Instant neural graphics primitives: lightning fast NeRF and more

how to optimize some algorithm in cuda.

cuGraph - RAPIDS Graph Analytics Library

[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl

Deformable ConvNets V2 (DCNv2) in PyTorch

[MICRO'23, MLSys'22] TorchSparse: Efficient Training and Inference Framework for Sparse Convolution on GPUs.

Efficient GPU kernels for block-sparse matrix multiplication and convolution

This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, s…

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 …

A simple GPU hash table implemented in CUDA using lock free techniques

Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.

GPU-accelerated triangle mesh processing

PyTorch-Based Fast and Efficient Processing for Various Machine Learning Applications with Diverse Sparsity

GPU based Solana ed25519 vanity key scanner.

Parallel CUDA FloodFill algorithm working on 2D and 3D arrays with obstacles