Mojo vs. CUDA vs. Python vs. Swagger Codegen 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.

Swagger Codegen can simplify your build process by generating server stubs and client SDKs for any API, defined with the OpenAPI (formerly known as Swagger) specification, so your team can focus better on your API’s implementation and adoption. Moving from design to development has never been easier with Swagger Codegen in SwaggerHub. API Definition files can be used to create stubs in popular languages, like Java, Scala, and Ruby, with just a few clicks.