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Publications

Over the years, researchers in the Performance and Algorithms Research Group have codified their research into papers that have been published in a variety of journals or conference proceedings.  Below is a sampling of our recent work.

2017

Samuel Williams, Introduction to the Roofline Model, Roofline Training, November 2017,

Philip C. Roth, Hongzhang Shan, David Riegner, Nikolas Antolin, Sarat Sreepathi, Leonid Oliker, Samuel Williams, Shirley Moore, Wolfgang Windl, "Performance Analysis and Optimization of the RAMPAGE Metal Alloy Potential Generation Software", SIGPLAN International Workshop on Software Engineering for Parallel Systems (SEPS), October 2017,

Jack Deslippe, Doug Doerfler, Brandon Cook, Tareq Malas, Samuel Williams, Sudip Dosanjh, "Optimizing science applications for the Cori, Knights Landing, System at NERSC", Advances in Parallel Computing, New Frontiers in High Performance Computing and Big Data, August 2017, 30, doi: 10.3233/978-1-61499-816-7-235

Hongzhang Shan, Samuel Williams, Calvin Johnson, Kenneth McElvain, "A Locality-based Threading Algorithm for the Configuration-Interaction Method", Parallel and Distributed Scientific and Engineering Computing (PDSEC), June 2017,

Bryce Adelstein Lelbach, Hans Johansen, Samuel Williams, "Solving Large Quantities of Small Matrix Problems on Cache-Coherent Many-Core SIMD Architectures", Parallel and Distributed Scientific and Engineering Computing (PDSEC), June 2017,

Brandon Cook, Thorsten Kurth, Brian Austin, Samuel Williams, Jack Deslippe, "Performance Variability on Xeon Phi", Intel Xeon Phi Users Group (IXPUG), June 2017,

Thorsten Kurth, William Arndt, Taylor Barnes, Brandon Cook, Jack Deslippe, Doug Doerfler, Brian Friesen, Yun (Helen) He, Tuomas Koskela, Mathieu Lobet, Tareq Malas, Leonid Oliker, Andrey Ovsyannikov, Samuel Williams, Woo-Sun Yang, and Zhengji Zhao, "Analyzing Performance on Selected NESAP Applications on the Cori HPC System", Intel Xeon Phi Users Group (IXPUG), June 2017,

Ariful Azad, Aydin Buluc, "Towards a GraphBLAS Library in Chapel", IPDPS Workshops, Orlando, FL, May 2017,

Aydin Buluc, Tim Mattson, Scott McMillan, Jose Moreira, Carl Yang, "Design of the GraphBLAS API for C", IEEE Workshop on Graph Algorithm Building Blocks, IPDPSW, 2017,

Ariful Azad, Aydin Buluc, "A work-efficient parallel sparse matrix-sparse vector multiplication algorithm", IEEE International Parallel & Distributed Processing Symposium (IPDPS), Orlando, FL, May 2017,

Ariful Azad, Mathias Jacquelin, Aydin Buluc, Esmond G. Ng, "The Reverse Cuthill-McKee Algorithm in Distributed-Memory", IEEE International Parallel & Distributed Processing Symposium (IPDPS), Orlando, FL, May 2017,

Nathan Zhang, Michael Driscoll, Armando Fox, Charles Markley, Samuel Williams, Protonu Basu, "Snowflake: A Lightweight Portable Stencil DSL", High-level Parallel Programming Models and Supportive Environments (HIPS), May 2017,

Bei Wang, Stephane Ethier, William Tang, Khaled Ibrahim, Kamesh Madduri, Samuel Williams, Leonid Oliker, "Modern Gyrokinetic Particle-in-cell Simulation of Fusion Plasmas on Top Supercomputers", International Journal of High-Performance Computing Applications (IJHPCA), May 2017, doi: https://doi.org/10.1177/1094342017712059

Protonu Basu, Samuel Williams, Brian Van Straalen, Leonid Oliker, Phillip Colella, Mary Hall, "Compiler-Based Code Generation and Autotuning for Geometric Multigrid on GPU-Accelerated Supercomputers", Parallel Computing (PARCO), April 2017, doi: 10.1016/j.parco.2017.04.002

Khaled Z. Ibrahim, Evgeny Epifanovsky, Samuel Williams, Anna I. Krylov, "Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends", Journal of Parallel and Distributed Computing (JPDC), February 2017, doi: 10.1016/j.jpdc.2017.02.010

Esmond Ng, Katherine J. Evans, Peter Caldwell, Forrest M. Hoffman, Charles Jackson, Kerstin Van Dam, Ruby Leung, Daniel F. Martin, George Ostrouchov, Raymond Tuminaro, Paul Ullrich, Stefan Wild, Samuel Williams, "Advances in Cross-Cutting Ideas for Computational Climate Science (AXICCS)", January 2017, doi: 10.2172/1341564

2016

S.V. Venkatakrishnan, Jeffrey Donatelli, Dinesh Kumar, Abhinav Sarje, Sunil K. Sinha, Xiaoye S. Li, Alexander Hexemer, "A Multi-slice Simulation Algorithm for Grazing-Incidence Small-Angle X-ray Scattering", Journal of Applied Crystallography, December 2016, 49-6, doi: 10.1107/S1600576716013273

Grazing-incidence small-angle X-ray scattering (GISAXS) is an important technique in the characterization of samples at the nanometre scale. A key aspect of GISAXS data analysis is the accurate simulation of samples to match the measurement. The distorted-wave Born approximation (DWBA) is a widely used model for the simulation of GISAXS patterns. For certain classes of sample such as nanostructures embedded in thin films, where the electric field intensity variation is significant relative to the size of the structures, a multi-slice DWBA theory is more accurate than the conventional DWBA method. However, simulating complex structures in the multi-slice setting is challenging and the algorithms typically used are designed on a case-by-case basis depending on the structure to be simulated. In this paper, an accurate algorithm for GISAXS simulations based on the multi-slice DWBA theory is presented. In particular, fundamental properties of the Fourier transform have been utilized to develop an algorithm that accurately computes the average refractive index profile as a function of depth and the Fourier transform of the portion of the sample within a given slice, which are key quantities required for the multi-slice DWBA simulation. The results from this method are compared with the traditionally used approximations, demonstrating that the proposed algorithm can produce more accurate results. Furthermore, this algorithm is general with respect to the sample structure, and does not require any sample-specific approximations to perform the simulations.

