Red Hat, Inc. (NYSE: RHT), the world's leading provider of open source solutions, today announced that Oak Ridge National Laboratory (ORNL), a multiprogram science and technology laboratory managed by the United States Department of Energy, is using Red Hat OpenStack Platform to deliver cloud services in its Compute And Data Environment for Science (CADES). The cloud operations at ORNL have been customized to offer self-serve, Infrastructure-as-a-Service (IaaS) capabilities for ORNL’s staff and is being progressively expanded with platform and analytics services specific to the research needs of the scientific staff. CADES uses the flexible, highly scalable power of Red Hat OpenStack Platform to extend the accessibility of ORNL’s world-class supercomputing environment to a broader set of scientific research projects.
CADES offers a science-focused computing and data-analytics environment that requires underlying flexibility and robustness coupled with a set of powerful tools. A key part of this is a configurable cloud and Red Hat OpenStack Platform offers us exactly that.
Housing some of the world’s most powerful supercomputers, ORNL is at the forefront of research in a variety of areas critical to the Department of Energy - from the physical and environmental sciences to neutron and nuclear science. While the supercomputing platforms provide the processing power and analytics capabilities to handle the most extreme research workloads, ORNL has deployed the on-demand, self-service cloud within CADES to complement the computing and data needs for a broad range of research at the laboratory, ultimately facilitating an on-ramp to leadership computing as an instrument for discovery.
At the start of the CADES development cycle, the Laboratory recognized the need for extreme flexibility and scalability of the underlying technology, as well as a need for open standards and components. By selecting Red Hat OpenStack Platform, ORNL gained the benefits of the community-driven OpenStack cloud framework backed by the enterprise-class support and reliability of Red Hat’s extensive expertise. In 2013, ORNL deployed Red Hat OpenStack Platform to form the cloud component of CADES with the backing of Red Hat’s support infrastructure, including training and Red Hat’s award-winning global support team.
Built on the proven, enterprise-grade backbone of Red Hat Enterprise Linux, Red Hat OpenStack Platform delivers a reliable cloud platform for mission-critical and data-intensive workloads. Hardened from OpenStack community code, Red Hat OpenStack Platform provides the agility to scale and more quickly meet demand without compromising availability, performance or IT security requirements.
CADES extends the leading-edge technologies of ORNL’s supercomputing resources to scientific and computational researchers in an easy-to-consume manner. By emphasizing support for data-driven computing and analytics, as well as cross-platform workflows, ORNL researchers are now able to run a variety of scale and type of workloads depending on the domain requirements. This means that users can spin up clusters, move and process data across facilities and accelerate the process of discovery.
Radhesh Balakrishnan, general manager, OpenStack, Red Hat
“Red Hat prides itself on pairing community innovation with enterprise-grade stability and support, and Red Hat OpenStack Platform is a paradigm for how stable, open innovation should look and function. Oak Ridge National Laboratory’s CADES project takes full advantage of Red Hat’s expertise in upstream community innovation backed by our award-winning support, and we’re pleased that our relationship helps to drive scientific and computational research forward.”
Arjun Shankar, director, Compute and Data Environment for Science (CADES), Oak Ridge National Laboratory
“CADES offers a science-focused computing and data-analytics environment that requires underlying flexibility and robustness coupled with a set of powerful tools. A key part of this is a configurable cloud and Red Hat OpenStack Platform offers us exactly that.”
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