compiler_commit
-RUN sh -c "echo compiler version = '$compiler_version'"
-RUN sh -c "echo compiler commit = '$compiler_commit'"
-
-ARG DISABLE_CACHE=0
+RUN sh -c "echo compiler version = '$compiler_version'" && \
+    sh -c "echo compiler commit = '$compiler_commit'"
 
-RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd-mainline-open" ] ) && [ "$compiler_commit" = "" ]; then \
+RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd-mainline" ] ) && [ "$compiler_commit" = "" ]; then \
         git clone -b "$compiler_version" https://github.com/ROCm/llvm-project.git && \
         cd llvm-project && mkdir build && cd build && \
         cmake -DCMAKE_INSTALL_PREFIX=/opt/rocm/llvm -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=1 -DLLVM_TARGETS_TO_BUILD="AMDGPU;X86" -DLLVM_ENABLE_PROJECTS="clang;lld" -DLLVM_ENABLE_RUNTIMES="compiler-rt" ../llvm && \
@@ -145,16 +117,10 @@ RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd
     else echo "using the release compiler"; \
     fi
 
-RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd-mainline-open" ] ) && [ "$compiler_commit" != "" ]; then \
+RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd-mainline" ] ) && [ "$compiler_commit" != "" ]; then \
         git clone -b "$compiler_version" https://github.com/ROCm/llvm-project.git && \
         cd llvm-project && git checkout "$compiler_commit" && echo "checking out commit $compiler_commit" && mkdir build && cd build && \
         cmake -DCMAKE_INSTALL_PREFIX=/opt/rocm/llvm -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=1 -DLLVM_TARGETS_TO_BUILD="AMDGPU;X86" -DLLVM_ENABLE_PROJECTS="clang;lld" -DLLVM_ENABLE_RUNTIMES="compiler-rt" ../llvm && \
         make -j 8 ; \
     else echo "using the release compiler"; \
     fi
-
-#clean-up the deb package
-RUN sh -c "rm -rf amdgpu-install*"
-
-#ENV HIP_CLANG_PATH='/llvm-project/build/bin'
-#RUN sh -c "echo HIP_CLANG_PATH = '$HIP_CLANG_PATH'"

Dockerfile.compiler

+ARG BASE_DOCKER="rocm/composable_kernel:ck_ub22.04_rocm6.3"
+FROM $BASE_DOCKER
+ARG compiler_version=""
+ARG compiler_commit=""
+
+# Add alternative compilers, if necessary
+ENV compiler_version=$compiler_version
+ENV compiler_commit=$compiler_commit
+RUN sh -c "echo compiler version = '$compiler_version'" && \
+    sh -c "echo compiler commit = '$compiler_commit'"
+
+RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd-mainline" ] ) && [ "$compiler_commit" = "" ]; then \
+        git clone -b "$compiler_version" https://github.com/ROCm/llvm-project.git && \
+        cd llvm-project && mkdir build && cd build && \
+        cmake -DCMAKE_INSTALL_PREFIX=/opt/rocm/llvm -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=1 -DLLVM_TARGETS_TO_BUILD="AMDGPU;X86" -DLLVM_ENABLE_PROJECTS="clang;lld" -DLLVM_ENABLE_RUNTIMES="compiler-rt" ../llvm && \
+        make -j 16 ; \
+    else echo "using the release compiler"; \
+    fi
+
+RUN if ( [ "$compiler_version" = "amd-staging" ] || [ "$compiler_version" = "amd-mainline" ] ) && [ "$compiler_commit" != "" ]; then \
+        git clone -b "$compiler_version" https://github.com/ROCm/llvm-project.git && \
+        cd llvm-project && git checkout "$compiler_commit" && echo "checking out commit $compiler_commit" && mkdir build && cd build && \
+        cmake -DCMAKE_INSTALL_PREFIX=/opt/rocm/llvm -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=1 -DLLVM_TARGETS_TO_BUILD="AMDGPU;X86" -DLLVM_ENABLE_PROJECTS="clang;lld" -DLLVM_ENABLE_RUNTIMES="compiler-rt" ../llvm && \
+        make -j 16 ; \
+    else echo "using the release compiler"; \
+    fi

Jenkinsfile

@@ -32,38 +32,40 @@ def runShell(String command){
     return (output != "")
 }
 
-def getDockerImageName(){
+def getBaseDockerImageName(){
     def img
     if (params.USE_CUSTOM_DOCKER != ""){
         img = "${params.USE_CUSTOM_DOCKER}"
     }
     else{
-    if (params.ROCMVERSION != "6.3"){
-       if (params.COMPILER_VERSION == "") {
-           img = "${env.CK_DOCKERHUB}:ck_ub20.04_rocm${params.ROCMVERSION}"
-       }
-       else{
-          if (params.COMPILER_COMMIT == ""){
-             img = "${env.CK_DOCKERHUB}:ck_ub20.04_rocm${params.ROCMVERSION}_${params.COMPILER_VERSION}"
+        def ROCM_numeric = "${params.ROCMVERSION}" as float
+        if ( ROCM_numeric < 6.4 ){
+            img = "${env.CK_DOCKERHUB}:ck_ub22.04_rocm${params.ROCMVERSION}"
             }
         else{
-             def commit = "${params.COMPILER_COMMIT}"[0..6]
-             img = "${env.CK_DOCKERHUB}:ck_ub20.04_rocm${params.ROCMVERSION}_${params.COMPILER_VERSION}_${commit}"
+            img = "${env.CK_DOCKERHUB_PRIVATE}:ck_ub22.04_rocm${params.ROCMVERSION}"
             }
         }
+    return img
+}
+
+def getDockerImageName(){
+    def img
+    def base_name = getBaseDockerImageName()
+    if (params.USE_CUSTOM_DOCKER != ""){
+        img = "${params.USE_CUSTOM_DOCKER}"
     }
     else{
        if (params.COMPILER_VERSION == "") {
-           img = "${env.CK_DOCKERHUB_PRIVATE}:ck_ub20.04_rocm${params.ROCMVERSION}"
+           img = "${base_name}"
        }
        else{
           if (params.COMPILER_COMMIT == ""){
-             img = "${env.CK_DOCKERHUB_PRIVATE}:ck_ub20.04_rocm${params.ROCMVERSION}_${params.COMPILER_VERSION}"
+             img = "${base_name}_${params.COMPILER_VERSION}"
           }
           else{
              def commit = "${params.COMPILER_COMMIT}"[0..6]
-             img = "${env.CK_DOCKERHUB_PRIVATE}:ck_ub20.04_rocm${params.ROCMVERSION}_${params.COMPILER_VERSION}_${commit}"
-          }
+             img = "${base_name}_${params.COMPILER_VERSION}_${commit}"
           }
        }
     }
@@ -131,17 +133,21 @@ def buildDocker(install_prefix){
     env.DOCKER_BUILDKIT=1
     checkout scm
     def image_name = getDockerImageName()
+    def base_image_name = getBaseDockerImageName()
     echo "Building Docker for ${image_name}"
-    def dockerArgs = "--build-arg BUILDKIT_INLINE_CACHE=1 --build-arg PREFIX=${install_prefix} --build-arg CK_SCCACHE='${env.CK_SCCACHE}' --build-arg compiler_version='${params.COMPILER_VERSION}' --build-arg compiler_commit='${params.COMPILER_COMMIT}' --build-arg ROCMVERSION='${params.ROCMVERSION}' --build-arg DISABLE_CACHE='git rev-parse ${params.COMPILER_VERSION}' "
-    if(params.COMPILER_VERSION == "amd-staging" || params.COMPILER_VERSION == "amd-mainline-open" || params.COMPILER_COMMIT != ""){
-        dockerArgs = dockerArgs + " --no-cache "
+    def dockerArgs = "--build-arg PREFIX=${install_prefix} --build-arg CK_SCCACHE='${env.CK_SCCACHE}' --build-arg compiler_version='${params.COMPILER_VERSION}' --build-arg compiler_commit='${params.COMPILER_COMMIT}' --build-arg ROCMVERSION='${params.ROCMVERSION}' "
+    if(params.COMPILER_VERSION == "amd-staging" || params.COMPILER_VERSION == "amd-mainline" || params.COMPILER_COMMIT != ""){
+        dockerArgs = dockerArgs + " --no-cache --build-arg BASE_DOCKER='${base_image_name}' -f Dockerfile.compiler . "
+    }
+    else{
+        dockerArgs = dockerArgs + " -f Dockerfile . "
     }
     echo "Build Args: ${dockerArgs}"
     try{
         if(params.BUILD_DOCKER){
             //force building the new docker if that parameter is true
             echo "Building image: ${image_name}"
-            retimage = docker.build("${image_name}", dockerArgs + ' .')
+            retimage = docker.build("${image_name}", dockerArgs)
             withDockerRegistry([ credentialsId: "docker_test_cred", url: "" ]) {
                 retimage.push()
             }
@@ -320,14 +326,38 @@ def cmake_build(Map conf=[:]){
     if (package_build == true && (env.BRANCH_NAME == "develop" || env.BRANCH_NAME == "amd-master")) {
         archiveArtifacts artifacts: "build/*.deb", allowEmptyArchive: true, fingerprint: true
     }
+    //check the node gpu architecture
+    def arch_type = 0
+    sh 'rocminfo | tee rocminfo.log'
+    if ( runShell('grep -n "gfx90a" rocminfo.log') ){
+        arch_type = 1
+    }
+    else if ( runShell('grep -n "gfx942" rocminfo.log') ) {
+        arch_type = 2
+    }
     if (params.RUN_CK_TILE_FMHA_TESTS){
         try{
-            archiveArtifacts "perf_fmha_fwd_*.log"
-            archiveArtifacts "perf_fmha_bwd_*.log"
-            stash name: "perf_fmha_fwd_gfx942.log"
-            stash name: "perf_fmha_bwd_gfx942.log"
-            stash name: "perf_fmha_fwd_gfx90a.log"
-            stash name: "perf_fmha_bwd_gfx90a.log"
+            archiveArtifacts "perf_fmha_*.log"
+            if (arch_type == 1){
+                stash includes: "perf_fmha_**_gfx90a.log", name: "perf_fmha_log_gfx90a"
+            }
+            else if (arch_type == 2){
+                stash includes: "perf_fmha_**_gfx942.log", name: "perf_fmha_log_gfx942"
+            }
+        }
+        catch(Exception err){
+            echo "could not locate the requested artifacts: ${err.getMessage()}. will skip the stashing."
+        }
+    }
+    if (params.RUN_CK_TILE_GEMM_TESTS){
+        try{
+            archiveArtifacts "perf_tile_gemm_*.log"
+            if (arch_type == 1){
+                stash includes: "perf_tile_gemm_**_fp16_gfx90a.log", name: "perf_tile_gemm_log_gfx90a"
+            }
+            else if (arch_type == 2){
+                stash includes: "perf_tile_gemm_**_fp16_gfx942.log", name: "perf_tile_gemm_log_gfx942"
+            }
         }
         catch(Exception err){
             echo "could not locate the requested artifacts: ${err.getMessage()}. will skip the stashing."
@@ -353,12 +383,12 @@ def buildHipClangJob(Map conf=[:]){
         def prefixpath = conf.get("prefixpath", "/opt/rocm")
 
