nerfstudio-project / gsplat
CUDA accelerated rasterization of gaussian splatting
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CUDA accelerated rasterization of gaussian splatting
Instant neural graphics primitives: lightning fast NeRF and more
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
Tile primitives for speedy kernels
GPU accelerated decision optimization
Causal depthwise conv1d in CUDA, with a PyTorch interface
DeepEP: an efficient expert-parallel communication library
NCCL Tests
how to optimize some algorithm in cuda.
CUDA Kernel Benchmarking 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.
[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl
RCCL Performance Benchmark Tests
Fast CUDA matrix multiplication from scratch
cuVS - a library for vector search and clustering on the GPU
LLM training in simple, raw C/CUDA