Apache SINGA vs Ray Train
Apache SINGA
singa.apache.orgRay Train
ray.ioSide by side
| Figure | Apache SINGA | Ray Train |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Deep Learning Software | 8.2 (#8) | 7.4 (#25) |
| Intended users | The project describes its focus as distributed training of deep-learning and machine-learning models and highlights large-scale data analytics. | Ray’s security documentation describes Ray developers running local single-node clusters or remote multi-node clusters on infrastructure provided by platform providers. |
| Support | The project lists mailing lists, issue tracking, and a security page under its community resources. | The Ray site offers a community Slack, forums, and documentation, and says Anyscale offers hands-on training and expert support. |
Plans
In their own words
Apache SINGA
Apache SINGA is a free distributed deep-learning library for training deep-learning and machine-learning models. Its listed training mode is local, with data-parallel training across multiple GPUs on one node or across multiple nodes. GPU packages use CUDA and cuDNN, and Docker images are available for Nvidia GPUs. Installation options include pip, Docker, Conda, and source builds; pip documentation covers Python 3.9, 3.10, and 3.11. SINGA supports Python and C++, loads ONNX models, and can save models defined through its APIs in ONNX format. Optimizers listed include momentum-based stochastic gradient descent, Adam, RMSProp, and AdaGrad. Models can be queried in an RDBMS. The repository and Google Colab provide domain-specific models, including healthcare and science examples. It runs on Linux, macOS, Windows, and self-hosted environments, with on-premises deployment and Apache License 2.0 licensing.