Demo Data from VLDB 2026 / reviewers in the wild / expert
U. Ben Schafer
dblp:127/3132
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
High-performance computing · 45% Hardware accelerators and domain-specific architectures · 20% Emerging computing paradigms · 17% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 50% Bioinformatics and computational biology · 50% |
Topics — the 6 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › scientific computing systems
molecular dynamics simulation |
0.2 | 2 | 2014 | Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer · SC 2014 Hardware support for fine-grained event-driven computation in Anton 2 · ASPLOS 2013 |
Hardware accelerators and domain-specific architectures › scientific computing accelerator
molecular dynamics accelerator |
0.2 | 1 | 2014 | Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer · SC 2014 |
High-performance computing
scientific computing systems |
0.2 | 1 | 2014 | Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer · SC 2014 |
Emerging computing paradigms
event-driven computing |
0.2 | 1 | 2013 | Hardware support for fine-grained event-driven computation in Anton 2 · ASPLOS 2013 |
Bioinformatics and computational biology › molecular informatics › molecular modeling
biomolecular simulation |
0.1 | 1 | 2014 | Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer · SC 2014 |
Computational science and engineering › computational chemistry
molecular simulation |
0.1 | 1 | 2014 | Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer · SC 2014 |
Methods — techniques the papers use, named apart from their topics
event-driven architecture · 0.4application-specific hardware · 0.4event-driven scheduling · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics SupercomputerabstractAnton 2 is a second-generation special-purpose supercomputer for molecular dynamics simulations that achieves significant gains in performance, programmability, and capacity compared to its predecessor, Anton 1. The architecture of Anton 2 is tailored for fine-grained event-driven operation, which improves performance by increasing the overlap of computation with communication, and also allows a wider range of algorithms to run efficiently, enabling many new software-based optimizations. A 512-node Anton 2 machine, currently in operation, is up to ten times faster than Anton 1 with the same number of nodes, greatly expanding the reach of all-atom bio molecular simulations. Anton 2 is the first platform to achieve simulation rates of multiple microseconds of physical time per day for systems with millions of atoms. Demonstrating strong scaling, the machine simulates a standard 23,558-atom benchmark system at a rate of 85 μs/day -- 180 times faster than any commodity hardware platform or general-purpose supercomputer. David E. Shaw, J. P. Grossman, Joseph A. Bank, Brannon Batson, J. Adam Butts, Jack C. Chao, Martin M. Deneroff, Ron O. Dror, Amos Even, Christopher H. Fenton, Anthony Forte, Joseph Gagliardo, Gennette Gill, Brian Greskamp, Richard Ho 0001, Doug Ierardi, Lev Iserovich, Jeffrey Kuskin, Richard H. Larson, Timothy Layman, Li-Siang Lee, Adam K. Lerer, Chester Li, Daniel Killebrew, Kenneth M. Mackenzie, Shark Yeuk-Hai Mok, Mark A. Moraes, Lawrence J. Nociolo, Jon L. Peticolas, Terry Quan, Daniel Ramot, John K. Salmon, Daniele Paolo Scarpazza, U. Ben Schafer, Naseer Siddique, Christopher W. Snyder, Jochen Spengler, Ping Tak Peter Tang, Michael Theobald, Horia Toma, Brian Towles, Benjamin Vitale, Stanley C. Wang, Cliff Young |
SC | 35 |
| 2013 | Hardware support for fine-grained event-driven computation in Anton 2abstractExploiting parallelism to accelerate a computation typically involves dividing it into many small tasks that can be assigned to different processing elements. An efficient execution schedule for these tasks can be difficult or impossible to determine in advance, however, if there is uncertainty as to when each task's input data will be available. Ideally, each task would run in direct response to the arrival of its input data, thus allowing the computation to proceed in a fine-grained event-driven manner. Realizing this ideal is difficult in practice, and typically requires sacrificing flexibility for performance. J. P. Grossman, Jeffrey Kuskin, Joseph A. Bank, Michael Theobald, Ron O. Dror, Doug Ierardi, Richard H. Larson, U. Ben Schafer, Brian Towles, Cliff Young, David E. Shaw |
ASPLOS | 8 |