array2d/deepx
Large-scale Auto-Distributed Training/Inference Unified Framework | Memory-Compute-Control Decoupled Architecture | Multi-language SDK & Heterogeneous Hardware Support
DeepX provides a unified framework for training and deploying deep learning models across multiple hardware platforms and programming languages. It helps machine learning engineers express complex model computations using simple mathematical forms, which are then automatically executed across distributed GPU clusters. The system takes these mathematical model definitions and outputs a deployable, high-performance deep learning solution, allowing practitioners to focus on algorithms rather than infrastructure.
Use this if you are an algorithm or infrastructure engineer needing to train and deploy large-scale deep learning models efficiently across heterogeneous hardware without getting bogged down in distributed computing complexities.
Not ideal if you are looking for a simple, single-machine deep learning library for small-scale projects, as its main benefit lies in managing distributed computations.
Stars
55
Forks
6
Language
C++
License
Apache-2.0
Category
Last pushed
Jan 30, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/array2d/deepx"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepspeedai/DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference...
helmholtz-analytics/heat
Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python
hpcaitech/ColossalAI
Making large AI models cheaper, faster and more accessible
horovod/horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
bsc-wdc/dislib
The Distributed Computing library for python implemented using PyCOMPSs programming model for HPC.