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
CUDA accelerated rasterization of gaussian splatting
LLM training in simple, raw C/CUDA
FlashInfer: Kernel Library for LLM Serving
Instant neural graphics primitives: lightning fast NeRF and more
NCCL Tests
DeepEP: an efficient expert-parallel communication library
[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.
Tile primitives for speedy kernels
[ICML2025] SpargeAttention: A training-free sparse attention that accelerates any model inference.
Causal depthwise conv1d in CUDA, with a PyTorch interface