JavaScript vs. CUDA vs. NumPy vs. TypeScript Comparison Chart

CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

TypeScript adds additional syntax to JavaScript to support a tighter integration with your editor. Catch errors early in your editor. TypeScript code converts to JavaScript, which runs anywhere JavaScript runs: In a browser, on Node.js or Deno and in your apps. TypeScript understands JavaScript and uses type inference to give you great tooling without additional code. TypeScript was used by 78% of the 2020 State of JS respondents, with 93% saying they would use it again. The most common kinds of errors that programmers write can be described as type errors: a certain kind of value was used where a different kind of value was expected. This could be due to simple typos, a failure to understand the API surface of a library, incorrect assumptions about runtime behavior, or other errors.