Mark Adams, Samuel Williams, HPGMG BoF - Introduction, HPGMG BoF, Supercomputing, November 2016,

Samuel Williams, HPGMG on the Knights Landing Processor, HPGMG BoF, Supercomputing, November 2016,

Samuel Williams, HPGMG Benchmark, Top500 BoF, Supercomputing, November 2016,

William Tang, Bei Wang, Stephane Ethier, Grzegorz Kwasniewski, Torsten Hoefler, Khaled Z. Ibrahim4, Kamesh Madduri, Samuel Williams, Leonid Oliker, Carlos Rosales-Fernandez, Tim Williams, "Extreme Scale Plasma Turbulence Simulations on Top Supercomputers Worldwide", Supercomputing, November 2016,

Taylor Barnes, Brandon Cook, Jack Deslippe, Douglas Doerfler, Brian Friesen, Yun (Helen) He, Thorsten Kurth, Tuomas Koskela, Mathieu Lobet, Tareq Malas, Leonid Oliker, Andrey Ovsyannikov, Abhinav Sarje, Jean-Luc Vay, Henri Vincenti, Samuel Williams, Pierre Carrier, Nathan Wichmann, Marcus Wagner, Paul Kent, Christopher Kerr, John Dennis, "Evaluating and Optimizing the NERSC Workload on Knights Landing", Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November 2016,

Hongzhang Shan, Samuel Williams, Yili Zheng, Weiqun Zhang, Bei Wang, Stephane Ethier, Zhengji Zhao, "Experiences of Applying One-Sided Communication to Nearest-Neighbor Communication", PGAS Applications Workshop (PAW), November 2016,

Ariful Azad, Grey Ballard, Aydin Buluc, James Demmel, Laura Grigori, Oded Schwartz, Sivan Toledo, Samuel Williams, "Exploiting multiple levels of parallelism in sparse matrix-matrix multiplication", SIAM Journal on Scientific Computing, 38(6), C624–C651, November 2016, doi: 10.1137/15M104253X

Nicholas Chaimov, Khaled Z. Ibrahim, Samuel Williams, Costin Iancu, "Reaching Bandwidth Saturation Using Transparent Injection Parallelization", International Journal of High Performance Computing Applications (IJHPCA), November 2016, doi: 10.1177/1094342016672720

Hasan Metin Aktulga, Md. Afibuzzaman, Samuel Williams, Aydın Buluc, Meiyue Shao, Chao Yang, Esmond G. Ng, Pieter Maris, James P. Vary, "A High Performance Block Eigensolver for Nuclear Configuration Interaction Calculations", IEEE Transactions on Parallel and Distributed Systems (TPDS), November 2016, doi: 10.1109/TPDS.2016.2630699

Zhaoyi Meng, Alice Koniges, Yun (Helen) He, Samuel Williams, Thorsten Kurth, Brandon Cook, Jack Deslippe, and Andrea L. Bertozzi, "OpenMP Parallelization and Optimization of Graph-Based Machine Learning Algorithms", 12th International Workshop on OpenMP (iWOMP), October 2016, doi: 10.1007/978-3-319-45550-1_2

Pieter Ghysels, Xiaoye S. Li, François-Henry Rouet, Samuel Williams, Artem Napov, "An Efficient Multicore Implementation of a Novel HSS-Structured Multifrontal Solver Using Randomized Sampling", SIAM J. Sci. Comput. 38-5, pp. S358-S384, October 2016, doi: 10.1137/15M1010117

Jeremy Kepner, Peter Aaltonen, David Bader, Aydin Buluç, Franz Franchetti, John Gilbert, Dylan Hutchison, Manoj Kumar, Andrew Lumsdaine, Henning Meyerhenke, Scott McMillan, José Moreira, John Owens, Carl Yang, Marcin Zalewski, Timothy Mattson., "Mathematical foundations of the GraphBLAS", IEEE High Performance Extreme Computing (HPEC), September 1, 2016,

Abhinav Sarje, Xiaoye S Li, Nicholas Wright, "Achieving High Parallel Efficiency on Modern Processors for X-ray Scattering Data Analysis", International Workshop on Multicore Software Engineering at EuroPar, 2016,

Khaled Z. Ibrahim, Evgeny Epifanovsky, Samuel Williams, Anna I. Krylov, "Cross-scale Efficient Tensor Contractions for Coupled Cluster Computations Through Multiple Programming Model Backends", LBNL. - Report Number: LBNL-1005853, July 1, 2016,

Ariful Azad, Bartek Rajwa, Alex Pothen, "flowVS: Channel-Speci c Variance Stabilization in Flow Cytometry", BMC Bioinformatics, June 2016,

Douglas Doerfer, Jack Deslippe, Samuel Williams, Leonid Oliker, Brandon Cook, Thorsten Kurth, Mathieu Lobet, Tareq Malas, Jean-Luc Vay, and Henri Vincenti, "Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor", Intel Xeon Phi User Group Workshop (IXPUG), June 2016,

Ariful Azad, Aydın Buluç, "A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs", Parallel Computing, June 2016,

Ariful Azad, Aydin Buluç, "Distributed-Memory Algorithms for Maximum Cardinality Matching in Bipartite Graphs", IEEE International Parallel & Distributed Processing Symposium (IPDPS), May 2016,

Penporn Koanantakool, Ariful Azad, Aydın Buluç, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, Katherine Yelick, "Communication-Avoiding Parallel Sparse-Dense Matrix-Matrix Multiplication", IEEE International Parallel & Distributed Processing Symposium (IPDPS), May 2016,

Ariful Azad, Aydın Buluç, Alex Pothen, "Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting", IEEE Transactions on Parallel and Distributed Systems (TPDS), May 2016,

Abhinav Sarje, Douglas W. Jacobsen, Samuel W. Williams, Todd Ringler, Leonid Oliker, "Exploiting Thread Parallelism for Ocean Modeling on Cray XC Supercomputers", Cray User Group (CUG), London, UK, May 2016,

Abhinav Sarje, Exploiting Thread Parallelism for Ocean Modeling on Cray XC Supercomputers, Cray Users Group (CUG), May 12, 2016,

