Cloud Computing Concepts and Applications at MIT Lincoln Laboratory HPEC Conference
Explore the cutting-edge advancements in cloud computing at the MIT Lincoln Laboratory HPEC Conference, including topics such as data intensive computing, compute architecture for large-scale data analysis, and the development of scalable knowledge spaces on the cloud. Learn about the key design parameters, performance metrics, and community collaborations shaping the future of cloud technologies.
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Presentation Transcript
Session 3: Cloud Computing Albert Reuther/ MIT Lincoln Laboratory HPEC Conference 16 September 2010 MIT Lincoln Laboratory HPEC-1
Cloud Computing Concepts Data Intensive Computing Compute architecture for large scale data analysis Billions of records/day, trillions of stored records, petabytes of storage o Google File System 2003 o Google MapReduce 2004 o Google BigTable 2006 Design Parameters Performance and scale Optimized for ingest, query and analysis Co-mingled data Relaxed data model Simplified programming Community: Utility Computing Compute services for outsourcing IT Concurrent, independent users operating across millions of records and terabytes of data o IT as a Service o Infrastructure as a Service (IaaS) o Platform as a Service (PaaS) o Software as a Service (SaaS) Design Parameters Isolation of user data and computation Portability of data with applications Hosting traditional applications Lower cost of ownership Capacity on demand Community: MIT Lincoln Laboratory HPEC-2
Session 3: Cloud Computing Invited: Accelerating Data Intensive Applications with Flash Allan Snavely / San Diego Supercomputing Center Invited: Cloud Computing for Processing Large Volumes of Data Patrick Dreher / Renaissance Computing Institute Break Persistent Surveillance Supercomputing in a Can Jeremy Kepner, William Arcand, Chansup Byun, Bill Bergeron, Matthew Hubbell, Andrew McCabe, Peter Michaleas, Julie Mullen and Albert Reuther / MIT Lincoln Laboratory Building a Scalable Knowledge Space on the Cloud: Initial Integration and Evaluation Delsey Sherrill, Jonathan Kurz and Craig McNally / MIT Lincoln Laboratory MIT Lincoln Laboratory HPEC-3
Poster / Demo B: Cloud Technologies and Applications Albert Reuther / MIT Lincoln Laboraroty HPEC Conference 15 September 2010 MIT Lincoln Laboratory HPEC-4
Cloud Technologies and Applications Performance Characterization of the Tile Processor Architecture: Lessons Learned Eric Grobelny, Jim Passwater and Andrew White / Honeywell The MIST, a local, secure cloud context and 802.11s testbed Gregory Dempsey, Ronald Feher and Lindsay Gordon / USMA Kurt Keville / MIT Development of a Real-Time Parallel UHF SAR Image Processor Matthew Alexander, Michael Vai, Thomas Emberley, Stephen Mooney and Joseph Rizzari / MIT Lincoln Laboratory Automated Software Cache Management William Lundgren, Kerry Barnes and James Steed / Gedae, Inc. Dependable Multiprocessor (DM) Implementation for Nano-satellite and CubeSat Applications Matthew Clark, John Samson, Jr., / Honeywell Combining Scripting Environments and Sourcery VSIPL++ for Rapid Prototyping Stefan Seefeld, Brooks Moses, Don McCoy and Justin Voo / CodeSourcery, Inc. Multicore, Multithreaded, and/or Multi- GPU-Kernel VSIPL Standardization, Implementation, and Programming Impacts: Syntax, Semantics, Models Anthony Skjellum / RunTime Computing Solutions, LLC Mnemosyne: A Tool for Temporal Memory Access Analysis in HPC Applications Shahrukh Tarapore and Matthew Burkholder / Lockheed Martin Development of a Component-Based Framework using VSIPL++ Alan Ward, Roger Winstanley and Mark Hayman / Northrop Grumman Deploying an ISR Cloud Platform Geert Wenes and Dan Poznanovic / Cray, Inc. Improving FFTW Benchmark to Measure Multi-core Processor Performance William Pilaud / Curtiss Wright Controls Embedded Computing 1 7 2 8 3 9 4 10 11 5 6 MIT Lincoln Laboratory HPEC-5