         // Jenkins is complaining about the render group 
-        def dockerOpts="--device=/dev/kfd --device=/dev/dri --group-add video --group-add render --cap-add=SYS_PTRACE --security-opt seccomp=unconfined"
+        def dockerOpts="-u root --device=/dev/kfd --device=/dev/dri --group-add video --group-add render --cap-add=SYS_PTRACE --security-opt seccomp=unconfined"
         if (conf.get("enforce_xnack_on", false)) {
             dockerOpts = dockerOpts + " --env HSA_XNACK=1 "
         }
         def dockerArgs = "--build-arg PREFIX=${prefixpath} --build-arg CK_SCCACHE='${env.CK_SCCACHE}' --build-arg compiler_version='${params.COMPILER_VERSION}' --build-arg compiler_commit='${params.COMPILER_COMMIT}' --build-arg ROCMVERSION='${params.ROCMVERSION}' "
-        if (params.COMPILER_VERSION == "amd-staging" || params.COMPILER_VERSION == "amd-mainline-open" || params.COMPILER_COMMIT != ""){
+        if (params.COMPILER_VERSION == "amd-staging" || params.COMPILER_VERSION == "amd-mainline" || params.COMPILER_COMMIT != ""){
             dockerOpts = dockerOpts + " --env HIP_CLANG_PATH='/llvm-project/build/bin' "
         }
         def video_id = sh(returnStdout: true, script: 'getent group video | cut -d: -f3')
@@ -373,7 +403,7 @@ def buildHipClangJob(Map conf=[:]){
 
         gitStatusWrapper(credentialsId: "${env.ck_git_creds}", gitHubContext: "Jenkins - ${variant}", account: 'ROCm', repo: 'composable_kernel') {
             withDockerContainer(image: image, args: dockerOpts + ' -v=/var/jenkins/:/var/jenkins') {
-                timeout(time: 48, unit: 'HOURS')
+                timeout(time: 20, unit: 'HOURS')
                 {
                     cmake_build(conf)
                 }
@@ -402,128 +432,6 @@ def buildHipClangJobAndReboot(Map conf=[:]){
     }
 }
 
-def runCKProfiler(Map conf=[:]){
-        show_node_info()
-
-        env.HSA_ENABLE_SDMA=0
-        checkout scm
-
-        def image = getDockerImageName()
-        def prefixpath = conf.get("prefixpath", "/opt/rocm")
-
-        // Jenkins is complaining about the render group 
-        def dockerOpts="--device=/dev/kfd --device=/dev/dri --group-add video --group-add render --cap-add=SYS_PTRACE --security-opt seccomp=unconfined"
-        if (conf.get("enforce_xnack_on", false)) {
-            dockerOpts = dockerOpts + " --env HSA_XNACK=1 "
-        }
-        def video_id = sh(returnStdout: true, script: 'getent group video | cut -d: -f3')
-        def render_id = sh(returnStdout: true, script: 'getent group render | cut -d: -f3')
-        dockerOpts = dockerOpts + " --group-add=${video_id} --group-add=${render_id} "
-        echo "Docker flags: ${dockerOpts}"
-
-        def dockerArgs = "--build-arg PREFIX=${prefixpath} --build-arg compiler_version='${params.COMPILER_VERSION}' --build-arg compiler_commit='${params.COMPILER_COMMIT}' --build-arg ROCMVERSION='${params.ROCMVERSION}' "
-
-        def variant = env.STAGE_NAME
-        def retimage
-
-        gitStatusWrapper(credentialsId: "${env.ck_git_creds}", gitHubContext: "Jenkins - ${variant}", account: 'ROCm', repo: 'composable_kernel') {
-            try {
-                (retimage, image) = getDockerImage(conf)
-                withDockerContainer(image: image, args: dockerOpts) {
-                    timeout(time: 5, unit: 'MINUTES'){
-                        sh 'rocminfo | tee rocminfo.log'
-                        if ( !runShell('grep -n "gfx" rocminfo.log') ){
-                            throw new Exception ("GPU not found")
-                        }
-                        else{
-                            echo "GPU is OK"
-                        }
-                    }
-                }
-            }
-            catch (org.jenkinsci.plugins.workflow.steps.FlowInterruptedException e){
-                echo "The job was cancelled or aborted"
-                throw e
-            }
-
-            withDockerContainer(image: image, args: dockerOpts + ' -v=/var/jenkins/:/var/jenkins') {
-                timeout(time: 24, unit: 'HOURS')
-                {
-                    sh """
-                        rm -rf build
-                        mkdir build
-                    """
-                    dir("build"){
-                        unstash 'ckProfiler.tar.gz'
-                        sh 'tar -xvf ckProfiler.tar.gz'
-                    }
-
-					dir("script"){
-                        if (params.RUN_FULL_QA){
-                            sh "./run_full_performance_tests.sh 0 QA_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME}"
-                            archiveArtifacts "perf_gemm.log"
-                            archiveArtifacts "perf_resnet50_N256.log"
-                            archiveArtifacts "perf_resnet50_N4.log"
-                            archiveArtifacts "perf_batched_gemm.log"
-                            archiveArtifacts "perf_grouped_gemm.log"
-                            archiveArtifacts "perf_grouped_conv_fwd.log"
-                            archiveArtifacts "perf_grouped_conv_bwd_data.log"
-                            archiveArtifacts "perf_grouped_conv_bwd_weight.log"
-                            archiveArtifacts "perf_gemm_bilinear.log"
-                            archiveArtifacts "perf_reduction.log"
-                            archiveArtifacts "perf_splitK_gemm.log"
-                            archiveArtifacts "perf_onnx_gemm.log"
-                            archiveArtifacts "perf_mixed_gemm.log"
-                           // stash perf files to master
-                            stash name: "perf_gemm.log"
-                            stash name: "perf_resnet50_N256.log"
-                            stash name: "perf_resnet50_N4.log"
-                            stash name: "perf_batched_gemm.log"
-                            stash name: "perf_grouped_gemm.log"
-                            stash name: "perf_grouped_conv_fwd.log"
-                            stash name: "perf_grouped_conv_bwd_data.log"
-                            stash name: "perf_grouped_conv_bwd_weight.log"
-                            stash name: "perf_gemm_bilinear.log"
-                            stash name: "perf_reduction.log"
-                            stash name: "perf_splitK_gemm.log"
-                            stash name: "perf_onnx_gemm.log"
-                            stash name: "perf_mixed_gemm.log"
-                            //we will process results on the master node
-                        }
-                        else{
-                            sh "./run_performance_tests.sh 0 CI_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME}"
-                            archiveArtifacts "perf_gemm.log"
-                            archiveArtifacts "perf_resnet50_N256.log"
-                            archiveArtifacts "perf_resnet50_N4.log"
-                            // stash perf files to master
-                            stash name: "perf_gemm.log"
-                            stash name: "perf_resnet50_N256.log"
-                            stash name: "perf_resnet50_N4.log"
-                            //we will process the results on the master node
-                        }
-					}
-                }
-            }
-        }
-        return retimage
-}
-
-def runPerfTest(Map conf=[:]){
-    try{
-        runCKProfiler(conf)
-    }
-    catch(e){
-        echo "throwing error exception in performance tests"
-        echo 'Exception occurred: ' + e.toString()
-        throw e
-    }
-    finally{
-        if (!conf.get("no_reboot", false)) {
-            reboot()
-        }
-    }
-}
-
 def Build_CK(Map conf=[:]){
         show_node_info()
 
