# AlgRUC/JittorGeometric

JittorGeometric is a Jittor-based graph machine learning library.

Repository: https://github.com/AlgRUC/JittorGeometric
Canonical: https://ross.abutalabs.com/products/jittorgeometric
Language: Python
License: Apache-2.0
License Family: permissive
Topics: graph, jittor, python
Last push: 2026-06-03T13:37:01+00:00

## Health v2 (maintenance only)
Score: 62/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 85, release rhythm 35, longevity 58
- inputs: {"age_days": 821, "days_push": 91, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1177, forks 184 (observed 2026-08-28T04:03:52.748640+00:00)

## What it is
JittorGeometric is a graph machine learning library built on the Jittor deep learning framework, providing implementations of 40+ Graph Neural Network models, dataset loaders, and optimized sparse operations. Version 2.0 adds distributed training, dynamic graph processing, mini-batch support, and NPU (Ascend) compatibility.

## Use cases
- train graph neural networks on citation datasets like Cora
- run GNN experiments on the Jittor framework
- distributed multi-GPU training of graph models
- process dynamic graphs with event-based updates
- mini-batch training on large-scale graphs like Reddit
- run graph learning on Huawei Ascend NPUs
- implement graph transformers and self-supervised graph learning

## When to choose
- you want a PyG-like GNN library but must use Jittor
- you need GNN support for Ascend NPUs
- you need distributed or mini-batch GNN training in Jittor

## When to avoid
- your stack is PyTorch or TensorFlow - use PyTorch Geometric or DGL instead
- you need a very mature ecosystem with broad community support

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, gpu-computing
- domain: machine-learning, deep-learning, graph-processing
- platform: python, cross-platform
- tags: graph-neural-networks, gnn, jittor, graph-machine-learning, model-zoo, distributed-training, dynamic-graphs, sparse-operations, algorithms, gpu, linux

## Member repositories
- AlgRUC/JittorGeometric (main) score 62

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:52.748640+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:26:10.103105+00:00, confidence not recorded.
  - readme: https://github.com/AlgRUC/JittorGeometric (fetched 2026-08-28T04:03:52.748640+00:00, sha b972887f1948)
- Data as of 2026-08-30T08:39:29.467469+00:00.