yahoo/CaffeOnSpark
Distributed deep learning on Hadoop and Spark clusters. observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases archived
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3887
- days_rel: n/a
- days_push: 2483
- n_releases_24m: 0
Adoption not part of the score
1261 stars · 352 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
CaffeOnSpark is a Spark package that brings the Caffe deep learning framework to Hadoop and Spark clusters, enabling distributed neural network training, testing, and feature extraction on GPU/CPU servers. It lets Caffe users train models directly on HDFS datasets using existing LMDB files and minimally adjusted network configs.
Use cases
- train deep learning models on a Hadoop cluster
- distributed neural network training with Spark
- run Caffe on HDFS data without conversion
- extract features from large image datasets on Spark
- scale deep learning across GPU servers with InfiniBand
- integrate deep learning into Scala Spark pipelines
When to avoid
- you are starting a new project - the repo is archived and unsupported
- you prefer modern frameworks like TensorFlow, PyTorch, or Spark's own deep learning integrations
- you need active community support or recent updates
Facets
library · maturity abandoned
deep-learning machine-learning etl deep-learning big-data machine-learning microservices jvm cloud spark hadoop caffe distributed-training hdfs archived linux gpu
1 source
- readme: https://github.com/yahoo/CaffeOnSpark · fetched 2026-08-28 · 262698c764c3
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| yahoo/CaffeOnSpark | main | 10 |
For agents
markdown · JSON · MCP: product_card(name="yahoo/CaffeOnSpark")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem