DataDirect Networks Case Studies Changing Research with a Forward-Looking AI and Big Data Computing Infrastructure

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	Changing Research with a Forward-Looking AI and Big Data Computing Infrastructure DataDirect Networks

Changing Research with a Forward-Looking AI and Big Data Computing Infrastructure

DataDirect Networks

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Machine Learning Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries	Education
Applicable Functions	Product Research & Development
Use Cases	Machine Condition Monitoring Predictive Maintenance
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	Tokyo Institute of Technology (Tokyo Tech) was faced with the challenge of speeding up data access times in parallel with continually improving algorithms that interact with data subsystems. They aimed to achieve this while maintaining optimal power consumption and system efficiency. The institution sought to break away from the conventions of the world's top supercomputers by incorporating elements and design points from containerization, cloud, artificial intelligence (AI), and Big Data. Read More
About Customer	Tokyo Institute of Technology (Tokyo Tech) is the largest institution for higher education in Japan dedicated to science and technology. The institution is known for its innovative approach to research and education in the fields of science and technology. Tokyo Tech is committed to advancing research computing for data-centric infrastructures for the future of research big data but also AI and machine learning. The institution's new TSUBAME3.0 system is a testament to this commitment, showcasing extreme innovation in the area of power consumption and system efficiency. Read More
Solution	To address the challenge, Tokyo Tech implemented a 15.9PB Lustre* parallel file system, composed of three DDN ES14K storage appliances. This solution was integrated into their new TSUBAME3.0 system, which breaks with many of the conventions of the world's top supercomputers. The system incorporates elements and design points from containerization, cloud, artificial intelligence (AI), and Big Data. The solution was designed to speed up data access times in parallel with continually improving algorithms that interact with data subsystems, all while achieving optimal power consumption and system efficiency. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Machine Learning

Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

Education

Applicable Functions

Product Research & Development

Use Cases

Machine Condition Monitoring

Predictive Maintenance

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

Tokyo Institute of Technology (Tokyo Tech) was faced with the challenge of speeding up data access times in parallel with continually improving algorithms that interact with data subsystems. They aimed to achieve this while maintaining optimal power consumption and system efficiency. The institution sought to break away from the conventions of the world's top supercomputers by incorporating elements and design points from containerization, cloud, artificial intelligence (AI), and Big Data.

About Customer

Tokyo Institute of Technology (Tokyo Tech) is the largest institution for higher education in Japan dedicated to science and technology. The institution is known for its innovative approach to research and education in the fields of science and technology. Tokyo Tech is committed to advancing research computing for data-centric infrastructures for the future of research big data but also AI and machine learning. The institution's new TSUBAME3.0 system is a testament to this commitment, showcasing extreme innovation in the area of power consumption and system efficiency.

Solution

To address the challenge, Tokyo Tech implemented a 15.9PB Lustre* parallel file system, composed of three DDN ES14K storage appliances. This solution was integrated into their new TSUBAME3.0 system, which breaks with many of the conventions of the world's top supercomputers. The system incorporates elements and design points from containerization, cloud, artificial intelligence (AI), and Big Data. The solution was designed to speed up data access times in parallel with continually improving algorithms that interact with data subsystems, all while achieving optimal power consumption and system efficiency.

Impact #1	The TSUBAME3.0 system, with its integrated 15.9PB Lustre* parallel file system, is rated at a peak performance of 150GB/s.
Impact #2	The system has established a clear vision of advancing research computing for data-centric infrastructures for the future of research big data but also AI and machine learning.
Impact #3	The implementation of the system creates opportunities to transition to new application areas, such as graph computing and machine learning.

Impact #1

The TSUBAME3.0 system, with its integrated 15.9PB Lustre* parallel file system, is rated at a peak performance of 150GB/s.

Impact #2

The system has established a clear vision of advancing research computing for data-centric infrastructures for the future of research big data but also AI and machine learning.

Impact #3

The implementation of the system creates opportunities to transition to new application areas, such as graph computing and machine learning.

Benefit #1	Peak performance of the system is 150GB/s.

Benefit #1

Peak performance of the system is 150GB/s.

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Overview

Changing Research with a Forward-Looking AI and Big Data Computing Infrastructure

Operational Impact

Quantitative Benefit