This project incorporates the Argo Navis Technologies, LLC contributions to the CBTF project. This project consists of support for building performance tools based on the CBTF baseline project (CBTF: https://github.com/OpenSpeedShop/cbtf). These contributions include a CUDA collection mechanism which uses the NVIDIA CUDA and CUPTI interfaces to …
OpenSpeedShop/cbtf-argonavis
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-------------------- OVERVIEW -------------------- The goal of the Component Based Tool Framework (CBTF) project is to create a community tool infrastructure that provides individual tool building components to allow others to add or replace modules, to integrate parts into their own tools, or to customize existing solutions. In other words, the CBTF project provides support for creating a compatible interface for components, finding compatible components and defining an interface API which facilitates communication between components. In the CBTF framework, a component is defined as a “black box” entity with zero or more inputs and zero or more outputs. You may connect these components into component networks both distributed and non-distributed. The CBTF transport mechanism, based on MRNet, allows distributed tools to automatically become highly scalable. There are four CBTF sub-projects that are represented by their corresponding source repositories that comprise the high level CBTF project: * CBTF project contains the base code for CBTF that supports creating components, component networks and the support to connect these components and component networks into sequential and distributed network tools. * CBTF Krell project contains the Krell Institute contributions to the CBTF project. These contributions include many performance data collectors and support libraries as well as some example tools that drive the data collection at HPC levels of scale. This is a fundamental, base portion of the OpenSpeedShop performance tool. * CBTF Argo Navis project contains the CUDA collector and supporting libraries that was done as a result of a DOE SBIR grant and is currently being developed via a NASA phase II SBIR. * CBTF LANL project contains a memory tool and data center type system command monitoring tool. -------------------- NOTES ON BUILDING -------------------- # Use a version of cmake: 2.8.12 or greater. # if not installed by default on the build system. module load cmake An example cmake run script is as follows: $ cat run_cmake_argo.sh rm -rf build mkdir build pushd build export CC=`which gcc` export CXX=`which g++` export KRELL_ROOT=/opt/krellroot_v2.2.2 export DYNINST_ROOT=/opt/krellroot_v2.2.2 export CBTF_ROOT=/opt/cbtf_v2.2.2 export CBTF_KRELL_ROOT=/opt/cbtf_v2.2.2 export CBTF_ARGO_PREFIX=/opt/cbtf_v2.2.2 export MY_CUDA_ROOT=/usr/local/cuda export MY_CMAKE_PREFIX_PATH="${KRELL_ROOT}:${CBTF_ROOT}:${CBTF_KRELL_ROOT}" cmake .. \ -DCMAKE_BUILD_TYPE=None \ -DCMAKE_CXX_FLAGS="-g -O2" \ -DCMAKE_C_FLAGS="-g -O2" \ -DCMAKE_VERBOSE_MAKEFILE=ON \ -DCMAKE_INSTALL_PREFIX=${CBTF_ARGO_PREFIX} \ -DCMAKE_PREFIX_PATH=${MY_CMAKE_PREFIX_PATH} \ -DCBTF_DIR=${CBTF_ROOT} \ -DCBTF_KRELL_DIR=${CBTF_KRELL_ROOT} \ -DCUPTI_DIR=${MY_CUDA_ROOT}/extras/CUPTI \ -DCUDA_INSTALL_PATH=${MY_CUDA_ROOT}\ -DCUDA_DIR=${MY_CUDA_ROOT} \ -DPAPI_DIR=${KRELL_ROOT} \ -DMRNET_DIR=${KRELL_ROOT} make clean make make install
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This project incorporates the Argo Navis Technologies, LLC contributions to the CBTF project. This project consists of support for building performance tools based on the CBTF baseline project (CBTF: https://github.com/OpenSpeedShop/cbtf). These contributions include a CUDA collection mechanism which uses the NVIDIA CUDA and CUPTI interfaces to …