NVIDIA / cub
[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl
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[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl
[ICLR2025, ICML2025, NeurIPS2025 Spotlight] Quantized Attention achieves speedup of 2-5x compared to FlashAttention, without lossing end-to-end metrics across language, image, and video models.
DeepEP: an efficient expert-parallel communication library
FlashInfer: Kernel Library for LLM Serving
CUDA Kernel Benchmarking Library
PyTorch bindings for CUTLASS grouped GEMM.
Causal depthwise conv1d in CUDA, with a PyTorch interface
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
Tile primitives for speedy kernels
LLM training in simple, raw C/CUDA
Instant neural graphics primitives: lightning fast NeRF and more
cuVS - a library for vector search and clustering on the GPU
CUDA Library Samples
NCCL Tests