Ariful Azad, Aydın Buluç, Distributed-memory algorithms for cardinality matching using matrix algebra, SIAM Conference on Parallel Processing for Scientific Computing (PP), Paris, France, April 2016,

J. R. Jones, F.-H. Rouet, K. V. Lawler, E. Vecharynski, K. Z. Ibrahim, S. Williams, B. Abeln, C. Yang, C. W. McCurdy, D. J. Haxton, X. S. Li, T. N. Rescigno, "An efficient basis set representation for calculating electrons in molecules", Journal of Molecular Physics, 2016, doi: 10.1080/00268976.2016.1176262

The method of McCurdy, Baertschy, and Rescigno, J. Phys. B, 37, R137 (2004) is generalized to obtain a straightforward, surprisingly accurate, and scalable numerical representation for calculating the electronic wave functions of molecules. It uses a basis set of product sinc functions arrayed on a Cartesian grid, and yields 1 kcal/mol precision for valence transition energies with a grid resolution of approximately 0.1 bohr. The Coulomb matrix elements are replaced with matrix elements obtained from the kinetic energy operator. A resolution-of-the-identity approximation renders the primitive one- and two-electron matrix elements diagonal; in other words, the Coulomb operator is local with respect to the grid indices. The calculation of contracted two-electron matrix elements among orbitals requires only O(N log(N)) multiplication operations, not O(N^4), where N is the number of basis functions; N = n^3 on cubic grids. The representation not only is numerically expedient, but also produces energies and properties superior to those calculated variationally. Absolute energies, absorption cross sections, transition energies, and ionization potentials are reported for one- (He^+, H_2^+ ), two- (H_2, He), ten- (CH_4) and 56-electron (C_8H_8) systems.

The method of McCurdy, Baertschy, and Rescigno, J. Phys. B, 37, R137 (2004) is generalized to obtain a straightforward, surprisingly accurate, and scalable numerical representation for calculating the electronic wave functions of molecules. It uses a basis set of product sinc functions arrayed on a Cartesian grid, and yields 1 kcal/mol precision for valence transition energies with a grid resolution of approximately 0.1 bohr. The Coulomb matrix elements are replaced with matrix elements obtained from the kinetic energy operator. A resolution-of-the-identity approximation renders the primitive one- and two-electron matrix elements diagonal; in other words, the Coulomb operator is local with respect to the grid indices. The calculation of contracted two-electron matrix elements among orbitals requires only O(N log(N)) multiplication operations, not O(N^4), where N is the number of basis functions; N = n^3 on cubic grids. The representation not only is numerically expedient, but also produces energies and properties superior to those calculated variationally. Absolute energies, absorption cross sections, transition energies, and ionization potentials are reported for one- (He^+, H_2^+ ), two- (H_2, He), ten- (CH_4) and 56-electron (C_8H_8) systems.The method of McCurdy, Baertschy, and Rescigno, J. Phys. B, 37, R137 (2004) is generalized to obtain a straightforward, surprisingly accurate, and scalable numerical representation for calculating the electronic wave functions of molecules. It uses a basis set of product sinc functions arrayed on a Cartesian grid, and yields 1 kcal/mol precision for valence transition energies with a grid resolution of approximately 0.1 bohr. The Coulomb matrix elements are replaced with matrix elements obtained from the kinetic energy operator. A resolution-of-the-identity approximation renders the primitive one- and two-electron matrix elements diagonal; in other words, the Coulomb operator is local with respect to the grid indices. The calculation of contracted two-electron matrix elements among orbitals requires only O(N log(N)) multiplication operations, not O(N^4), where N is the number of basis functions; N = n^3 on cubic grids. The representation not only is numerically expedient, but also produces energies and properties superior to those calculated variationally. Absolute energies, absorption cross sections, transition energies, and ionization potentials are reported for one- (He^+, H_2^+ ), two- (H_2, He), ten- (CH_4) and 56-electron (C_8H_8) systems.

 

The method of McCurdy, Baertschy, and Rescigno, J. Phys. B, 37, R137 (2004) is generalized to obtain a straightforward, surprisingly accurate, and scalable numerical representation for calculating the electronic wave functions of molecules. It uses a basis set of product sinc functions arrayed on a Cartesian grid, and yields 1 kcal/mol precision for valence transition energies with a grid resolution of approximately 0.1 bohr. The Coulomb matrix elements are replaced with matrix elements obtained from the kinetic energy operator. A resolution-of-the-identity approximation renders the primitive one- and two-electron matrix elements diagonal; in other words, the Coulomb operator is local with respect to the grid indices. The calculation of contracted two-electron matrix elements among orbitals requires only O(N log(N)) multiplication operations, not O(N^4), where N is the number of basis functions; N = n^3 on cubic grids. The representation not only is numerically expedient, but also produces energies and properties superior to those calculated variationally. Absolute energies, absorption cross sections, transition energies, and ionization potentials are reported for one- (He^+, H_2^+ ), two- (H_2, He), ten- (CH_4) and 56-electron (C_8H_8) systems.The method of McCurdy, Baertschy, and Rescigno, J. Phys. B, 37, R137 (2004) is generalized to obtain a straightforward, surprisingly accurate, and scalable numerical representation for calculating the electronic wave functions of molecules. It uses a basis set of product sinc functions arrayed on a Cartesian grid, and yields 1 kcal/mol precision for valence transition energies with a grid resolution of approximately 0.1 bohr. The Coulomb matrix elements are replaced with matrix elements obtained from the kinetic energy operator. A resolution-of-the-identity approximation renders the primitive one- and two-electron matrix elements diagonal; in other words, the Coulomb operator is local with respect to the grid indices. The calculation of contracted two-electron matrix elements among orbitals requires only O(N log(N)) multiplication operations, not O(N^4), where N is the number of basis functions; N = n^3 on cubic grids. The representation not only is numerically expedient, but also produces energies and properties superior to those calculated variationally. Absolute energies, absorption cross sections, transition energies, and ionization potentials are reported for one- (He^+, H_2^+ ), two- (H_2, He), ten- (CH_4) and 56-electron (C_8H_8) systems.

