# apache/singa

a distributed deep learning platform

Repository: https://github.com/apache/singa
Canonical: https://ross.abutalabs.com/products/singa
Language: C++
License: Apache-2.0
License Family: permissive
Topics: deep-learning
Last push: 2026-07-07T14:12:05+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 91, release rhythm 8, longevity 100
- inputs: {"age_days": 4171, "days_push": 57, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3606, forks 1267 (observed 2026-08-28T04:08:11.533771+00:00)

## What it is
Apache SINGA is a distributed deep learning platform for training neural networks across multiple devices and machines. It provides a C++ core with Python APIs and supports distributed model training.

## Use cases
- train deep learning models across multiple GPUs
- run distributed neural network training on a cluster
- build and train CNNs and RNNs with a Python API
- scale deep learning workloads beyond a single machine
- experiment with an Apache-licensed deep learning framework

## When to choose
- you need distributed training with an Apache-2.0 license
- you want a C++ core with Python bindings
- you prefer an Apache Foundation project with community governance

## When to avoid
- you need a mainstream ecosystem like PyTorch or TensorFlow with broad community support
- you only train small models on a single machine
- you need extensive pretrained models and tutorials

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, machine-learning, gpu-computing
- domain: deep-learning, machine-learning, microservices
- platform: cpp, python
- tags: distributed-training, apache-project, neural-networks, linux, macos, docker

## Member repositories
- apache/singa (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:11.533771+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 2026-08-29T18:33:42.050355+00:00, confidence not recorded.
  - readme: https://github.com/apache/singa (fetched 2026-08-28T04:08:11.533771+00:00, sha 87d027bbce8d)
- Data as of 2026-08-30T08:39:29.467469+00:00.