2021 - IEEE Fellow For leadership in the design and use of large-scale computing systems
2016 - ACM Senior Member
2006 - ACM Gordon Bell Prize Large-scale Electronic Structure Calculations of High-Z Metals on the BlueGene/L Platform
His scientific interests lie mostly in Parallel computing, Scalability, Distributed computing, Supercomputer and Performance prediction. His work on Multi-core processor as part of general Parallel computing research is often related to Energy, thus linking different fields of science. Bronis R. de Supinski has researched Scalability in several fields, including Critical path method, Data mining and File system.
His work on Software fault tolerance as part of his general Distributed computing study is frequently connected to Context, thereby bridging the divide between different branches of science. His study in Supercomputer is interdisciplinary in nature, drawing from both Provisioning and Computational science. His Performance prediction study integrates concerns from other disciplines, such as Artificial neural network, Machine learning, Artificial intelligence, Architectural model and Parallel algorithm.
His primary areas of investigation include Parallel computing, Distributed computing, Scalability, Supercomputer and Operating system. The concepts of his Parallel computing study are interwoven with issues in Scheduling, Software and Programming paradigm. Bronis R. de Supinski has included themes like Correctness and Interface in his Distributed computing study.
In his research on the topic of Scalability, Computer network is strongly related with File system. He merges Supercomputer with Energy in his study. His Shared memory research incorporates themes from Programming language and Thread.
Bronis R. de Supinski mainly focuses on Parallel computing, Supercomputer, Distributed computing, Programming language and Programming paradigm. His Parallel computing study combines topics from a wide range of disciplines, such as Computer architecture and Software portability. The Supercomputer study combines topics in areas such as Workload and Provisioning.
His studies in Distributed computing integrate themes in fields like Scalability and Computation. His Programming language research includes themes of Task and Interoperability. The various areas that Bronis R. de Supinski examines in his Programming paradigm study include Field-programmable gate array, Software, Task and Center of excellence.
His primary areas of study are Distributed computing, Parallel computing, Supercomputer, CUDA and Scheduling. He studies Distributed computing, focusing on Fault tolerance in particular. His study looks at the relationship between Parallel computing and fields such as Programming paradigm, as well as how they intersect with chemical problems.
His work investigates the relationship between Supercomputer and topics such as Provisioning that intersect with problems in Computer hardware and Power management. He combines subjects such as Virtual function, Pipeline, Memory bandwidth, Cyclomatic complexity and Speedup with his study of CUDA. His work often combines Power budget and Scalability studies.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Design, Modeling, and Evaluation of a Scalable Multi-level Checkpointing System
Adam Moody;Greg Bronevetsky;Kathryn Mohror;Bronis R. de Supinski.
ieee international conference on high performance computing data and analytics (2010)
Adagio: making DVS practical for complex HPC applications
Barry Rountree;David K. Lownenthal;Bronis R. de Supinski;Martin Schulz.
international conference on supercomputing (2009)
Methods of inference and learning for performance modeling of parallel applications
Benjamin C. Lee;David M. Brooks;Bronis R. de Supinski;Martin Schulz.
acm sigplan symposium on principles and practice of parallel programming (2007)
Dynamic Software Testing of MPI Applications with Umpire
Jeffrey S. Vetter;Bronis R. de Supinski.
conference on high performance computing (supercomputing) (2000)
Prediction models for multi-dimensional power-performance optimization on many cores
Matthew Curtis-Maury;Ankur Shah;Filip Blagojevic;Dimitrios S. Nikolopoulos.
international conference on parallel architectures and compilation techniques (2008)
An approach to performance prediction for parallel applications
Engin Ipek;Bronis R. de Supinski;Martin Schulz;Sally A. McKee.
european conference on parallel processing (2005)
Bounding energy consumption in large-scale MPI programs
Barry Rountree;David K. Lowenthal;Shelby Funk;Vincent W. Freeh.
conference on high performance computing (supercomputing) (2007)
A regression-based approach to scalability prediction
Bradley J. Barnes;Barry Rountree;David K. Lowenthal;Jaxk Reeves.
international conference on supercomputing (2008)
Soft error vulnerability of iterative linear algebra methods
Greg Bronevetsky;Bronis de Supinski.
international conference on supercomputing (2008)
Beyond DVFS: A First Look at Performance under a Hardware-Enforced Power Bound
Barry Rountree;Dong H. Ahn;Bronis R. de Supinski;David K. Lowenthal.
international parallel and distributed processing symposium (2012)
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