NEWS
Tags: 

Cray and NERSC partnership to drive advanced AI development

Cray has announced the Company has joined the Big Data Center (BDC) at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC).

The collaboration between the two organisations highlights Cray’s commitment to leverage its supercomputing expertise, technologies, and best practices to advance the adoption of Artificial Intelligence (AI), deep learning, and data-intensive computing.

The BDC at NERSC was established with a goal of addressing the Department of Energy’s leading data-intensive science problems, harnessing the performance and scale of the Cray XC40 ‘Cori’ supercomputer at NERSC. The collaboration is focused on three fundamental areas that are key to unlocking the capabilities required for the most challenging data-intensive workflows:

•             Advancing the state-of-the-art in scalable, deep learning training algorithms, which is critical to the ability to train models as quickly as possible in an environment of ever-increasing data sizes and complexity;

•             Developing a framework for automated hyper-parameter tuning, which provides optimised training of deep learning models and maximises a model’s predictive accuracy;

•             Exploring the use of deep learning techniques and applications against a diverse set of important scientific use cases, such as genomics and climate change, which broadens the range of scientific disciplines where advanced AI can have an impact.

‘We are really excited to have Cray join the Big Data Center,’ said Prabhat, director of the Big Data Center, and group lead for data and analytics services at NERSC. ‘Cray’s deep expertise in systems, software, and scaling is critical in working towards the BDC mission of enabling capability applications for data-intensive science on Cori. Cray and NERSC, working together with Intel and our IPCC academic partners, are well positioned to tackle performance and scaling challenges of Deep Learning.’

‘Deep learning is increasingly dependent on high performance computing, and as the leader in supercomputing, Cray is focused on collaborating with the innovators in AI to address present and future challenges for our customers,’ said Per Nyberg, Cray’s senior director of artificial intelligence and analytics. ‘Joining the Big Data Center at NERSC is an important step forward in fostering the advancement of deep learning for science and enterprise, and is another example of our continued R&D investments in AI.’

Other tags: 
Company: 
Twitter icon
Google icon
Del.icio.us icon
Digg icon
LinkedIn icon
Reddit icon
e-mail icon
Feature

Building a Smart Laboratory 2018 highlights the importance of adopting smart laboratory technology, as well as pointing out the challenges and pitfalls of the process

Feature

Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory

Feature

This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.

Feature

This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value

Feature

This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment