Apache SINGA vs DeepSpeed
Apache SINGA
singa.apache.orgDeepSpeed
deepspeed.aiSide by side
| Figure | Apache SINGA | DeepSpeed |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Deep Learning Software | 8.2 (#8) | 8.0 (#12) |
| Intended users | The project describes its focus as distributed training of deep-learning and machine-learning models and highlights large-scale data analytics. | The project describes its audience as deep learning researchers and practitioners working on large-scale training and inference. |
| License | The SINGA history page says the project is released under Apache License Version 2.0. | The GitHub repository identifies DeepSpeed as an open-source project under the Apache-2.0 license. |
| Support | The project lists mailing lists, issue tracking, and a security page under its community resources. | The GitHub repository says DeepSpeed holds public office hours on the last Tuesday of each month. |
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.