CuPy vs Grooper

Grooper vs CuPy: What are the differences?

What is Grooper? Innovate workflows by integrating difficult data. It empowers rapid innovation for organizations processing and integrating large quantities of difficult data. Created by a team of courageous developers frustrated by limitations in existing solutions, It is an intelligent document and digital data integration platform. It combines patented and sophisticated image processing, capture technology, machine learning, and natural language processing.

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.

Grooper and CuPy can be primarily classified as "Data Science" tools.

Some of the features offered by Grooper are:

• Text and Document Classification
• Hierarchical Data Modeling
• Image Capture

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 4.14K GitHub stars and 373 GitHub forks. Here's a link to CuPy's open source repository on GitHub.