StarPU is a open-source software framework that enables the optimization of scientific computing applications for heterogeneous architectures. It provides a simple and efficient way to parallelize compute-intensive tasks and manage resources, resulting in improved performance and reduced execution time.

The oneAPI-intel project is a unified programming model that allows developers to build high-performance applications for various architectures, including CPUs, GPUs, and FPGAs. It provides a set of libraries, tools, and extensions for optimizing computing-intensive workloads, such as AI, data analytics, and scientific simulations.

The cmake_external_blas project provides a way to externalize BLAS (Basic Linear Algebra Subprograms) libraries during the cmake build process, allowing for better customization and optimization of numerical computations in scientific computing applications.

The oneapi-nvidia project focuses on optimizing deep learning models for NVIDIA GPUs, developing high-performance computing applications, and accelerating scientific simulations using NVIDIA hardware. It provides tools and libraries for developers to leverage the power of NVIDIA GPUs and improve the performance of their data-intensive workloads.

This project is a benchmark plugin for the ICY application, designed to optimize scientific workflows, evaluate the performance of algorithms, and analyze data processing pipelines. It provides a set of methods to measure and compare the performance of different computational tasks.