Azure Data Science Virtual Machines vs. NVIDIA RAPIDS vs. Python vs. pygame 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.

Pygame is a set of Python modules designed for writing video games. Pygame adds functionality on top of the excellent SDL library. This allows you to create fully featured games and multimedia programs in the python language. Pygame is highly portable and runs on nearly every platform and operating system. Pygame is free. Released under the LGPL license, you can create open-source, freeware, shareware, and commercial games with it. With dual-core CPUs common, and 8-core CPUs cheaply available on desktop systems, making use of multi-core CPUs allows you to do more in your game. Selected pygame functions release the dreaded python GIL, which is something you can do from C code. Uses optimized C and assembly code for core functions. C code is often 10-20 times faster than python code, and assembly code can easily be 100x or more times faster than python code. Comes with many operating systems. Just an apt-get, emerge, pkg_add, or just install away.