DOKSparse VS cuhnsw

Compare DOKSparse vs cuhnsw and see what are their differences.

DOKSparse

sparse DOK tensors on GPU, pytorch (by DeMoriarty)
Cuda Pytorch Sparse
Source Code
Suggest alternative
Edit details

cuhnsw

CUDA implementation of Hierarchical Navigable Small World Graph algorithm (by js1010)
Hnsw GPU Ann Cuda
Source Code
Suggest alternative
Edit details
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
DOKSparse cuhnsw
2 4
2 112
- -
4.2 0.0
10 months ago about 3 years ago
Cuda Cuda
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DOKSparse

Posts with mentions or reviews of DOKSparse. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-03.
  • GDlog: A GPU-Accelerated Deductive Engine
    16 projects | news.ycombinator.com | 3 Dec 2023
  • tensor.to_sparse() Memory Allocation
    1 project | /r/pytorch | 22 Apr 2023
    If using sparse tensors is a must, you can look into DOK sparse format, which is supported for 2d matrices in scipy. it kinda allows you to access any element of the sparse tensor in constant time, which makes it possible to create your tensor directly in sparse format, skipping the need to create a dense numpy array first. In case you need a GPU version of this, I have a library that implements sparse dok tensor in pytorch and cuda. currently it's GPU only.

cuhnsw

Posts with mentions or reviews of cuhnsw. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing DOKSparse and cuhnsw you can also consider the following projects:

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

Open3D - Open3D: A Modern Library for 3D Data Processing

MegBA - MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment

lightseq - LightSeq: A High Performance Library for Sequence Processing and Generation

CUDA-Guide - CUDA Guide

cuml - cuML - RAPIDS Machine Learning Library

TorchPQ - Approximate nearest neighbor search with product quantization on GPU in pytorch and cuda

FirstCollisionTimestepRarefiedGasSimulator - This simulator computes all possible intersections for a very small timestep for a particle model

instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more

cccl - CUDA C++ Core Libraries

warpcore - A Library for fast Hash Tables on GPUs

gdlog

DOKSparse vs cub cuhnsw vs Open3D DOKSparse vs MegBA cuhnsw vs lightseq DOKSparse vs CUDA-Guide cuhnsw vs cuml DOKSparse vs TorchPQ cuhnsw vs FirstCollisionTimestepRarefiedGasSimulator DOKSparse vs instant-ngp DOKSparse vs cccl DOKSparse vs warpcore DOKSparse vs gdlog