Samuel Williams, Mark Adams, Brian Van Straalen, Performance Portability in Hybrid and Heterogeneous Multigrid Solvers, Copper Moutain, March 2016,

2015

Abhinav Sarje, Particle Swarm Optimization, DUNE Wire-Cell Reconstruction Summit, December 2015,

Samuel Williams, X-TUNE, X-Stack PI Meeting, December 2015,

Evangelos Georganas, Aydın Buluç, Jarrod Chapman, Steven Hofmeyr,
Chaitanya Aluru, Rob Egan, Leonid Oliker, Daniel Rokhsar, Katherine Yelick,
"HipMer: An Extreme-Scale De Novo Genome Assembler", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), November 19, 2015,

Samuel Williams, 4th Order HPGMG-FV Implementation, HPGMG BoF, Supercomputing, November 2015,

Vladimir Marjanovic, HPC Benchmarking, HPGMG BoF, Supercomputing, November 2015,

Hongzhang Shan, Kenneth McElvain, Calvin Johnson, Samuel Williams, W. Erich Ormand, "Parallel Implementation and Performance Optimization of the Configuration-Interaction Method", Supercomputing (SC), November 2015, doi: 10.1145/2807591.2807618

Hongzhang Shan, Samuel Williams, Yili Zheng, Amir Kamil, Katherine Yelick, "Implementing High-Performance Geometric Multigrid Solver With Naturally Grained Messages", 9th International Conference on Partitioned Global Address Space Programming Models (PGAS), September 2015,

Ariful Azad, Aydin Buluc, "Distributed-Memory Algorithms for Maximal Cardinality Matching using Matrix Algebra", IEEE Cluster, Chicago, IL, September 2015,

Alex Druinsky, Pieter Ghysels, Xiaoye S. Li, Osni Marques, Samuel Williams, Andrew Barker, Delyan Kalchev, Panayot Vassilevski, "Comparative Performance Analysis of Coarse Solvers for Algebraic Multigrid on Multicore and Manycore Architectures", International Conference on Parallel Processing and Applied Mathematics (PPAM), September 6, 2015, doi: 10.1007/978-3-319-32149-3_12

Aydin Buluç, Scott Beamer, Kamesh Madduri, Krste Asanović, David Patterson., "Distributed-memory breadth-first search on massive graphs.", In D. Bader (editor), Parallel Graph Algorithms. CRC Press/Taylor-Francis, ( 2015)

Mahantesh Halappanavar, Alex Pothen, Ariful Azad, Fredrik Manne, Johannes Langguth, Arif Khan, "Codesign Lessons Learned from Implementing Graph Matching on Multithreaded Architectures", IEEE Computer, August 2015,

Abhinav Sarje, Parallel Performance Optimizations on Unstructured Mesh-Based Simulations, International Conference on Computational Science, June 2015,

Abhinav Sarje, Sukhyun Song, Douglas Jacobsen, Kevin Huck, Jeffrey Hollingsworth, Allen Malony, Samuel Williams, and Leonid Oliker, "Parallel Performance Optimizations on Unstructured Mesh-Based Simulations", Procedia Computer Science, 1877-0509, June 2015, 51:2016-2025, doi: 10.1016/j.procs.2015.05.466

This paper addresses two key parallelization challenges the unstructured mesh-based ocean modeling code, MPAS-Ocean, which uses a mesh based on Voronoi tessellations: (1) load imbalance across processes, and (2) unstructured data access patterns, that inhibit intra- and inter-node performance. Our work analyzes the load imbalance due to naive partitioning of the mesh, and develops methods to generate mesh partitioning with better load balance and reduced communication. Furthermore, we present methods that minimize both inter- and intra- node data movement and maximize data reuse. Our techniques include predictive ordering of data elements for higher cache efficiency, as well as communication reduction approaches. We present detailed performance data when running on thousands of cores using the Cray XC30 supercomputer and show that our optimization strategies can exceed the original performance by over 2×. Additionally, many of these solutions can be broadly applied to a wide variety of unstructured grid-based computations.

Evangelos Georganas, Aydın Buluç, Jarrod Chapman, Leonid Oliker, Daniel Rokhsar, Katherine Yelick, "merAligner: A Fully Parallel Sequence Aligner", IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2015,

Protonu Basu, Samuel Williams, Brian Van Straalen, Mary Hall, Leonid Oliker, Phillip Colella, "Compiler-Directed Transformation for Higher-Order Stencils", International Parallel and Distributed Processing Symposium (IPDPS), May 2015,

Ariful Azad, Aydin Buluc, John Gilbert, "Parallel Triangle Counting and Enumeration using Matrix Algebra", Workshop on Graph Algorithms Building Blocks (GABB), in conjunction with IPDPS, IEEE, May 2015,

Ariful Azad, Aydin Buluç, Alex Pothen, "A Parallel Tree Grafting Algorithm for Maximum Cardinality Matching in Bipartite Graphs", International Parallel and Distributed Processing Symposium (IPDPS), May 2015,

Didem Unat, Cy Chan, Weiqun Zhang, Samuel Williams, John Bachan, John Bell, John Shalf, "ExaSAT: An Exascale Co-Design Tool for Performance Modeling", International Journal of High Performance Computing Applications (IJHPCA), May 2015, doi: 10.1177/1094342014568690

Hongzhang Shan, Samuel Williams, Wibe de Jong, Leonid Oliker, "Thread-Level Parallelization and Optimization of NWChem for the Intel MIC Architecture", Programming Models and Applications for Multicores and Manycores (PMAM), February 2015,

Costin Iancu, Nicholas Chaimov, Khaled Z. Ibrahim, Samuel Williams, "Exploiting Communication Concurrency on High Performance Computing Systems", Programming Models and Applications for Multicores and Manycores (PMAM), February 2015,

Aydin Buluç, Henning Meyerhenke, Ilya Safro, Peter Sanders, Christian Schulz., "Recent advances in graph partitioning", ArXiv, ( 2015)

Thorsten Kurth, Andrew Pochinsky, Abhinav Sarje, Sergey Syritsyn, Andre Walker-Loud, "High-Performance I/O: HDF5 for Lattice QCD", arXiv:1501.06992, January 2015,

Practitioners of lattice QCD/QFT have been some of the primary pioneer users of the state-of-the-art high-performance-computing systems, and contribute towards the stress tests of such new machines as soon as they become available. As with all aspects of high-performance-computing, I/O is becoming an increasingly specialized component of these systems. In order to take advantage of the latest available high-performance I/O infrastructure, to ensure reliability and backwards compatibility of data files, and to help unify the data structures used in lattice codes, we have incorporated parallel HDF5 I/O into the SciDAC supported USQCD software stack. Here we present the design and implementation of this I/O framework. Our HDF5 implementation outperforms optimized QIO at the 10-20% level and leaves room for further improvement by utilizing appropriate dataset chunking.