@@ -544,12 +452,12 @@ def Build_CK(Map conf=[:]){
         def prefixpath = conf.get("prefixpath", "/opt/rocm")
 
         // Jenkins is complaining about the render group 
-        def dockerOpts="--device=/dev/kfd --device=/dev/dri --group-add video --group-add render --cap-add=SYS_PTRACE --security-opt seccomp=unconfined"
+        def dockerOpts="-u root --device=/dev/kfd --device=/dev/dri --group-add video --group-add render --cap-add=SYS_PTRACE --security-opt seccomp=unconfined"
         if (conf.get("enforce_xnack_on", false)) {
             dockerOpts = dockerOpts + " --env HSA_XNACK=1 "
         }
         def dockerArgs = "--build-arg PREFIX=${prefixpath} --build-arg compiler_version='${params.COMPILER_VERSION}' --build-arg compiler_commit='${params.COMPILER_COMMIT}' --build-arg ROCMVERSION='${params.ROCMVERSION}' "
-        if (params.COMPILER_VERSION == "amd-staging" || params.COMPILER_VERSION == "amd-mainline-open" || params.COMPILER_COMMIT != ""){
+        if (params.COMPILER_VERSION == "amd-staging" || params.COMPILER_VERSION == "amd-mainline" || params.COMPILER_COMMIT != ""){
             dockerOpts = dockerOpts + " --env HIP_CLANG_PATH='/llvm-project/build/bin' "
         }
         if(params.BUILD_LEGACY_OS){
@@ -567,7 +475,7 @@ def Build_CK(Map conf=[:]){
             try {
                 (retimage, image) = getDockerImage(conf)
                 withDockerContainer(image: image, args: dockerOpts) {
-                    timeout(time: 5, unit: 'MINUTES'){
+                    timeout(time: 2, unit: 'MINUTES'){
                         sh 'rocminfo | tee rocminfo.log'
                         if ( !runShell('grep -n "gfx" rocminfo.log') ){
                             throw new Exception ("GPU not found")
@@ -583,36 +491,102 @@ def Build_CK(Map conf=[:]){
                 throw e
             }
             withDockerContainer(image: image, args: dockerOpts + ' -v=/var/jenkins/:/var/jenkins') {
-                timeout(time: 24, unit: 'HOURS')
+                timeout(time: 20, unit: 'HOURS')
                 {
                     //check whether to run performance tests on this node
-                    def do_perf_tests = 0
+                    def arch_type = 0
                     sh 'rocminfo | tee rocminfo.log'
-                    if ( runShell('grep -n "gfx1030" rocminfo.log') || runShell('grep -n "gfx1101" rocminfo.log') || runShell('grep -n "gfx1201" rocminfo.log') || runShell('grep -n "gfx942" rocminfo.log') ){
-                        do_perf_tests = 1
-                        echo "Stash profiler and run performance tests"
+                    if ( runShell('grep -n "gfx90a" rocminfo.log') ){
+                        arch_type = 1
+                    }
+                    else if ( runShell('grep -n "gfx942" rocminfo.log') ) {
+                        arch_type = 2
+                    }
+                    else if ( runShell('grep -n "gfx1030" rocminfo.log') ) {
+                        arch_type = 3
+                    }
+                    else if ( runShell('grep -n "gfx1101" rocminfo.log') ) {
+                        arch_type = 4
+                    }
+                    else if ( runShell('grep -n "gfx1201" rocminfo.log') ) {
+                        arch_type = 5
                     }
                     cmake_build(conf)
+                    if ( !params.BUILD_LEGACY_OS && arch_type == 1 ){
+                            echo "Run inductor codegen tests"
+                            sh """
+                                  pip install --verbose .
+                                  pytest python/test/test_gen_instances.py
+                            """
+                    }
                     dir("build"){
-                        //run tests and examples
-                        //sh 'make -j check'
-                        if (params.RUN_PERFORMANCE_TESTS && do_perf_tests == 0 ){
-                            //we only need the ckProfiler to run the performance tests, so we pack and stash it
-                            //do not stash profiler on nodes where we don't need to run performance tests
-                            sh 'tar -zcvf ckProfiler.tar.gz bin/ckProfiler'
-                            stash name: "ckProfiler.tar.gz"
-                        }
-                        if (params.RUN_FULL_QA && do_perf_tests == 0 ){
-                            // build deb packages for all gfx9 targets and prepare to export
+                        if (params.RUN_FULL_QA && arch_type == 1 ){
+                            // build deb packages for all gfx9 targets on gfx90a system and prepare to export
+                            echo "Build ckProfiler package"
                             sh 'make -j package'
                             archiveArtifacts artifacts: 'composablekernel-ckprofiler_*.deb'
-                            archiveArtifacts artifacts: 'composablekernel-tests_*.deb'
                             sh 'mv composablekernel-ckprofiler_*.deb ckprofiler_0.2.0_amd64.deb'
-                            stash name: "ckprofiler_0.2.0_amd64.deb"
+                            stash includes: "ckprofiler_0.2.0_amd64.deb", name: "ckprofiler_0.2.0_amd64.deb"
                         }
                     }
-                    if (params.hipTensor_test && do_perf_tests == 0 ){
-                        //build and test hipTensor
+                    // run performance tests, stash the logs, results will be processed on the master node
+					dir("script"){
+                        if (params.RUN_PERFORMANCE_TESTS){
+                        if (params.RUN_FULL_QA && arch_type == 1){
+                            // run full tests on gfx90a
+                            echo "Run full performance tests"
+                            sh "./run_full_performance_tests.sh 0 QA_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME}"
+                            archiveArtifacts "perf_gemm.log"
+                            archiveArtifacts "perf_resnet50_N256.log"
+                            archiveArtifacts "perf_resnet50_N4.log"
+                            archiveArtifacts "perf_batched_gemm.log"
+                            archiveArtifacts "perf_grouped_gemm.log"
+                            archiveArtifacts "perf_grouped_conv_fwd.log"
+                            archiveArtifacts "perf_grouped_conv_bwd_data.log"
+                            archiveArtifacts "perf_grouped_conv_bwd_weight.log"
+                            archiveArtifacts "perf_gemm_bilinear.log"
+                            archiveArtifacts "perf_reduction.log"
+                            archiveArtifacts "perf_splitK_gemm.log"
+                            archiveArtifacts "perf_onnx_gemm.log"
+                            archiveArtifacts "perf_mixed_gemm.log"
+                            stash includes: "perf_**.log", name: "perf_log"
+                        }
+                        else if ( arch_type == 1 ){
+                            // run standard tests on gfx90a
+                            echo "Run performance tests"
+                            sh "./run_performance_tests.sh 0 CI_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME}"
+                            archiveArtifacts "perf_gemm.log"
+                            archiveArtifacts "perf_onnx_gemm.log"
+                            archiveArtifacts "perf_resnet50_N256.log"
+                            archiveArtifacts "perf_resnet50_N4.log"
+                            stash includes: "perf_**.log", name: "perf_log"
+                        }
+                        // disable performance tests on gfx1030 for now.
+                        //else if ( arch_type == 3){
+                            // run basic tests on gfx1030
+                        //    echo "Run gemm performance tests"
+                        //    sh "./run_gemm_performance_tests.sh 0 CI_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME} gfx10"
+                        //    archiveArtifacts "perf_onnx_gemm_gfx10.log"
+                        //    stash includes: "perf_onnx_gemm_gfx10.log", name: "perf_log_gfx10"
+                        //}
+                        else if ( arch_type == 4){
+                            // run basic tests on gfx11
+                            echo "Run gemm performance tests"
+                            sh "./run_gemm_performance_tests.sh 0 CI_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME} gfx11"
+                            archiveArtifacts "perf_onnx_gemm_gfx11.log"
+                            stash includes: "perf_onnx_gemm_gfx11.log", name: "perf_log_gfx11"
+                        }
+                        else if ( arch_type == 5 ){
+                            // run basic tests on gfx12
+                            echo "Run gemm performance tests"
+                            sh "./run_gemm_performance_tests.sh 0 CI_${params.COMPILER_VERSION} ${env.BRANCH_NAME} ${NODE_NAME} gfx12"
+                            archiveArtifacts "perf_onnx_gemm_gfx12.log"
+                            stash includes: "perf_onnx_gemm_gfx12.log", name: "perf_log_gfx12"
+                        }                        
+                        }
+                    }
+                    if (params.hipTensor_test && arch_type == 1 ){
+                        // build and test hipTensor on gfx90a node
                         sh """#!/bin/bash
                             rm -rf "${params.hipTensor_branch}".zip
                             rm -rf hipTensor-"${params.hipTensor_branch}"
@@ -625,11 +599,9 @@ def Build_CK(Map conf=[:]){
                                 ls -ltr
                                 CC=hipcc CXX=hipcc cmake -Bbuild . -D CMAKE_PREFIX_PATH="${env.WORKSPACE}/install"
                                 cmake --build build -- -j
+                                ctest --test-dir build
                             """
                         }
-                        dir("hipTensor-${params.hipTensor_branch}/build"){
-                            sh 'ctest'
-                        }
                     }
                 }
             }
@@ -679,44 +651,51 @@ def process_results(Map conf=[:]){
     }
 
