Run High-Performance Core Math at Scale with NVIDIA nvmath-python | NVIDIA Technical Blog

What this post added

This post introduces nvmath-python v1.0, a Pythonic abstraction layer over CUDA-X and NVPL math libraries. It enables Python users to access accelerated math operations on CPU, GPU, and distributed multi-node systems, integrating with NumPy, CuPy, and PyTorch. Key contributions include universal sparse tensor (UST) support via a domain-specific language, generic and specialized APIs for performance optimization, fast and flexible installation, and integration with Python's logging module for computational tracing. It also highlights the ability to amortize planning and autotuning costs and allows for custom kernel fusion.