2014

Khaled Z. Ibrahim, Samuel W. Williams, Evgeny Epifanovsky, Anna I. Krylov, "Analysis and Tuning of Libtensor Framework on Multicore Architectures", High Performance Computing Conference (HIPC), December 2014,

Samuel Williams, HPGMG-FV, FastForward2 Proxy App Presentation, December 2014,

Mark Adams, Samuel Williams, Jed Brown, HPGMG, Birds of a Feather (BoF), Supercomputing, November 2014,

Yu Jung Lo, Samuel Williams, Brian Van Straalen, Terry J. Ligocki, Matthew J. Cordery, Leonid Oliker, Mary W. Hall, "Roofline Model Toolkit: A Practical Tool for Architectural and Program Analysis", Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November 2014, doi: 10.1007/978-3-319-17248-4_7

Protonu Basu, Samuel Williams, Brian Van Straalen, Leonid Oliker, Mary Hall, "Converting Stencils to Accumulations for Communication-Avoiding Optimization in Geometric Multigrid", Workshop on Stencil Computations (WOSC), October 2014,

Hongzhang Shan, Amir Kamil, Samuel Williams, Yili Zheng, Katherine Yelick, "Evaluation of PGAS Communication Paradigms with Geometric Multigrid", 8th International Conference on Partitioned Global Address Space Programming Models (PGAS), October 2014, doi: 10.1145/2676870.2676874

Hongzhang Shan, Samuel Williams, Wibe de Jong, Leonid Oliker, "Thread-Level Parallelization and Optimization of NWChem for the Intel MIC Architecture", LBNL Technical Report, October 2014, LBNL 6806E,

Abhinav Sarje, Xiaoye S Li, Alexander Hexemer, "Tuning HipGISAXS on Multi and Many Core Supercomputers", High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation, Denver, CO, Springer International Publishing, 2014, 8551:217-238, doi: 10.1007/978-3-319-10214-6_11

With the continual development of multi and many-core architectures, there is a constant need for architecture-specific tuning of application-codes in order to realize high computational performance and energy efficiency, closer to the theoretical peaks of these architectures. In this paper, we present optimization and tuning of HipGISAXS, a parallel X-ray scattering simulation code [9], on various massively-parallel state-of-the-art supercomputers based on multi and many-core processors. In particular, we target clusters of general-purpose multi-cores such as Intel Sandy Bridge and AMD Magny Cours, and many-core accelerators like Nvidia Kepler GPUs and Intel Xeon Phi coprocessors. We present both high-level algorithmic and low-level architecture-aware optimization and tuning methodologies on these platforms. We cover a detailed performance study of our codes on single and multiple nodes of several current top-ranking supercomputers. Additionally, we implement autotuning of many of the algorithmic and optimization parameters for dynamic selection of their optimal values to ensure high-performance and high-efficiency.

Abhinav Sarje, Xiaoye S Li, Alexander Hexemer, "High-Performance Inverse Modeling with Reverse Monte Carlo Simulations", 43rd International Conference on Parallel Processing, Minneapolis, MN, IEEE, September 2014, 201-210, doi: 10.1109/ICPP.2014.29

In the field of nanoparticle material science, X-ray scattering techniques are widely used for characterization of macromolecules and particle systems (ordered, partially-ordered or custom) based on their structural properties at the micro- and nano-scales. Numerous applications utilize these, including design and fabrication of energy-relevant nanodevices such as photovoltaic and energy storage devices. Due to its size, analysis of raw data obtained through present ultra-fast light beamlines and X-ray scattering detectors has been a primary bottleneck in such characterization processes. To address this hurdle, we are developing high-performance parallel algorithms and codes for analysis of X-ray scattering data for several of the scattering methods, such as the Small Angle X-ray Scattering (SAXS), which we talk about in this paper. As an inverse modeling problem, structural fitting of the raw data obtained through SAXS experiments is a method used for extracting meaningful information on the structural properties of materials. Such fitting processes involve a large number of variable parameters and, hence, require a large amount of computational power. In this paper, we focus on this problem and present a high-performance and scalable parallel solution based on the Reverse Monte Carlo simulation algorithm, on highly-parallel systems such as clusters of multicore CPUs and graphics processors. We have implemented and optimized our algorithm on generic multi-core CPUs as well as the Nvidia GPU architectures with C++ and CUDA. We also present detailed performance results and computational analysis of our code.

Adam Lugowski, Shoaib Kamil, Aydın Buluç, Samuel Williams, Erika Duriakova, Leonid Oliker, Armando Fox, John R. Gilbert,, "Parallel processing of filtered queries in attributed semantic graphs", Journal of Parallel and Distributed Computing (JPDC), September 2014, doi: 10.1016/j.jpdc.2014.08.010

George Michelogiannakis, Alexander Williams, Samuel Williams, John Shalf, "Collective Memory Transfers for Multi-Core Chips", International Conference on Supercomputing (ICS), June 2014, doi: 10.1145/2597652.2597654

H. M. Aktulga, A. Buluc, S. Williams, C. Yang, "Optimizing Sparse Matrix-Multiple Vector Multiplication for Nuclear Configuration Interaction Calculations", International Parallel and Distributed Processing Symposium (IPDPS 2014), May 2014, doi: 10.1109/IPDPS.2014.125

Mark F. Adams, Jed Brown, John Shalf, Brian Van Straalen, Erich Strohmaier, Samuel Williams, "HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems", LBNL Technical Report, 2014, LBNL 6630E,

Samuel Williams, Mike Lijewski, Ann Almgren, Brian Van Straalen, Erin Carson, Nicholas Knight, James Demmel, "s-step Krylov subspace methods as bottom solvers for geometric multigrid", Parallel and Distributed Processing Symposium, 2014 IEEE 28th International, January 2014, 1149--1158, doi: 10.1109/IPDPS.2014.119

2013

Protonu Basu, Anand Venkat, Mary Hall, Samuel Williams, Brian Van Straalen, Leonid Oliker, "Compiler generation and autotuning of communication-avoiding operators for geometric multigrid", 20th International Conference on High Performance Computing (HiPC), December 2013, 452--461,