     withDockerContainer(image: image, args: dockerOpts + ' -v=/var/jenkins/:/var/jenkins') {
-        timeout(time: 1, unit: 'HOURS'){
+        timeout(time: 15, unit: 'MINUTES'){
             try{
                 dir("script"){
                     if (params.RUN_CK_TILE_FMHA_TESTS){
                         try{
-                            unstash "perf_fmha_fwd_gfx942.log"
-                            unstash "perf_fmha_bwd_gfx942.log"
-                            unstash "perf_fmha_fwd_gfx90a.log"
-                            unstash "perf_fmha_bwd_gfx90a.log"
+                            unstash "perf_fmha_log_gfx942"
+                            unstash "perf_fmha_log_gfx90a"
                         }
                         catch(Exception err){
                             echo "could not locate the FMHA performance logs: ${err.getMessage()}."
                         }
                     }
+                    if (params.RUN_CK_TILE_GEMM_TESTS){
+                        try{
+                            unstash "perf_tile_gemm_log_gfx942"
+                            unstash "perf_tile_gemm_log_gfx90a"
+                        }
+                        catch(Exception err){
+                            echo "could not locate the GEMM performance logs: ${err.getMessage()}."
+                        }
+                    }
                     if (params.RUN_FULL_QA){
                         // unstash perf files to master
                         unstash "ckprofiler_0.2.0_amd64.deb"
                         sh "sshpass -p ${env.ck_deb_pw} scp -o StrictHostKeyChecking=no ckprofiler_0.2.0_amd64.deb ${env.ck_deb_user}@${env.ck_deb_ip}:/var/www/html/composable_kernel/"
-                        unstash "perf_gemm.log"
-                        unstash "perf_resnet50_N256.log"
-                        unstash "perf_resnet50_N4.log"
-                        unstash "perf_batched_gemm.log"
-                        unstash "perf_grouped_gemm.log"
-                        unstash "perf_grouped_conv_fwd.log"
-                        unstash "perf_grouped_conv_bwd_data.log"
-                        unstash "perf_grouped_conv_bwd_weight.log"
-                        unstash "perf_gemm_bilinear.log"
-                        unstash "perf_reduction.log"
-                        unstash "perf_splitK_gemm.log"
-                        unstash "perf_onnx_gemm.log"
-                        unstash "perf_mixed_gemm.log"
+                        unstash "perf_log"
+                        try{
+                            unstash "perf_log_gfx11"
+                            unstash "perf_log_gfx12"
+                        }
+                        catch(Exception err){
+                            echo "could not locate the GEMM gfx11/gfx12 performance logs: ${err.getMessage()}."
+                        }
                         sh "./process_qa_data.sh"
                     }
                     else{
                         // unstash perf files to master
-                        unstash "perf_gemm.log"
-                        unstash "perf_resnet50_N256.log"
-                        unstash "perf_resnet50_N4.log"
+                        unstash "perf_log"
+                        try{
+                            unstash "perf_log_gfx11"
+                            unstash "perf_log_gfx12"
+                        }
+                        catch(Exception err){
+                            echo "could not locate the GEMM gfx11/gfx12 performance logs: ${err.getMessage()}."
+                        }
                         sh "./process_perf_data.sh"
                     }
                 }
@@ -734,10 +713,10 @@ def process_results(Map conf=[:]){
 }
 
 //launch develop branch daily at 23:00 UT in FULL_QA mode and at 19:00 UT with latest staging compiler version
-CRON_SETTINGS = BRANCH_NAME == "develop" ? '''0 23 * * * % RUN_FULL_QA=true;ROCMVERSION=6.2;RUN_CK_TILE_FMHA_TESTS=true;RUN_CK_TILE_GEMM_TESTS=true
-                                              0 21 * * * % ROCMVERSION=6.2;hipTensor_test=true;RUN_CODEGEN_TESTS=true
-                                              0 19 * * * % BUILD_DOCKER=true;DL_KERNELS=true;COMPILER_VERSION=amd-staging;BUILD_COMPILER=/llvm-project/build/bin/clang++;BUILD_GFX12=true;USE_SCCACHE=false;NINJA_BUILD_TRACE=true
-                                              0 17 * * * % BUILD_DOCKER=true;DL_KERNELS=true;COMPILER_VERSION=amd-mainline-open;BUILD_COMPILER=/llvm-project/build/bin/clang++;BUILD_GFX12=true;USE_SCCACHE=false;NINJA_BUILD_TRACE=true
+CRON_SETTINGS = BRANCH_NAME == "develop" ? '''0 23 * * * % RUN_FULL_QA=true;ROCMVERSION=6.3;RUN_CK_TILE_FMHA_TESTS=true;RUN_CK_TILE_GEMM_TESTS=true
+                                              0 21 * * * % ROCMVERSION=6.3;hipTensor_test=true;RUN_CODEGEN_TESTS=true
+                                              0 19 * * * % BUILD_DOCKER=true;DL_KERNELS=true;COMPILER_VERSION=amd-staging;BUILD_COMPILER=/llvm-project/build/bin/clang++;USE_SCCACHE=false;NINJA_BUILD_TRACE=true
+                                              0 17 * * * % BUILD_DOCKER=true;DL_KERNELS=true;COMPILER_VERSION=amd-mainline;BUILD_COMPILER=/llvm-project/build/bin/clang++;USE_SCCACHE=false;NINJA_BUILD_TRACE=true
                                               0 15 * * * % BUILD_INSTANCES_ONLY=true;RUN_PERFORMANCE_TESTS=false;USE_SCCACHE=false
                                               0 13 * * * % BUILD_LEGACY_OS=true''' : ""
 
