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Petaflop Computing for Protein Folding

by Shannon K. Kuntz, Richard C. Murphy, Michael T. Niemier, Jesus Izaguirre, Peter M. Kogge - In Proceedings of the Tenth SIAM Conference on Parallel Processing for Scientific Computing
"... Protein Folding is considered one of today’s most significant “grand challenge ” problems and, together with other computational chemistry problems, has been one of the driving forces for the development of bigger, better, faster supercomputers. IBM is currently proposing to build the “Blue Gene ” [ ..."
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Protein Folding is considered one of today’s most significant “grand challenge ” problems and, together with other computational chemistry problems, has been one of the driving forces for the development of bigger, better, faster supercomputers. IBM is currently proposing to build the “Blue Gene

Porting Ordinary Applications to Blue Gene/Q Supercomputers

by Ketan Maheshwari, Justin M. Wozniak, Timothy G. Armstrong, Daniel S. Katz, T. Andrew Binkowski, Xiaoliang Zhong, Olle Heinonen, Dmitry Karpeyev, Michael Wilde
"... Abstract—Efficiently porting ordinary applications to Blue Gene/Q supercomputers is a significant challenge. Codes are often originally developed without considering advanced archi-tectures and related tool chains. Science needs frequently lead users to want to run large numbers of relatively small ..."
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Abstract—Efficiently porting ordinary applications to Blue Gene/Q supercomputers is a significant challenge. Codes are often originally developed without considering advanced archi-tectures and related tool chains. Science needs frequently lead users to want to run large numbers of relatively small

A Flexible Resource Management Architecture for the Blue Gene/P Supercomputer

by Sam Miller, Mark Megerian, Paul Allen, Tom Budnik
"... Blue Gene R ○ /P is a massively parallel supercomputer intended as the successor to Blue Gene/L. It leverages much of the existing architecture of its predecessor to provide scalability up to a petaflop of peak computing power. The resource management software for such a large parallel system faces ..."
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Blue Gene R ○ /P is a massively parallel supercomputer intended as the successor to Blue Gene/L. It leverages much of the existing architecture of its predecessor to provide scalability up to a petaflop of peak computing power. The resource management software for such a large parallel system faces

The IBM BlueGene (Supercomputer) Project Capability in Science Application (Molecular Dynamics and Protein Folding)

by David Tin Win, Pornsak Budhraja
"... A scientific background on proteins and molecular dynamics precedes a technical description of the DOE's IBM BlueGene/L supercomputer, which is the present and previous No. 1 in the TOP500 supercomputer list (announced November 2005). The system size has doubled, achieving a record Linpack perf ..."
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A scientific background on proteins and molecular dynamics precedes a technical description of the DOE's IBM BlueGene/L supercomputer, which is the present and previous No. 1 in the TOP500 supercomputer list (announced November 2005). The system size has doubled, achieving a record Linpack

Astronomical Real-Time Streaming Signal Processing on a Blue Gene/L Supercomputer

by John W. Romein, Kjeld Van Der Schaaf, P. Chris Broekema, Walther H. Zwart, Ellen Van Meijeren - In ACM Symposium on Parallel Algorithms and Architectures , 2006
"... LOFAR is the first of a new generation of radio telescopes, that combines the signals from many thousands of simple, fixed antennas, rather than from expensive dishes. Its revolutionary design and unprecedented size enables observations in a frequency range that could hardly be observed before, and ..."
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hardware was used. This, and LOFAR’s exceptional real-time, streaming signalprocessing requirements compel the use of a supercomputer. We focus on the LOFAR CEntral Processing facility (CEP), that combines the signals of all LOFAR stations. CEP consists of a 12,288core IBM Blue Gene/L supercomputer