Hongzhang Shan, Brian Austin, Wibe de Jong, Leonid Oliker, Nick Wright, Edoardo Apra, "Performance Tuning of Fock Matrix and Two Electron Integral Calculations for NWChem on Leading HPC Platforms", Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November 2013, doi: 10.1007/978-3-319-10214-6_13

Slim T. Chourou, Abhinav Sarje, Xiaoye Li, Elaine Chan and Alexander Hexemer, "HipGISAXS: a high-performance computing code for simulating grazing-incidence X-ray scattering data", Journal of Applied Crystallography, 2013, 46:1781-1795, doi: 10.1107/ S0021889813025843

We have implemented a flexible Grazing Incidence Small-Angle Scattering (GISAXS) simulation code in the framework of the Distorted Wave Born Approximation (DWBA) that effectively utilizes the parallel processing power provided by graphics processors and multicore processors. This constitutes a handy tool for experimentalists facing a massive flux of data, allowing them to accurately simulate the GISAXS process and analyze the produced data. The software computes the diffraction image for any given superposition of custom shapes or morphologies in a user-defined region of the reciprocal space for all possible grazing incidence angles and sample orientations. This flexibility then allows to easily tackle a wide range of possible sample structures such as nanoparticles on top of or embedded in a substrate or a multilayered structure. In cases where the sample displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample and compute the averaged refractive index profile to be used as the reference geometry of the unperturbed system. Preliminary tests show good agreement with experimental data for a variety of commonly encountered nanostrutures.

Bei Wang, Stephane Ethier, William Tang, Timothy Williams, Khaled Z. Ibrahim, Kamesh Madduri, Samuel Williams, Leonid Oliker, "Kinetic Turbulence Simulations at Extreme Scale on Leadership-Class Systems", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), November 2013, doi: 10.1145/2503210.2503258

Samuel Williams, At Exascale, Will Bandwidth Be Free?, DOE ModSim Workshop, 2013,

Tim Mattson, David Bader, Jon Berry, Aydin Buluc, Jack Dongarra, Christos Faloutsos, John Feo, John Gilbert, Joseph Gonzalez, Bruce
Hendrickson, Jeremy Kepner, Charles Leiserson, Andrew Lumsdaine, David Padua, Stephen Poole, Steve Reinhardt, Mike Stonebraker, Steve Wallach,
Andrew Yoo,
"Standards for Graph Algorithm Primitives", HPEC, 2013,

James Demmel, Samuel Williams, Katherine Yelick, "Automatic Performance Tuning (Autotuning)", The Berkeley Par Lab: Progress in the Parallel Computing Landscape, edited by David Patterson, Dennis Gannon, Michael Wrinn, (Microsoft Research: August 2013) Pages: 337-376

Khaled Z Ibrahim, Kamesh Madduri, Samuel Williams, Bei Wang, Stephane Ethier, Leonid Oliker, "Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms", International Journal of High Performance Computing Applications (IJHPCA), July 2013, doi: 10.1177/1094342013492446

P. Basu, A. Venkat, M. Hall, S. Williams, B. Van Straalen, L. Oliker, "Compiler Generation and Autotuning of Communication-Avoiding Operators for Geometric Multigrid", Workshop on Stencil Computations (WOSC), 2013,

Christopher D. Krieger, Michelle Mills Strout, Catherine Olschanowsky, Andrew Stone, Stephen Guzik, Xinfeng Gao, Carlo Bertolli, Paul H.J. Kelly, Gihan Mudalige, Brian Van Straalen, Sam Williams, "Loop chaining: A programming abstraction for balancing locality and parallelism", Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2013 IEEE 27th International, May 2013, 375--384, doi: 10.1109/IPDPSW.2013.68

Aydın Buluç, Erika Duriakova, Armando Fox, John Gilbert, Shoaib Kamil, Adam Lugowski, Leonid Oliker, Samuel Williams, "High-Productivity and High-Performance Analysis of Filtered Semantic Graphs", International Parallel and Distributed Processing Symposium (IPDPS), 2013, doi: 10.1145/2370816.2370897

Abhinav Sarje, Samuel Williams, David H. Bailey, "MPQC: Performance analysis and optimization", LBNL Technical Report, February 2013, LBNL 6076E,

2012

Samuel Williams, Dhiraj D. Kalamkar, Amik Singh, Anand M. Deshpande, Brian Van Straalen, Mikhail Smelyanskiy,
Ann Almgren, Pradeep Dubey, John Shalf, Leonid Oliker,
"Implementation and Optimization of miniGMG - a Compact Geometric Multigrid Benchmark", December 2012, LBNL 6676E,

Samuel Williams, Optimization of Geometric Multigrid for Emerging Multi- and Manycore Processors, Supercomputing (SC), November 2012,

Abhinav Sarje, Xiaoye S. Li, Slim Chourou, Elaine R. Chan, Alexander Hexemer, "Massively Parallel X-ray Scattering Simulations", Supercomputing, November 2012,

Although present X-ray scattering techniques can provide tremendous information on the nano-structural properties of materials that are valuable in the design and fabrication of energy-relevant nano-devices, a primary challenge remains in the analyses of such data. In this paper we describe a high-performance, flexible, and scalable Grazing Incidence Small Angle X-ray Scattering simulation algorithm and codes that we have developed on multi-core/CPU and many-core/GPU clusters. We discuss in detail our implementation, optimization and performance on these platforms. Our results show speedups of ~125x on a Fermi-GPU and ~20x on a Cray-XE6 24-core node, compared to a sequential CPU code, with near linear scaling on multi-node clusters. To our knowledge, this is the first GISAXS simulation code that is flexible to compute scattered light intensities in all spatial directions allowing full reconstruction of GISAXS patterns for any complex structures and with high-resolutions while reducing simulation times from months to minutes.