@@ -760,12 +739,12 @@ pipeline {
             description: 'If you want to use a custom docker image, please specify it here (default: leave blank).')
         string(
             name: 'ROCMVERSION', 
-            defaultValue: '6.2', 
-            description: 'Specify which ROCM version to use: 6.2 (default).')
+            defaultValue: '6.3',
+            description: 'Specify which ROCM version to use: 6.3 (default).')
         string(
             name: 'COMPILER_VERSION', 
             defaultValue: '', 
-            description: 'Specify which version of compiler to use: release, amd-staging, amd-mainline-open, or leave blank (default).')
+            description: 'Specify which version of compiler to use: release, amd-staging, amd-mainline, or leave blank (default).')
         string(
             name: 'COMPILER_COMMIT', 
             defaultValue: '', 
@@ -816,16 +795,16 @@ pipeline {
             description: "Run the ck_tile FMHA tests (default: OFF)")
         booleanParam(
             name: "RUN_CK_TILE_GEMM_TESTS",
-            defaultValue: false,
-            description: "Run the ck_tile GEMM tests (default: OFF)")
+            defaultValue: true,
+            description: "Run the ck_tile GEMM tests (default: ON)")
         booleanParam(
             name: "BUILD_INSTANCES_ONLY",
             defaultValue: false,
             description: "Test building instances for various architectures simultaneously (default: OFF)")
         booleanParam(
             name: "BUILD_GFX12",
-            defaultValue: false,
-            description: "Build CK and run tests on gfx12 (default: OFF)")
+            defaultValue: true,
+            description: "Build CK and run tests on gfx12 (default: ON)")
         booleanParam(
             name: "NINJA_BUILD_TRACE",
             defaultValue: false,
@@ -1019,7 +998,7 @@ pipeline {
                     environment{
                         setup_args = "NO_CK_BUILD"
                         execute_args = """ ../script/cmake-ck-dev.sh  ../ gfx90a && \
-                                           make -j64 tile_example_gemm_basic && \
+                                           make -j64 tile_example_gemm_basic tile_example_gemm_universal && \
                                            cd ../ &&
                                            example/ck_tile/03_gemm/script/run_full_test.sh "CI_${params.COMPILER_VERSION}" "${env.BRANCH_NAME}" "${NODE_NAME}" gfx90a """
                     }
@@ -1038,7 +1017,7 @@ pipeline {
                     environment{
                         setup_args = "NO_CK_BUILD"
                         execute_args = """ ../script/cmake-ck-dev.sh  ../ gfx942 && \
-                                           make -j64 tile_example_gemm_basic && \
+                                           make -j64 tile_example_gemm_basic tile_example_gemm_universal && \
                                            cd ../ &&
                                            example/ck_tile/03_gemm/script/run_full_test.sh "CI_${params.COMPILER_VERSION}" "${env.BRANCH_NAME}" "${NODE_NAME}" gfx942 """
                     }
@@ -1235,29 +1214,6 @@ pipeline {
                 }
             }
         }
-
-        stage("Performance Tests")
-        {
-            parallel
-            {
-                stage("Run ckProfiler: gfx90a")
-                {
-                    when {
-                        beforeAgent true
-                        expression { params.RUN_PERFORMANCE_TESTS.toBoolean() && !params.BUILD_LEGACY_OS.toBoolean() }
-                    }
-                    options { retry(1) }
-                    agent{ label rocmnode("gfx90a")}
-                    environment{
-                        setup_args = "NO_CK_BUILD"
-                    }
-                    steps{
-                        runPerfTest(setup_args:setup_args, config_targets: "ckProfiler", no_reboot:true, build_type: 'Release')
-                        cleanWs()
-                    }
-                }
-            }
-        }
         stage("Process Performance Test Results")
         {
             parallel

LICENSE

@@ -7,7 +7,7 @@ Copyright (c) 2020     , Advanced Micro Devices, Inc. (Xiaoyan Zhou)
 Copyright (c) 2021-2022, Advanced Micro Devices, Inc. (Jianfeng Yan)
 
 SPDX-License-Identifier: MIT
-Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -26,23 +26,15 @@ The current CK library is structured into four layers:
 
 ## General information
 
-To build our documentation locally, use the following code:
-
-``` bash
-cd docs
-pip3 install -r sphinx/requirements.txt
-python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
-```
-
-You can find a list of our developers and contributors on our [Contributors](/CONTRIBUTORS.md) page.
-
-```note
-If you use CK, cite us as follows:
-
-* [Realizing Tensor Operators Using Coordinate Transformations and Tile Based Programming](???):
-  This paper will be available on arXiv soon.
-* [CITATION.cff](/CITATION.cff)
-```
+* [CK supported operations](include/ck/README.md)
+* [CK Tile supported operations](include/ck_tile/README.md)
+* [CK wrapper](client_example/25_wrapper/README.md)
+* [CK codegen](codegen/README.md)
+* [CK profiler](profiler/README.md)
+* [Examples (Custom use of CK supported operations)](example/README.md)
+* [Client examples (Use of CK supported operations with instance factory)](client_example/README.md)
+* [Terminology](/TERMINOLOGY.md)
+* [Contributors](/CONTRIBUTORS.md)
 
 CK is released under the **[MIT license](/LICENSE)**.
 
@@ -129,6 +121,15 @@ Docker images are available on [DockerHub](https://hub.docker.com/r/rocm/composa
 
     You can find instructions for running each individual example in [example](/example).
 
+* Build and run smoke/regression examples and tests:
+
+    ```bash
+    make -j smoke # tests and examples that run for < 30 seconds each
+    ```
+     ```bash
+    make -j regression # tests and examples that run for >= 30 seconds each
+    ```
+
 * Build ckProfiler:
 
     ```bash
@@ -137,6 +138,14 @@ Docker images are available on [DockerHub](https://hub.docker.com/r/rocm/composa
 
     You can find instructions for running ckProfiler in [profiler](/profiler).
 
+* Build our documentation locally:
+
+    ``` bash
+    cd docs
+    pip3 install -r sphinx/requirements.txt
+    python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
+    ```
+
 Note the `-j` option for building with multiple threads in parallel, which speeds up the build significantly.
 However, `-j` launches unlimited number of threads, which can cause the build to run out of memory and
 crash. On average, you should expect each thread to use ~2Gb of RAM.
@@ -153,9 +162,11 @@ Additional cmake flags can be used to significantly speed-up the build:
   `batched_gemm_multi_d_dl`. These instances are useful on architectures like the NAVI2x, as most
   other platforms have faster instances, such as `xdl` or `wmma`, available.
 
+* `DPP_KERNELS` (default is OFF) must be set to ON in order to build instances, such as `gemm_dpp`. 
+  These instances are useful on architectures like the NAVI2x, as most other platforms have faster instances, such as `xdl` or `wmma`, available.
+
 * `CK_USE_FP8_ON_UNSUPPORTED_ARCH` (default is OFF) must be set to ON in order to build instances,
-  such as `gemm_universal` and `gemm_multiply_multiply` for fp8 data type for GPU targets which do not
-  have native support for fp8 data type, such as gfx908 or gfx90a. These instances are useful on
+  such as `gemm_universal`, `gemm_universal_streamk` and `gemm_multiply_multiply` for fp8 data type for GPU targets which do not  have native support for fp8 data type, such as gfx908 or gfx90a. These instances are useful on
   architectures like the MI100/MI200 for the functional support only.
 
