Orchest vs CuPy: What are the differences?
What is Orchest? An open source tool for creating data science pipelines. It is a web-based data science tool that works on top of your filesystem allowing you to use your editor of choice. With Orchest you get to focus on visually building and iterating on your pipeline ideas. Under the hood Orchest runs a collection of containers to provide a scalable platform that can run on your laptop as well as on a large scale cloud cluster.
What is CuPy? A NumPy-compatible matrix library accelerated by CUDA. It is an open-source matrix library accelerated with NVIDIA CUDA. CuPy provides GPU accelerated computing with Python. It uses CUDA-related libraries including cuBLAS, cuDNN, cuRand, cuSolver, cuSPARSE, cuFFT and NCCL to make full use of the GPU architecture.
Orchest and CuPy can be categorized as "Data Science" tools.
Some of the features offered by Orchest are:
- Visual pipeline editor
- Executable notebooks
- Open source
On the other hand, CuPy provides the following key features:
- It's interface is highly compatible with NumPy in most cases it can be used as a drop-in replacement
- Supports various methods, indexing, data types, broadcasting and more
- You can easily make a custom CUDA kernel if you want to make your code run faster, requiring only a small code snippet of C++
CuPy is an open source tool with 4.45K GitHub stars and 402 GitHub forks. Here's a link to CuPy's open source repository on GitHub.