nerfstudio-project / gsplat
CUDA accelerated rasterization of gaussian splatting
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CUDA accelerated rasterization of gaussian splatting
Tile primitives for speedy kernels
[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.
DeepEP: an efficient expert-parallel communication library
FlashInfer: Kernel Library for LLM Serving
GPU accelerated decision optimization
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
LLM training in simple, raw C/CUDA
[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
CUDA Kernel Benchmarking Library
how to optimize some algorithm in cuda.
Instant neural graphics primitives: lightning fast NeRF and more
NCCL Tests
Distributed multigrid linear solver library on GPU