S. Williams, D. Kalamkar, A. Singh, A. Deshpande, B. Van Straalen, M. Smelyanskiy, A. Almgren, P. Dubey, J. Shalf, L. Oliker, "Optimization of Geometric Multigrid for Emerging Multi- and Manycore Processors", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), November 2012, doi: 10.1109/SC.2012.85

B. Wang, S. Ethier, W. Tang, K. Ibrahim, K. Madduri, S. Williams, "Advances in gyrokinetic particle in cell simulation for fusion plasmas to Extreme scale", Supercomputing (SC), 2012,

Hongzhang Shan, Brian Austin, Nicholas Wright, Erich Strohmaier, John Shalf, Katherine Yelick, "Accelerating Applications at Scale Using One-Sided Communication", Santa Barbara, CA, The 6th Conference on Partitioned Global Address Programming Models, October 10, 2012,

A. Buluç, A. Fox, J. R. Gilbert, S. Kamil, A. Lugowski, L. Oliker, S. Williams, "High-performance analysis of filtered semantic graphs", PACT '12 Proceedings of the 21st international conference on Parallel architectures and compilation techniques (extended abstract), 2012, doi: 10.1145/2370816.2370897

K. Madduri, J. Su, S. Williams, L. Oliker, S. Ethier, K. Yelick, "Optimization of Parallel Particle-to-Grid Interpolation on Leading Multicore Platforms", Transactions on Parallel and Distributed Systems (TPDS), October 1, 2012, doi: 10.1109/TPDS.2012.28

J. Krueger, P. Micikevicius, S. Williams, "Optimization of Forward Wave Modeling on Contemporary HPC Architectures", LBNL Technical Report, 2012, LBNL 5751E,

Hongzhang Shan, Erich Strohmaier, James Amundson, Eric G. Stern, "Optimizing The Advanced Accelerator Simulation Framework Synergia Using OpenMP", IWOMP'12 Proceedings of the 8th International COnference on OpenMP, June 11, 2012,

Abhinav Sarje, Next-Generation Scientific Computing with Graphics Processors, Beijing Computational Science Research Center, February 2012,

2011

S. Williams, et al., Extracting Ultra-Scale Lattice Boltzmann Performance via Hierarchical and Distributed Auto-Tuning, Supercomputing (SC), 2011,

S. Williams, et al., Stencil Computations on CPUs, Stanford Earth Sciences Algorithms and Architectures Initiative (SESAAI), 2011,

S. Williams, et al., Performance Optimization of HPC Applications on Multi- and Manycore Processors, Workshop on Hybrid Technologies for NASA Applications, 4th Internation Conference on Space Mission Challenges for Information Technology, 2011,

J. Demmel, K. Yelick, M. Anderson, G. Ballard, E. Carson, I. Dumitriu, L. Grigori, M. Hoemmen, O. Holtz, K. Keutzer, N. Knight, J. Langou, M. Mohiyuddin, O. Schwartz, E. Solomonik, S. Williams, Hua Xiang, Rethinking Algorithms for Future Architectures: Communication-Avoiding Algorithms, Hot Chips 23, 2011,

S. Williams, et al, Stencil Computations on CPUs, Society of Exploration Geophysicists High-Performance Computing Workshop (SEG), July 2011,

A. Buluç, S. Williams, L. Oliker, J. Demmel, "Reduced-Bandwidth Multithreaded Algorithms for Sparse Matrix-Vector Multiplication", International Parallel Distributed Processing Symposium (IPDPS), May 2011, doi: 10.1109/IPDPS.2011.73

P. Narayanan, A. Koniges, L. Oliker, R. Preissl, S. Williams, N. Wright, M. Umansky, X. Xu, S. Ethier, W. Wang, J. Candy, J. Cary, "Performance Characterization for Fusion Co-design Applications", Cray Users Group (CUG), May 2011,

A. Kaiser, S. Williams, K. Madduri, K. Ibrahim, D. Bailey, J. Demmel, E. Strohmaier, "TORCH Computational Reference Kernels: A Testbed for Computer Science Research", LBNL Technical Report, 2011, LBNL 4172E,

David H. Bailey, Robert F. Lucas, Samuel W. Williams, ed., Performance Tuning of Scientific Applications, (CRC Press: 2011)

M. Christen, N. Keen, T. Ligocki, L. Oliker, J. Shalf, B. van Straalen, S. Williams, "Automatic Thread-Level Parallelization in the Chombo AMR Library", LBNL Technical Report, 2011, LBNL 5109E,

David H. Bailey, Lin-Wang Wang, Hongzhang Shan, Zhengji Zhao, Juan Meza, Erich Strohmaier, Byounghak Lee, "Tuning an electronic structure code", Performance Tuning of Scientific Applications, edited by David H. Bailey, Robert F. Lucas, Samuel W. Williams, (CRC Press: 2011) Pages: 339-354

Kamesh Madduri, Khaled Ibrahim, Samuel Williams, Eun-Jin Im, Stephane Ethier, John Shalf, Leonid Oliker, "Gyrokinetic toroidal simulations on leading multi- and manycore HPC systems", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), January 2011, 23, doi: 10.1145/2063384.2063415

Samuel Williams, Oliker, Carter, John Shalf, "Extracting ultra-scale Lattice Boltzmann performance via hierarchical and distributed auto-tuning", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), New York, NY, USA, ACM, January 2011, 55, doi: 10.1145/2063384.2063458

Jens Krueger, David Donofrio, John Shalf, Marghoob Mohiyuddin, Samuel Williams, Leonid Oliker, Franz-Josef Pfreund, "Hardware/software co-design for energy-efficient seismic modeling", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), January 2011, 73, doi: 10.1145/2063384.2063482

Kamesh Madduri, Eun-Jin Im, Khaled Z. Ibrahim, Samuel Williams, Stephane Ethier, Leonid Oliker, "Gyrokinetic Particle-in-cell Optimization on Emerging Multi- and Manycore Platforms", Parallel Computing (PARCO), January 2011, 37:501 - 520, doi: 10.1016/j.parco.2011.02.001

2010

Khaled Z. Ibrahim, Erich Strohmaier, "Characterizing the Relation Between Apex-Map Synthetic Probes and Reuse Distance Distributions", The 39th International Conference on Parallel Processing (ICPP), 2010, 353 -362,

Samuel W. Williams, David H. Bailey, "Parallel Computer Architecture", Performance Tuning of Scientific Applications, edited by David H. Bailey, Robert F. Lucas, Samuel W. Williams, (CRC Press: 2010) Pages: 11-33

S. Williams, N. Bell, J. W. Choi, M. Garland, L. Oliker, R. Vuduc, "Sparse Matrix-Vector Multiplication on Multicore and Accelerators", chapter in Scientific Computing with Multicore and Accelerators, edited by Jack Dongarra, David A. Bader, Jakub Kurzak, ( 2010)