 ## Using sccache for building

TERMINOLOGY.md

+[Back to the main page](./README.md)
+# Composable Kernel terminology
\ No newline at end of file

client_example/01_gemm/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel GEMM
+
+## GEMM
+General matrix multiplications operation. In CK GEMM operation is called as `DeviceGemm` and requires following types as template parameters:
+
+* **ALayout** - A matrix layout (RowMajor/ColumnMajor).
+* **BLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **CLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **ADataType** - A matrix data type.
+* **BDataType** - B matrix data type.
+* **CDataType** - B matrix data type.
+* **AElementwiseOperation** - Fused operation on tensor A before GEMM.
+* **BElementwiseOperation** - Fused operation on tensor B before GEMM.
+* **CElementwiseOperation** - Fused operation on tensor C after GEMM.
+
+For matrices with large K dimension `DeviceGemmSplitK` implementation is available. This implementation allows user to split K dimension between work groups. This implementation uses `AtomicAdd` operation on global memory, thus need to zero-out output buffer for correct results.
+
+For fused operations with additional tensor there are `DeviceGemmMultipleABD` or `DeviceGemmMultipleD` operation which require following parameters:
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **DsDataType** - data types for additional tensors for fused operations.
+
+For `DeviceGemmMultipleABD` **ALayout**, **BLayout**, **ADataType** and **BDataType** user should pass a tuple.
+
+List of the device operations in CK:
+
+* **DeviceGemmDl** - Device operation with DL instructions.
+* **DeviceGemmDpp** - Device operation with DL instructions with DPP instructions during data load.
+* **DeviceGemmWmma_CShuffle** - Device operation with WMMA instructions with CShuffle optimization for more optimized data store.
+* **DeviceGemm_Xdl_CShuffle_LdsDirectLoad** - Device operation with XDL instructions and CShuffle optimization for more optimized data store and direct load from global memory to shared memory.
+* **DeviceGemm_Xdl_CShuffle** - Device operation with XDL instructions with CShuffle optimization for more optimized data store.
+* **DeviceGemm_Xdl_CShuffleV2** - Device operation with XDL instructions with CShuffle optimization for more optimized data store. GEMM pipeline has been optimized compared to **DeviceGemm_Xdl_CShuffle**.
+* **DeviceGemmXdlSkipBLds** - Device operation with XDL instructions. Load to shared memory has been skiped for B matrix.
+* **DeviceGemm_Xdl_WaveletModel_CShuffle** - Device operation with XDL instructions with CShuffle optimization for more optimized data store. Producer and consumer scheme cooperation between waves in workgroup.
+* **DeviceGemmXdl** - Device operation with XDL instructions.
+
+Table of supported cases by instance factory with XDL instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✓|
+|fp16|✓|
+|fp32|✓|
+|int8|✓|
+|fp8 |✓|
+
+Table of supported cases by instance factory with WMMA instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✓|
+|fp16|✓|
+|fp32|✗|
+|int8|✓|
+|fp8 |✗|
+
+Table of supported cases by instance factory with DL instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✗|
+|fp16|✓|
+|fp32|✓|
+|int8|✓|
+|fp8 |✗|
+
+Table of supported cases by instance factory with fused output elementwise operation:
+
+* **B Matrix Multiply + Add + Gelu** - bf16 (int8 for B matrix)
+* **B Matrix Multiply + Add** - bf16 (int8 for B matrix)
+* **B Matrix Multiply + Gelu** - bf16 (int8 for B matrix)
+* **B Matrix Multiply** - bf16 (int8 for B matrix)
+
+* **Add + Add + Gelu** - fp16
+* **Add + Gelu** - fp16, bf16 (int8 for B matrix) for Row/Column/Row
+* **Multiply** - fp16
+* **Add + Multiply** - fp16
+* **Add + Relu** - fp16 (int8 for B matrix)  for Row/Column/Row, bf16 (int8 for B matrix) for Row/Column/Row
+* **Add + Silu** - fp16 (int8 for B matrix)  for Row/Column/Row, bf16 (int8 for B matrix) for Row/Column/Row
+* **Add** - fp16 (int8 for B matrix)  for Row/Column/Row, bf16 (int8 for B matrix) for Row/Column/Row
+* **Bilinear** - fp16, int8
+* **Gelu** - fp16
+* **Multiply + Add** - fp16 for Row/Column/Row and Row/Row/Row, fp16 (int8 for B matrix, fp32 for Bias) for Row/Column/Row and Row/Row/Row, 
+* **Quantization** - int8
+
+## GEMM V2 (Universal GEMM)
+General matrix multiplications operation optimized for MI300 series. Operation is called as `DeviceGemmV2` and requires following types as template parameters:
+
+* **ALayout** - A matrix layout (RowMajor/ColumnMajor).
+* **BLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **CLayout** - B matrix layout (RowMajor/ColumnMajor).
+* **ADataType** - A matrix data type.
+* **BDataType** - B matrix data type.
+* **CDataType** - B matrix data type.
+* **AElementwiseOperation** - Fused operation on tensor A before GEMM.
+* **BElementwiseOperation** - Fused operation on tensor B before GEMM.
+* **CElementwiseOperation** - Fused operation on tensor C after GEMM.
+
+This implementation allows user to split K dimension between work groups. This implementation requires AtomicAdd operation on global memory (output buffer must be set to zeroes if splitK parameter is larger than one).
+
+List of the device operations for in CK:
+
+* **DeviceGemm_Xdl_CShuffleV3** - Device operation with XDL instructions with CShuffle optimization for more optimized data store.
+* **DeviceGemm_Xdl_CShuffleV3R1** - Device operation with XDL instructions with CShuffle optimization for more optimized data store. This implementation perform reduction on splitted K dimension after GEMM instead of AtomicAdd instruction. 
+
+Table of supported cases by instance factory with XDL instruction for Row/Row/Row, Row/Column/Row, Column/Row/Row or Column/Column/Row:
+
+|       |Is supported|
+|-------|---|
+|bf16|✓|
+|fp16|✓|
+|fp32|✗|
+|int8|✗|
+|fp8 (C bf16)|✓|
+|fp16 (A fp8)|✓|
+|fp16 (B fp8)|✓|
+
+## Others
+
+* **DeviceGemm_dequantB** - GEMM with dequantization (implemented with WMMA instructions).
+* **DeviceGemmMultipleD_ABScale** - GEMM with scale for A and B matrix.
+* **DeviceGemmMultipleDLayernorm** - GEMM fused with layernorm.
+* **DeviceGemmMultipleDMultipleR** - GEMM fused with reductions and custom global reductions operators.
+* **DeviceGemmReduce** - GEMM fused with reduction.
+* **DeviceGemm_Streamk_V2** - GEMM stream K implementation. Implementation allows to use reduction instead of AtomicAdd.
+* **DeviceGemmStreamK** - GEMM stream K implementation using AtomicAdd.

client_example/07_grouped_convnd_fwd/CMakeLists.txt

@@ -22,4 +22,7 @@ if(GPU_TARGETS MATCHES "gfx9")
         add_executable(client_grouped_conv3d_fwd_bf8_fp8 grouped_conv3d_fwd_bf8_fp8.cpp)
         target_link_libraries(client_grouped_conv3d_fwd_bf8_fp8 PRIVATE composable_kernel::device_conv_operations)
     endif()
+
+    add_executable(grouped_conv2d_fwd_ngchw grouped_conv2d_fwd_ngchw.cpp)
+    target_link_libraries(grouped_conv2d_fwd_ngchw PRIVATE composable_kernel::device_conv_operations)
 endif()

