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2 repositories tagged with scientific-computing
NVIDIA PhysicsNeMo: Deep Learning Framework for Physics-ML Models
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building, training, and fine-tuning Physics AI models. It leverages state-of-the-art scientific machine learning methods, enabling real-time predictions by combining physics knowledge with data. This framework provides scalable, GPU-optimized tools for AI4Science and engineering applications.
CuPy: NumPy & SciPy for GPU-Accelerated Computing in Python
CuPy is a powerful Python array library that provides NumPy and SciPy-compatible interfaces for GPU-accelerated computing. It enables users to seamlessly run existing numerical code on NVIDIA CUDA or AMD ROCm platforms with minimal changes. This tool also offers direct access to low-level CUDA features for advanced performance tuning and high-performance scientific computing.