RocketML Low-code Distributed Deep Learning

RocketML

3.2

Price: Typical Total Price$4.05/hrTotal pricing per instance for services hosted on p3.2xlarge in US East (N. Virginia). View Details

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Product Overview

rmldnn is a command-line tool that makes deep-learning models easy to build and fast to train. It does not require knowledge of any deep-learning framework (Pytorch, Tensorflow, Keras, etc) or any Python code. Using rmldnn, one can build deep-learning models on either a small single GPU laptop or a large supercomputer with hundreds of GPUs or CPUs without any prior knowledge of distributed computing.Benefits:Does not require any knowledge of deep-learning frameworks (Pytorch, Keras, etc) or Python.Is designed with scalability & performance in mind from the get-go.Is agnostic to machine and processor architectures, running seamlessly on both CPU and GPU systems.Runs on anything from one to hundreds of GPUs or CPUs without any required knowledge of distributed computing, automatically managing data partitioning and communication among nodes.Allows building models for different computer vision use cases like image classification, object detection, image segmentation, autoencoders, and generative networks.
Version: 1.3.0
By
RocketML

Categories: Computer Vision
High Performance Computing
ML Solutions

Operating System
Linux/Unix, Ubuntu 18.04
Delivery Methods
Amazon Machine Image

Highlights: Ease-of-use: Simple, code-free, configuration-based command-line interface Uncompromising performance: Blazing-fast speeds and HPC-grade scalability on GPU/CPU clusters

Category: Infrastructure Software

Delivery Method: Amazon Machine Image

Company Information

Company Name: RocketML

About Company: RocketML is a Super Fast Computational engine for Machine Learning. Built for data scientists and engineers, RocketML scales Machine Learning models theoretically with no limits. RocketML works best when datasets are complex and large. It also works with Apache Spark and other popular open source infrastructure tools and libraries.

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