Overview of the IBM Blue Gene/P project

by IBM Blue Gene team , 2008
"... On June 26, 2007, IBM announced the Blue Gene/Pe system as the leading offering in its massively parallel Blue Genet supercomputer line, succeeding the Blue Gene/Le system. The Blue Gene/P system is designed to scale to at least 262,144 quadprocessor nodes, with a peak performance of 3.56 petaflops. ..."
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On June 26, 2007, IBM announced the Blue Gene/Pe system as the leading offering in its massively parallel Blue Genet supercomputer line, succeeding the Blue Gene/Le system. The Blue Gene/P system is designed to scale to at least 262,144 quadprocessor nodes, with a peak performance of 3.56 petaflops

An Overview of the Blue Gene/L System Software Organization

by George Almasi, Ralph Bellofatto, Jose Brunheroto, Calin Cascaval, Jose G. Castanos, José G, Luis Ceze, Paul Crumley, C. Christopher Erway, Joseph Gagliano, Derek Lieber, Xavier Martorell, José E. Moreira, Alda Sanomiya - In Proceedings of Euro-Par 2003 Conference, Lecture Notes in Computer Science , 2003
"... The Blue Gene/L supercomputer will use system-on-a-chip integration and a highly scalable cellular architecture. With 65,536 compute nodes, Blue Gene/L represents a new level of complexity for parallel system software, with specific challenges in the areas of scalability, maintenance and usabilit ..."
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The Blue Gene/L supercomputer will use system-on-a-chip integration and a highly scalable cellular architecture. With 65,536 compute nodes, Blue Gene/L represents a new level of complexity for parallel system software, with specific challenges in the areas of scalability, maintenance

Massively parallel BLAST for the Blue Gene/L

by Huzefa Rangwala, Eric Lantz, Roy Musselman, Kurt Pinnow, Brian Smith, Brian Wallenfelt - In High Availability and Performance Computing Workshop , 2005
"... Abstract — The focus of this article is to explain our research involved with running a parallel implementation of the widely used BLAST algorithm on thousands of processors, available on supercomputers like the IBM Blue Gene/L. Our work involved optimally splitting up the set of queries as well as ..."
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Abstract — The focus of this article is to explain our research involved with running a parallel implementation of the widely used BLAST algorithm on thousands of processors, available on supercomputers like the IBM Blue Gene/L. Our work involved optimally splitting up the set of queries as well

Early Evaluation of IBM BlueGene/P

by S. Alam, R. Barrett, M. Bast, M. R. Fahey, J. Kuehn, C. Mccurdy, J. Rogers, P. Roth, R. Sankaran, J. S. Vetter, P. Worley, W. Yu - In SC , 2008
"... ABSTRACT. BlueGene/P (BG/P) is the second generation BlueGene architecture from IBM, succeeding BlueGene/L (BG/L). BG/P is a system-on-a-chip (SoC) design that uses four PowerPC 450 cores operating at 850 MHz with a double precision, dual pipe floating point unit per core. These chips are connected ..."
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ABSTRACT. BlueGene/P (BG/P) is the second generation BlueGene architecture from IBM, succeeding BlueGene/L (BG/L). BG/P is a system-on-a-chip (SoC) design that uses four PowerPC 450 cores operating at 850 MHz with a double precision, dual pipe floating point unit per core. These chips are connected

Scaling Physics and Material Science Applications on a Massively Parallel Blue Gene/L System

by George Almasi, Gyan Bhanot, Alan Gara, Manish Gupta, James Sexton, Bob Walkup, Vasily V. Bulatov, Andrew W. Cook, Bronis R. De Supinski, James N. Glosli, Jeffrey A. Greenough, Francois Gygi, Alison Kubota, Steve Louis, Thomas E. Spelce, Frederick H. Streitz, Peter L. Williams, Robert K. Yates, Charles Archer, Jose Moreira, Charles Rendleman
"... Blue Gene/L represents a new way to build supercomputers, using a large number of low power processors, together with multiple integrated interconnection networks. Whether real applications can scale to tens of thousands of processors (on a machine like Blue Gene/L) has been an open question. In thi ..."
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Blue Gene/L represents a new way to build supercomputers, using a large number of low power processors, together with multiple integrated interconnection networks. Whether real applications can scale to tens of thousands of processors (on a machine like Blue Gene/L) has been an open question
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