client_example/07_grouped_convnd_fwd/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel Grouped Convolution
+
+## Grouped Convolution Forward
+Grouped convolution operation for 1D, 2D or 3D spatial dimensions. Convolution utilizes GEMM kernel after tensor coordinate transform. In CK Grouped Convolution Forward operation is called as `DeviceGroupedConvFwdMultipleABD` and requires following types as template parameters:
+
+* **NumDimSpatial** - number of spatial dimensions (1D, 2D, 3D).
+* **InLayout** - input layout (NHWGC, GNHWC, NGCHW).
+* **WeiLayout** - weight layout (GKYXC).
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **OutLayout** - output layout (NHWGK, GNHWK, NGKHW).
+* **ADataType** - input data type. Pass tuple if there is fused operation with input.
+* **BDataType** - weight data type. Pass tuple if there is fused operation with weight.
+* **DsDataType** - data types for additional tensors for fused operations.
+* **EDataType** - Output data type.
+* **AElementwiseOperation** - fused operation on tensor A (input).
+* **BElementwiseOperation** - fused operation on tensor B (weight).
+* **CDEElementwiseOperation** - fused operation on tensor C (output).
+* **AComputeType** - compute data type of tensor A for mfma instruction (ADataType by default).
+* **BComputeType** - compute data type of tensor B for mfma instruction (AComputeType by default).
+
+Grouped convolution forward support tensors larger than 2GB.
+
+List of the device operations for grouped convolution forward in CK:
+
+* **DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3** - Device operation with XDL instructions. Optimized for AMD Instinct MI300 series.
+* **DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle** - Device operation with XDL instructions and support of fused operations to input, weight and output.
+* **DeviceGroupedConvFwdMultipleD_Wmma_CShuffle** - Device operation with WMMA instructions.
+* **DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK** - Device operation with DL instructions.
+
+Table of supported cases by instance factory with XDL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16 |2D, 3D|2D|1D, 2D, 3D|
+|fp16 |2D, 3D|2D|1D, 2D, 3D|
+|fp32 |2D, 3D|2D|1D, 2D, 3D|
+|int8 |2D, 3D|2D|1D, 3D|
+|fp8  |3D|✗|✗|
+|bf8  |3D|✗|✗|
+
+Table of supported cases by instance factory with WMMA instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|fp16 |2D, 3D|✗|2D, 3D|
+|int8 |2D, 3D|✗|2D, 3D|
+
+Table of supported cases by instance factory with DL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16 |✗|✗|2D|
+|fp16 |✗|✗|2D|
+|fp32 |✗|✗|2D|
+|int8 |✗|✗|2D|
+
+Table of supported cases by instance factory with fused elementwise operation:
+
+* **Dynamic elementwise operation** - 2D/3D, NHWGC, bf16/fp16/fp32/int8
+* **Bilinear** - 3D, NHWGC, bf16/fp16/fp32/int8
+* **ConvInvScale** - 3D, NHWGC, fp8
+* **ConvScale** - 3D, NHWGC, fp8/bf8
+* **ConvScale + Add** - 3D, NHWGC, fp8
+* **ConvScale + Relu** - 3D, NHWGC, fp8
+* **Scale** - 3D, NHWGC, bf16/fp16/fp32/int8
+* **Scale + Add (for A and B)** - 3D, NHWGC, bf16/fp16/fp32/int8
+* **Scale + Add + Scale + Add + Relu** - 3D, NHWGC, bf16/fp16/fp32/int8

client_example/07_grouped_convnd_fwd/grouped_conv2d_fwd_ngchw.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <tuple>
+#include <cstdlib>
+#include <iomanip>
+#include <iostream>
+#include <iterator>
+#include <numeric>
+#include <vector>
+
+#include "ck/utility/data_type.hpp"
+#include "ck/utility/tuple.hpp"
+#include "ck/ck.hpp"
+#include "ck/library/tensor_operation_instance/gpu/grouped_convolution_forward.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+
+using InDataType  = ck::half_t;
+using WeiDataType = ck::half_t;
+using OutDataType = ck::half_t;
+// Use std tuple instead of ck tuple to avoid clang
+// implicit instantiation of undefined template error.
+using DDataTypes = std::tuple<ck::half_t>;
+
+using InLayout    = ck::tensor_layout::convolution::NGCHW;
+using WeiLayout   = ck::tensor_layout::convolution::GKYXC;
+using OutLayout   = ck::tensor_layout::convolution::NGKHW;
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+static constexpr ck::index_t NumDimSpatial = 2;
+static constexpr ck::index_t G             = 32;
+static constexpr ck::index_t N             = 64; // batch size
+static constexpr ck::index_t K             = 64; // output channel
+static constexpr ck::index_t C             = 32; // input channel (per group)
+static constexpr ck::index_t Y             = 3;  // filter H
+static constexpr ck::index_t X             = 3;  // filter W
+static constexpr ck::index_t Hi            = 14; // input H
+static constexpr ck::index_t Wi            = 14; // input W
+static constexpr ck::index_t Ho            = 14; // output H
+static constexpr ck::index_t Wo            = 14; // output W
+
+struct SimpleDeviceMem
+{
+    SimpleDeviceMem() = delete;
+
+    SimpleDeviceMem(std::size_t mem_size) : p_mem_{}
+    {
+        (void)hipMalloc(static_cast<void**>(&p_mem_), mem_size);
+    }
+
+    void* GetDeviceBuffer() { return p_mem_; }
+
+    ~SimpleDeviceMem() { (void)hipFree(p_mem_); }
+
+    void* p_mem_;
+};
+
+int execute_conv_fwd()
+{
+    std::array<ck::index_t, 5> in_lengths{G, N, C, Hi, Wi};
+    std::array<ck::index_t, 5> in_strides{C * Hi * Wi, G * C * Hi * Wi, Hi * Wi, Wi, 1};
+    std::array<ck::index_t, 5> wei_lengths{G, K, C, Y, X};
+    std::array<ck::index_t, 5> wei_strides{K * Y * X * C, Y * X * C, 1, X * C, C};
+    std::array<ck::index_t, 5> out_lengths{G, N, K, Ho, Wo};
+    std::array<ck::index_t, 5> out_strides{K * Ho * Wo, G * K * Ho * Wo, Ho * Wo, Wo, 1};
+
+    std::array<ck::index_t, NumDimSpatial> filter_strides{1, 1};
+    std::array<ck::index_t, NumDimSpatial> filter_dilations{1, 1};
+    std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1};
+    std::array<ck::index_t, NumDimSpatial> input_right_pads{1, 1};
+
+    SimpleDeviceMem in(sizeof(InDataType) * N * Hi * Wi * G * C);
+    SimpleDeviceMem wei(sizeof(WeiDataType) * G * K * Y * X * C);
+    SimpleDeviceMem out(sizeof(OutDataType) * N * Ho * Wo * G * K);
+
+    using DeviceOp = ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD<NumDimSpatial,
+                                                                                   InLayout,
+                                                                                   WeiLayout,
+                                                                                   ck::Tuple<>,
+                                                                                   OutLayout,
+                                                                                   InDataType,
+                                                                                   WeiDataType,
+                                                                                   ck::Tuple<>,
+                                                                                   OutDataType,
+                                                                                   PassThrough,
+                                                                                   PassThrough,
+                                                                                   PassThrough>;
+
+    // get device op instances
+    const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
+        DeviceOp>::GetInstances();
+
+    std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
+
+    std::string best_op_name;
+    int best_op_id        = -1;
+    float best_avg_time   = std::numeric_limits<float>::max();
+    float best_gb_per_sec = 0;
+    float best_tflops     = 0;
+
+    // profile device operation instances
+    std::cout << "Run all instances and do timing" << std::endl;
+
+    for(int i = 0; i < op_ptrs.size(); ++i)
+    {
+        auto& op_ptr        = op_ptrs[i];
+        auto argument_ptr   = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
+                                                        wei.GetDeviceBuffer(),
+                                                        {},
+                                                        out.GetDeviceBuffer(),
+                                                        in_lengths,
+                                                        in_strides,
+                                                        wei_lengths,
+                                                        wei_strides,
+                                                        {},
+                                                        {},
+                                                        out_lengths,
+                                                        out_strides,
+                                                        filter_strides,
+                                                        filter_dilations,
+                                                        input_left_pads,
+                                                        input_right_pads,
+                                                        PassThrough{},
+                                                        PassThrough{},
+                                                        PassThrough{});
+        auto invoker_ptr    = op_ptr->MakeInvokerPointer();
+        std::string op_name = op_ptr->GetTypeString();
+
+        // workspace_sz will be equal to 0 for other layout than NGCHW
+        const std::size_t workspace_sz = op_ptr->GetWorkSpaceSize(argument_ptr.get());
+        SimpleDeviceMem workspace_dev(workspace_sz);
+        op_ptr->SetWorkSpacePointer(argument_ptr.get(), workspace_dev.GetDeviceBuffer());
+
+        if(op_ptr->IsSupportedArgument(argument_ptr.get()))
+        {
+            float avg_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});
+
+            std::size_t flop =
+                std::size_t(2) * G * N * K * C * Ho * Wo * Y * X + 3 * N * Ho * Wo * G * K;
+            std::size_t num_bytes = sizeof(InDataType) * N * Hi * Wi * G * C +
+                                    sizeof(WeiDataType) * G * K * Y * X * C +
+                                    sizeof(OutDataType) * 2 * N * Ho * Wo * G * K;
+
+            float tflops     = static_cast<float>(flop) / 1.E9 / avg_time;
+            float gb_per_sec = num_bytes / 1.E6 / avg_time;
+
+            std::cout << "Perf: " << std::setw(10) << avg_time << " ms, " << tflops << " TFlops, "
+                      << gb_per_sec << " GB/s, " << op_name << std::endl;
+
+            if(tflops > best_tflops)
+            {
+                best_op_id      = i;
+                best_op_name    = op_name;
+                best_avg_time   = avg_time;
+                best_gb_per_sec = gb_per_sec;
+                best_tflops     = tflops;
+            }
+        }
+        else
+        {
+            std::cerr << op_name << " does not support this problem" << std::endl;
+        }
+    }
+
+    if(best_op_id < 0)
+    {
+        std::cerr << "no suitable instance" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
+              << " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
+
+    // run the best intance
+    {
+        auto& op_ptr = op_ptrs[best_op_id];
+        std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
+                  << std::endl;
+        auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
+                                                        wei.GetDeviceBuffer(),
+                                                        {},
+                                                        out.GetDeviceBuffer(),
+                                                        in_lengths,
+                                                        in_strides,
+                                                        wei_lengths,
+                                                        wei_strides,
+                                                        {},
+                                                        {},
+                                                        out_lengths,
+                                                        out_strides,
+                                                        filter_strides,
+                                                        filter_dilations,
+                                                        input_left_pads,
+                                                        input_right_pads,
+                                                        PassThrough{},
+                                                        PassThrough{},
+                                                        PassThrough{});
+
+        const std::size_t workspace_sz = op_ptr->GetWorkSpaceSize(argument_ptr.get());
+        SimpleDeviceMem workspace_dev(workspace_sz);
+        op_ptr->SetWorkSpacePointer(argument_ptr.get(), workspace_dev.GetDeviceBuffer());
+
+        auto invoker_ptr = op_ptr->MakeInvokerPointer();
+
+        if(op_ptr->IsSupportedArgument(argument_ptr.get()))
+        {
+            invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
+        }
+
+        std::cout << "Done" << std::endl;
+    }
+    return 0;
+}
+
+int main() { return execute_conv_fwd(); }

