Instant neural graphics primitives: lightning fast NeRF and more
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Updated
Apr 18, 2024 - Cuda
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
Instant neural graphics primitives: lightning fast NeRF and more
GPU Accelerated t-SNE for CUDA with Python bindings
cuGraph - RAPIDS Graph Analytics Library
🎉CUDA 笔记 / 大模型手撕CUDA / C++笔记,更新随缘: flash_attn、sgemm、sgemv、warp reduce、block reduce、dot product、elementwise、softmax、layernorm、rmsnorm、hist etc.
FlashInfer: Kernel Library for LLM Serving
Fuse multiple depth frames into a TSDF voxel volume.
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.
CUDA Kernel Benchmarking Library
MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment
Graphics Processing Units Molecular Dynamics
PopSift is an implementation of the SIFT algorithm in CUDA.
A simple GPU hash table implemented in CUDA using lock free techniques
Neighborhood Attention Extension. Bringing attention to a neighborhood near you!
SDK for GPU accelerated genome assembly and analysis
Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.
Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
Created by Nvidia
Released June 23, 2007