Fungible and LANL's EMC3 Launch Collaboration to Explore Offloading of Processing to Network and Storage for Complex Simulation Application
SAN JOSE, Calf., March 16, 2021 /PRNewswire/ -- Fungible Inc., a pioneer in data-centric computing, today announced the company is collaborating with the Efficient Mission Centric Computing Consortium (EMC3) at Los Alamos National Laboratory (LANL) to help solve some of the world's most complex physical simulation problems.
The Fungible and LANL collaboration will initially be exploring the scalability of computational NVMe over fabrics and will be demonstrating offload of analytics functions on data produced by extreme scale physical simulation.
"We've identified the bottlenecks within our existing distributed storage architectures. To achieve our desired storage system efficiency targets we are looking to new hardware approaches that better support our storage processing stacks," said Brad Settlemyer, Sr. Scientist in Los Alamos' HPC Design group. "The co-design of software and hardware to support data services and data analysis is integral to meeting our efficiency targets and advancing our national security mission."
Offloading computational tasks to programmable network and storage devices has emerged as a promising path to improve the performance of applications and services running at scale - especially critical for both cloud and HPC data centers. Fungible's distributed approach to offloading and accelerating infrastructure functions, via the Fungible Data Processing Unit™ or Fungible DPU™, represents a powerful change to existing storage and networking concepts.
Settlemyer added that "Los Alamos is happy to see standards-based computational network and storage technology emerging and has high hopes it can be applied to our most pressing and complex simulations for national security needs. We look forward to a fruitful collaboration with Fungible and welcome Fungible to the Efficient Mission Centric Computing Consortium (EMC3) at LANL."
"LANL intends to reduce the processing time of the most complex physical simulation problems from 6 months to 6 days," said Pradeep Sindhu, CEO and Co-Founder of Fungible. "Fungible is confident that the Fungible DPU will be one of the key enablers in achieving this aggressive goal."
The Fungible Storage Cluster is a high performance, secure, scale-out, disaggregated data storage platform, delivering an unprecedented 15M IOPS in a 2RU form factor, scaling linearly to 300M IOPS in a single 40RU rack, and extending further to many racks. The industry-leading performance enables workloads to be consolidated, increasing utilization of storage media, and improving footprint and $/IOPS by at least 3x compared to existing software-defined storage solutions.
About Los Alamos National Laboratory
Los Alamos National Laboratory, a multidisciplinary research institution engaged in strategic science on behalf of national security, is operated by Triad a public service oriented, national security science organization equally owned by its three founding members: Battelle Memorial Institute (Battelle), The Texas A&M University System (TAMUS) and The Regents of the University of California (UC) for the Department of Energy's National Nuclear Security Administration.
Los Alamos enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health and global security concerns.
About Fungible Inc.
Silicon Valley-based Fungible is revolutionizing the performance, economics, reliability and security of scale-out data centers. Visit Fungible to learn more. Follow us on Twitter and LinkedIn.
Fungible, Fungible Data Processing Unit, Fungible DPU, Fungible Data Center and TrueFabric are registered trademarks of Fungible Inc. All registered or unregistered trademarks are the sole property of their respective owners.
Media Contact:
Gary Bird
Fungible Media
831.401.3175
[email protected]
SOURCE Fungible
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