NERSCPowering Scientific Discovery Since 1974

Harvey Wasserman

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Harvey J. Wasserman , Ph.D.
HPC Consultant ,
Phone: (510) 486-4750 , Fax: (510) 486-4316
1 Cyclotron Road
Mail Stop 943-256
Berkeley, CA 94720

Biographical Sketch

Consultant Harvey Wasserman has been involved in workload characterization, benchmarking, and system evaluation at NERSC and at Los Alamos National Laboratory for over 24 years.  He helps run NERSC's requirements gathering workshops and also helps to organize the SC supercomputer conference series.  One of his interests at NERSC is in tracking down and publicizing recent scientific discoveries made by NERSC users.

Journal Articles

J. Levesque, J. Larkin, M. Foster, J. Glenski, G. Geissler, S. Whalen, B. Waldecker, J. Carter, D. Skinner, H. He, H. Wasserman, J. Shalf, H. Shan, “Understanding and mitigating multicore performance issues on the AMD opteron architecture”, March 1, 2007, LBNL 62500

Over the past 15 years, microprocessor performance has doubled approximately every 18 months through increased clock rates and processing efficiency. In the past few years, clock frequency growth has stalled, and microprocessor manufacturers such as AMD have moved towards doubling the number of cores every 18 months in order to maintain historical growth rates in chip performance. This document investigates the ramifications of multicore processor technology on the new Cray XT4systems based on AMD processor technology. We begin by walking through the AMD single-core and dual-core and upcoming quad-core processor architectures. This is followed by a discussion of methods for collecting performance counter data to understand code performance on the Cray XT3and XT4systems. We then use the performance counter data to analyze the impact of multicore processors on the performance of microbenchmarks such as STREAM, application kernels such as the NAS Parallel Benchmarks, and full application codes that comprise the NERSC-5 SSP benchmark suite. We explore compiler options and software optimization techniques that can mitigate the memory bandwidth contention that can reduce computing efficiency on multicore processors. The last section provides a case study of applying the dual-core optimizations to the NAS Parallel Benchmarks to dramatically improve their performance.1

 

Conference Papers

Keith R. Jackson, Ramakrishnan, Muriki, Canon, Cholia, Shalf, J. Wasserman, Nicholas J. Wright, “Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud”, CloudCom, Bloomington, Indiana, January 1, 2010, 159-168,

Jonathan Carter, Yun (Helen) He, John Shalf, Hongzhang Shan, Erich Strohmaier, and Harvey Wasserman, “The Performance Effect of Multi-Core on Scientific Applications”, Cray User Group 2007, May 2007, LBNL 62662

The historical trend of increasing single CPU performance has given way to roadmap of increasing core count. The challenge of effectively utilizing these multi- core chips is just starting to be explored by vendors and application developers alike. In this study, we present some performance measurements of several complete scientific applications on single and dual core Cray XT3 and XT4 systems with a view to characterizing the effects of switching to multi-core chips. We consider effects within a node by using applications run at low concurrencies, and also effects on node- interconnect interaction using higher concurrency results. Finally, we construct a simple performance model based on the principle on-chip shared resource—memory bandwidth—and use this to predict the performance of the forthcoming quad-core system.

 

Presentation/Talks

Richard A. Gerber, Harvey Wasserman, NERSC Requirements Reviews, February 12, 2013,

An update on the NERSC Requirements Reviews at NUG 2013. Richard Gerber and Harvey Wasserman, NERSC>

J. Shalf, K. Antypas, H.J. Wasserman, Recent Workload Characterization Activities at NERSC, Santa Fe Workshop, January 1, 2008,

Jonathan Carter, Helen He*, John Shalf, Erich Strohmaier, Hongzhang Shan, and Harvey Wasserman, The Performance Effect of Multi-Core on Scientific Applications, Cray User Group 2007, May 2007,

Reports

Richard A. Gerber, Harvey J. Wasserman, “Large Scale Computing and Storage Requirements for Nuclear Physics”, Workshop, March 26, 2012, LBNL LBNL-5355E

Report of the user requirements workshop for lattice gauge theory and nuclear physics computation at NERSC that took place May 26, 2011

Richard A. Gerber, Harvey J. Wasserman, “Large Scale Computing and Storage Requirements for Advanced Computational Science Research”, Workshop, January 2012, LBNL LBNL-5249E

Richard A. Gerber, Harvey J. Wasserman, “Large Scale Computing and Storage Requirements for Fusion Energy Sciences”, Workshop, December 2011,

Richard A. Gerber, Harvey J. Wasserman, “Large Scale Computing and Storage Requirements for Basic Energy Sciences”, Workshop, June 10, 2011, LBNL LBNL-4809E

Richard A. Gerber, Harvey J. Wasserman, “Large Scale Computing and Storage Requirements for High Energy Physics”, Workshop, November 15, 2010,

Richard A. Gerber, Harvey J. Wasserman, “Large Scale Computing and Storage Requirements for Biological and Environmental Research”, Workshop, October 19, 2009, LBNL LBNL-2710E

K. Antypas, J. Shalf, H. Wasserman, “NERSC-6 Workload Analysis and Benchmark Selection Process”, January 1, 2008,