GAIA: GPU Artificial Intelligence Appliance
#whenperformancematters
The “ready-to-go” GPU appliance
GAIA is a powerful solution that exclusively uses top-of-the range hardware: multi-core CPUs, up to 2TB of RAM, NVMe drives and high speed interconnected multi-GPUs.
The end-user can access a series of containerised workspaces for the development of Data Analytics, Machine Learning and Deep Learning applications while using better underlying hardware. Additionally, GAIA uses leading open-source frameworks (Rapids.AI, Tensorflow, PyTorch, MXnet…).
Engineered, not assembled
GAIA produces an easy-to-use interactive multiuser interface (based on notebook technology).
GAIA is an open solution, making it easy to integrate third-party containers (Nvidia, DockerHub…). Moreover, with regular additions and updates delivered by E4 Analytics, GAIA will always remain state of the art for Data Science.
The GAIA approach
GAIA (GPU Artificial Intelligence Appliance) is the platform for enabling scalable and high performance Machine Learning and Deep learning workloads.
GAIA was designed by our professionals at E4 Analytics to help data scientists maximise their productivity in collecting, cleaning up and transforming company data, implementing and testing the most advanced Machine Learning algorithms, and exploiting the results of Big Data analyses for the benefit of their company.
POWERFUL
The foundation of GAIA’s hardware is a super server which can integrate up to a 64 core CPU, up to 2TB of RAM, fast and large storage devices based on NVMe technology and up to 8 interconnected all-to-all GPUs.
CONTAINERIZED
Workspaces are always implemented across container images: the end user has access to numerous workspaces, designed to perform optimally at each stage of the typical data science workflow, without compromising performance.
READY TO USE
GAIA is a “ready-to-use” solution that integrates a multi-user web interface based on Jupyter Notebook, which incorporates code with descriptive text, formulae, graphical visualisation, and multimedia content, interactively.
FUTURE PROOF
The world of Data Science is in a constant state of change. Like all services offered by E4 analytics, GAIA’s stack software is regularly renewed and upgraded with the most innovative updates from open source.
Designed to be the best: always
Advanced Analytics and Artificial Intelligence: decision support systems.
Business Intelligence: understanding what happened in the past.
Artificial Intelligence: making predictions and generating recommendations for the future.
In these technologies, computers are trained to perform specific tasks through the processing of large quantities of data and the identification of models present within these data. This requires both high performance server accelerators (GPU and FPGA), as well as networking and storage components.
Discover the advantages
Solution Layout
Technical features
What is E4AI-PLATFORM
A software stack which integrates all the necessary components to implement a full AI workflow.
KUBERNETES Single Node: orchestration of Containers
NVIDIA GPU Operator: GPU Computing support
DirectPV: Persistency of container data
MinIO Object Storage: Shared Data Storage service
ICE4AI: interactive workspace based on Notebook technology, along with services necessary for the implementation and automation of an AI workflow.
What is ICE4AI
ICE4AI is an interactive computing environment for development in Python and beyond.
ICE4AI is based on Jupyter Notebook technology
ICE4AI is designed and configured for Data Analysis, Machine Learning and Deep Learning
ICE4AI can be configured to offer the end-user dedicated computing resources
ICE4AI is easily integrated with the main NVIDIA containers (NGC).
Components
GAIA 2022 | working enviroments
GAIA 2022 | extended Jupiterlab UI
ICE4AI: Container structure
Access to ICE4AI workspaces is gained through a customised version of JupyterHub, necessary to provide multi-user access to the software stack. The interface gives the end user choice of both which workspace to use, from a list of container images, and allocation of computing resources, from a series of profiles predefined by the system administrator.
In addition to the base images, ICE4AI includes the following workspaces:
- DASK, a framework for distributed computing in Data Science, that gives the developer the same APIs as Numpy, Pandas, and Scikit-Learn, but that can use all the cores of the containers by which it is instantiated
- RAPIDS.AI, a framework developed and maintained by NVIDIA that offers the same APIs as the typical Data Analysis tools in Python (Numpy, Pandas, Scikit-learn, …), but that is totally GPU-based. This allows the user to, for example, use GPU computing when preparing, transforming and enriching data, which is often necessary prior to using specific Machine Learning models.
- Tensorflow2, an “end-to-end open-source platform for Machine Learning”, with a complete and flexible ecosystem full of state of the art tools and libraries for Machine Learning
- PyTorch, a high performance framework for the development of Deep Learning applications, with additional tools and libraries extending the framework’s capabilities, so as to support the development of Artificial Vision, Natural Language Processing and Time Series Analysis applications based on Deep Learning
- MXnet, a slim, flexible and highly-scalable framework for the development of Deep Learning models, managed by the Apache Software Foundation, which also includes high performance Gluon modules for Computer Vision, NLP, and Time Series Analysis
Architectural advantages
HIGH PERFORMANCE APPLIANCE
GAIA is a ready-to-use, high performance appliance, used for the development, testing and deployment of scalable Data Analytics, Machine Learning and Deep Learning applications. It is the ideal solution for companies that want to extract the most value from their data.
VERSATILE
GAIA enables the user to have different integrated versions of each workspace online and allows them to make additional customised versions if required.
OPEN SOURCE
GAIA exclusively uses open source technology developed by the most relevant and active Data Science communities
SCALABILE
GAIA‘s architecture responds to growing demands for better computing resources, enabling the creation of a cluster consisting of multiple GAIAs, functioning as worker nodes.
Why choose this E4 solution
READY-TO-USE
A ready-to-use appliance equipped with a multi-user Interactive Computing Environment made for Data Science
VALIDATED
Performance tests are carried out on all servers that make up the solution before they are released to the client. In addition to the usual firmware check, homogeneity check, sanity check and setup check, we use additional tools that verify whether performance levels correspond to those requested by the client. A few tests of note include HPL (High Performance Linpack) to test a machine’s computing power, measured in FLOPs; STREAM to test the memory’s bandwidth, measured in MB/s; and IOzone to test a disk’s access speed, measured in MB/s and IOPS.
TESTED
Each component is burn-in tested for up to 120hrs, according to a protocol developed by E4, to ensure that our unique systems remain perfectly engineered and functioning, thus reducing both the Dead on Arrival and “early failure” rate following release. This significantly improves the overall reliability of E4 solutions.
SERVICED
E4 is amongst the few companies that currently provides high level services to both large academic and private organisations, as well as to international research centres of complexity and of national and international importance. We support these institutions in the design, configuration and commissioning of extremely sophisticated solutions for the processing of Big Data with our high performance solutions.
Basic services
Data scientist services
– per activity
– pay-per-day packages
– work-for-hire
Functional training on the workspace END-2-END SOFTWARE STACK FOR AI
Basic services
Senior Data Scientist consultation
– online session (pay-per-hour)
– onsite session (pay-per-day)
– work-for-hire
Platform customisation END-2-END SOFTWARE STACK FOR AI
Extra | New functionalities coming soon
NEW FUNCTIONALITIES
- GAIA will soon support development in R and Julia
- GAIA will soon directly integrate several NVIDIA containers (NGC)
- GAIA enterprise based on E4 VSTONE
GPU Appliance