client_example/10_grouped_convnd_bwd_data/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel Grouped Convolution
+
+## Grouped Convolution Backward Data
+
+Grouped convolution operation for 1D, 2D or 3D spatial dimensions. Convolution utilizes GEMM kernel after tensor coordinate transform. In CK Grouped Convolution Backward Data operation is called as `DeviceGroupedConvBwdDataMultipleD` and requires following types as template parameters:
+
+* **NumDimSpatial** - number of spatial dimensions (1D, 2D, 3D).
+* **ALayout** - output layout (NHWGK, GNHWK, NGKHW).
+* **BLayout** - weight layout (GKYXC).
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **ELayout** - input layout (NHWGC, GNHWC, NGCHW).
+* **ADataType** - output data type.
+* **BDataType** - weight data type.
+* **DsDataType** - data types for additional tensors for fused operations.
+* **EDataType** - input data type.
+* **AElementwiseOperation** - fused operation on tensor A (output).
+* **BElementwiseOperation** - fused operation on tensor B (weight).
+* **CDEElementwiseOperation** - fused operation on tensor C (input).
+* **AComputeType** - compute data type of tensor A for mfma instruction (ADataType by default).
+* **BComputeType** - compute data type of tensor B for mfma instruction (AComputeType by default).
+
+Grouped convolution backward data supports tensors larger than 2GB (except when image is larger than 2GB).
+
+List of the device operations for grouped convolution backward data in CK:
+
+* **DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1** - Device operation with XDL instructions and support of fused operations to input.
+* **DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle** - Device operation with WMMA instructions.
+
+Table of supported cases by instance factory with XDL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16|2D, 3D|✗|2D, 3D|
+|fp16 |2D, 3D|✗|2D, 3D|
+|fp32  |2D, 3D|✗|2D, 3D|
+
+Table of supported cases by instance factory with WMMA instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|fp16 |2D, 3D|✗|2D, 3D|
+|int8 |2D, 3D|✗|2D, 3D|
+
+Table of supported cases by instance factory with fused elementwise operation:
+
+* **Bilinear** - 3D, NHWGC, bf16/fp16/fp32
+* **Scale** - 3D, NHWGC, bf16/fp16/fp32

client_example/11_grouped_conv_bwd_weight/README.md

+[Back to supported operations](../../../include/ck/README.md)
+# Composable Kernel Grouped Convolution
+
+## Grouped Convolution Backward Weight
+
+Grouped convolution operation for 1D, 2D or 3D spatial dimensions. Convolution utilizes GEMM kernel after tensor coordinate transform. Backward weight version uses splitK feature (due to large GEMM K dimension). In CK Grouped Convolution Backward Weight operation is called as `DeviceGroupedConvBwdWeight` and requires following types as template parameters:
+
+* **NumDimSpatial** - number of spatial dimensions (1D, 2D, 3D).
+* **InLayout** - input layout (NHWGC, GNHWC, NGCHW).
+* **WeiLayout** - weight layout (GKYXC).
+* **OutLayout** - output layout (NHWGK, GNHWK, NGKHW).
+* **InDataType** - input data type.
+* **WeiDataType** - weight data type.
+* **OutDataType** - output data type.
+* **InElementwiseOperation** - fused operation on tensor input.
+* **WeiElementwiseOperation** - fused operation on tensor weight.
+* **OutElementwiseOperation** - fused operation on tensor output.
+* **ComputeTypeA** - compute data type of tensor A for mfma instruction (ADataType by default).
+* **ComputeTypeB** - compute data type of tensor B for mfma instruction (ComputeTypeA by default).
+
+For fused operations with additional tensor there is `DeviceGroupedConvBwdWeightMultipleD` operation which requires following parameters:
+* **DsLayout** - layouts for additional tensors for fused operations.
+* **DsDataType** - data types for additional tensors for fused operations.
+
+Grouped convolution backward weight doesn't supports tensors larger than 2GB.
+
+List of the device operations for grouped convolution backward weight in CK:
+
+* **DeviceGroupedConvBwdWeight_Xdl_CShuffle** - Device operation with XDL instructions.
+* **DeviceGroupedConvBwdWeightTwoStage_Xdl_CShuffle** - Device operation with XDL instructions. Optimized for small C or K.
+* **DeviceGroupedConvBwdWeight_Wmma_CShuffle** - Device operation with WMMA instructions.
+* **DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle** - Device operation with XDL instructions and support of fused operations to output.
+* **DeviceGroupedConvBwdWeight_Dl** - Device operation with DL instructions.
+
+Table of supported cases by instance factory with XDL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16|2D, 3D|✗|✗|
+|bf16(fp32 for weight)|2D, 3D|✗|1D, 2D, 3D|
+|fp16 |2D, 3D|✗|1D, 2D, 3D|
+|fp32  |2D, 3D|✗|1D, 2D, 3D|
+
+Table of supported cases by instance factory with WMMA instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|fp16 |3D|✗|3D|
+|int8 |3D|✗|3D|
+
+Table of supported cases by instance factory with DL instruction:
+
+|       |NHWGC/GKYXC/NHWGK|NGCHW/GKYXC/NGKHW|GNHWC/GKYXC/GNHWK|
+|-------|---|---|---|
+|bf16(fp32 for weight)|1D, 2D, 3D|✗|1D, 2D, 3D|
+|fp16 |1D, 2D, 3D|✗|1D, 2D, 3D|
+|fp32  |1D, 2D, 3D|✗|1D, 2D, 3D|
+
+Table of supported cases by instance factory with fused elementwise operation:
+
+* **Bilinear** - 3D, NHWGC, bf16(fp32 for weight)/fp16/fp32
+* **Scale** - 3D, NHWGC, bf16(fp32 for weight)/fp16/fp32

client_example/24_grouped_conv_activation/CMakeLists.txt

@@ -54,7 +54,7 @@ target_link_libraries(client_conv3d_fwd_convscale_relu_amax_fp8
                       PRIVATE composable_kernel::device_conv_operations
                               composable_kernel::device_other_operations
                               composable_kernel::device_reduction_operations
-                              utility)
+                              composable_kernel::utility)
 # Fwd convscale + AMAX
 add_executable(client_conv3d_fwd_convscale_amax_fp8
                grouped_convnd_fwd_convscale_reduce/conv3d_fwd_convscale_amax_fp8.cpp)
@@ -62,7 +62,7 @@ target_link_libraries(client_conv3d_fwd_convscale_amax_fp8
                       PRIVATE composable_kernel::device_conv_operations
                               composable_kernel::device_other_operations
                               composable_kernel::device_reduction_operations
-                              utility)
+                              composable_kernel::utility)
 # Fwd convscale
 add_executable(client_conv3d_fwd_convscale_fp8
                grouped_convnd_fwd_convscale/conv3d_fwd_convscale_fp8.cpp)