MegBA VS DOKSparse

Compare MegBA vs DOKSparse and see what are their differences.

MegBA

MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment (by MegviiRobot)
High Performance Distributed bundleadjustment gpu-acceleration Cuda graph-optimization
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DOKSparse

sparse DOK tensors on GPU, pytorch (by DeMoriarty)
Cuda Pytorch Sparse
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MegBA DOKSparse
1 2
431 2
1.2% -
4.5 4.2
5 months ago 10 months ago
Cuda Cuda
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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MegBA

Posts with mentions or reviews of MegBA. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-07.

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.

What are some alternatives?

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

PBA - Photometric Bundle Adjustment for Dense Multi-View Stereo

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

pixel-perfect-sfm - Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Best Student Paper Award)

CUDA-Guide - CUDA Guide

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

cuhnsw - CUDA implementation of Hierarchical Navigable Small World Graph algorithm

TornadoVM - TornadoVM: A practical and efficient heterogeneous programming framework for managed languages

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

ceres-solver - A large scale non-linear optimization library

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

Scalix - Scalix is a data parallel compute library that automatically scales to the available compute resources.

cccl - CUDA C++ Core Libraries

MegBA vs PBA DOKSparse vs cub MegBA vs pixel-perfect-sfm DOKSparse vs CUDA-Guide MegBA vs FirstCollisionTimestepRarefiedGasSimulator DOKSparse vs cuhnsw MegBA vs TornadoVM DOKSparse vs TorchPQ MegBA vs ceres-solver DOKSparse vs instant-ngp MegBA vs Scalix DOKSparse vs cccl