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- Ongoing research training transformer models at scale
- CUDA Templates for Linear Algebra Subroutines
- C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
- A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
- AIStore: scalable storage for AI applications
- TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and support state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in performant way.
- CUDA Core Compute Libraries
- Documentation repository for NVIDIA Cloud Native Technologies
- Differentiable signal processing on the sphere for PyTorch
- CUDA Kernel Benchmarking Library