Mojo vs. NVIDIA RAPIDS vs. Python vs. RT-LAB Comparison Chart

The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes. Accelerate your Python data science toolchain with minimal code changes and no new tools to learn. Increase machine learning model accuracy by iterating on models faster and deploying them more frequently.

RT-LAB is OPAL-RT’s real-time simulation software combining performance and enhanced user experience. Fully integrated with MATLAB/Simulink®, RT-LAB offers the most complex model-based design for interaction with real-world environments. It provides the flexibility and scalability to achieve the most complex real-time simulation applications in the automotive, aerospace, power electronics, and power systems industries. Since its first application nearly 20 years ago on the Canadian Space Agency’s Canada Arm, RT-LAB has revolutionized the world of systems engineering, whether in space, on the ground or at sea. RT-LAB enables engineers and scientists to accelerate the development of new prototypes and to meet the most rigorous testing required by new and innovative technologies. RT-LAB handles everything, including code generation, with an easy-to-use interface. With just a few clicks of the mouse, a Simulink® model becomes an interactive real-time simulation application.