This is the Linux app named Ray whose latest release can be downloaded as Ray-2.7.1.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS
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Ray
DESCRIPTION
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core.
Features
- Reinforcement learning
- General Python apps
- Data processing
- Hyperparameter tuning
- Deep learning
- Model serving
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/ray.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
