NVIDIA / cuopt
GPU accelerated decision optimization
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GPU accelerated decision optimization
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
[ICLR2025, ICML2025, NeurIPS2025 Spotlight] Quantized Attention achieves speedup of 2-5x compared to FlashAttention, without losing end-to-end metrics across language, image, and video models.
Causal depthwise conv1d in CUDA, with a PyTorch interface
[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl
NCCL Tests
Lightning fast differentiable SSIM.
cuGraph - RAPIDS Graph Analytics Library
Tile primitives for speedy kernels
CUDA Kernel Benchmarking Library
Instant neural graphics primitives: lightning fast NeRF and more
DeepEP: an efficient expert-parallel communication library
LLM training in simple, raw C/CUDA