K. Datta, S. Williams, V. Volkov, J. Carter, L. Oliker, J. Shalf, K. Yelick, "Auto-tuning Stencil Computations on Multicore and Accelerators", Scientific Computing with Multicore and Accelerators, edited by Jack Dongarra, David A. Bader, ( 2010)

S. Williams, "The Roofline Model", chapter in Performance Tuning of Scientific Applications, edited by David H. Bailey, Robert F. Lucas, Samuel W. Williams, (CRC Press: 2010)

Hongzhang Shan, Erich Strohmaier, "Developing a Parameterized Performance Proxy for Sequential Scientific Kernels", 12th IEEE International Conference on High Performance Computing and Communications (HPCC), 2010, September 1, 2010,

A. Kaiser, S. Williams, K. Madduri, K. Ibrahim, D. Bailey, J. Demmel, E. Strohmaier, "A Principled Kernel Testbed for Hardware/Software Co-Design Research", Proceedings of the 2nd USENIX Workshop on Hot Topics in Parallelism (HotPar), 2010,

S. Williams, et al., Lattice Boltzmann Hybrid Auto-tuning on High-End Computational Platforms, Worshop on Programming Environments for Emerging Parallel Systems (PEEPS), 2010,

E. Strohmaier, S. Williams, A. Kaiser, K. Madduri, K. Ibrahim, D. Bailey, J. Demmel,, "A Kernel Testbed for Parallel Architecture, Language, and Performance Research", International Conference of Numerical Analysis and Applied Mathematics (ICNAAM), June 1, 2010, doi: 10.1063/1.3497950

A. Kaiser, S. Williams, K. Madduri, K. Ibrahim, D. Bailey, J. Demmel, E. Strohmaier, "A Principled Kernel Testbed for Hardware/Software Co-Design Research", Proceedings of the 2nd USENIX Workshop on Hot Topics in Parallelism (HotPar), 2010,

Shoaib Kamil, Cy Chan, Leonid Oliker, John Shalf, Samuel Williams, "An auto-tuning framework for parallel multicore stencil computations", International Parallel & Distributed Processing Symposium (IPDPS), January 1, 2010, 1-12, doi: 10.1109/IPDPS.2010.5470421

Samuel Williams, Kaushik Datta, Leonid Oliker, Jonathan Carter, John Shalf, Katherine Yelick, "Auto-Tuning Memory-Intensive Kernels for Multicore", Performance Tuning of Scientific Applications, edited by D. H. Bailey, R. F. Lucas, S. W. Williams, (CRC Press: 2010) Pages: 219

A. Chandramowlishwaran, S. Williams, L. Oliker, I. Lashuk, G. Biros, R. Vuduc, "Optimizing and Tuning the Fast Multipole Method for State-of-the-Art Multicore Architectures", International Parallel & Distributed Processing Symposium (IPDPS), 2010, doi: 10.1109/IPDPS.2010.5470415

2009

"Accelerating Time-to-Solution for Computational Science and Engineering", J. Demmel, J. Dongarra, A. Fox, S. Williams, V. Volkov, K. Yelick, SciDAC Review, Number 15, December 2009,

Kamesh Madduri, Samuel Williams, Stephane Ethier, Leonid Oliker, John Shalf, Erich Strohmaier, Katherine Yelick, "Memory-Efficient Optimization of Gyrokinetic Particle-to-Grid Interpolation for Multicore Processors", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), November 2009, doi: 10.1145/1654059.1654108

S. Zhou, D. Duffy, T. Clune, M. Suarez, S. Williams, M. Halem, "The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models", Concurrency and Computation:Practice and Experience (CCPE), August 2009, doi: 10.1002/cpe.1482

Zhengji Zhao, Juan Meza, Byounghak Lee, Hongzhang Shan, Eric Strohmaier, David H. Bailey, Lin-Wang Wang, "The linearly scaling 3D fragment method for large scale electronic structure calculations", Journal of Physics: Conference Series, July 1, 2009,

Shoaib Kamil, Cy Chan, Samuel Williams, Leonid Oliker, John Shalf, Mark Howison, E. Wes Bethel, Prabhat, "A Generalized Framework for Auto-tuning Stencil Computations", BEST PAPER AWARD - Cray User Group Conference (CUG), Atlanta, GA, May 4, 2009, LBNL 2078E,

Best Paper Award

S. Williams, J. Carter, L. Oliker, J. Shalf, K. Yelick, "Resource-Efficient, Hierarchical Auto-Tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4", Proceedings of the Cray User Group (CUG), Atlanta, GA, 2009,

S. Williams, et al., A Generalized Framework for Auto-tuning Stencil Computations, Cray User Group (CUG), 2009,

S. Williams, et al., Resource-Efficient, Hierarchical Auto-Tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4, Cray User Group (CUG), 2009,

S. Williams, A. Waterman, D. Patterson, "Roofline: an insightful visual performance model for multicore architectures", Communications of the ACM (CACM), April 2009, doi: 10.1145/1498765.1498785

Marghoob Mohiyuddin, Murphy, Oliker, Shalf, Wawrzynek, Samuel Williams, "A design methodology for domain-optimized power-efficient supercomputing", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), 2009, doi: 10.1145/1654059.1654072

Joseph Gebis, Oliker, Shalf, Williams, Katherine A. Yelick, "Improving Memory Subsystem Performance Using ViVA: Virtual Vector Architecture", International Conference on Architecture of Computing Systems (ARCS), Delft, Netherlands, 2009, 146-158,

K. Datta, S. Williams, V. Volkov, J. Carter, L. Oliker, J. Shalf, K. Yelick, "Auto-Tuning the 27-point Stencil for Multicore", Proceedings of Fourth International Workshop on Automatic Performance Tuning (iWAPT2009), January 2009,

91BYM4FUXJL

Kaushik Datta, Kamil, Williams, Oliker, Shalf, Katherine A. Yelick, "Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors", SIAM Review, 2009, 51:129-159, doi: 10.1137/070693199

Samuel Williams, Carter, Oliker, Shalf, Katherine A. Yelick, "Optimization of a lattice Boltzmann computation on state-of-the-art multicore platforms", Journal of Parallel Distributed Computing (JPDC), 2009, 69:762-777, doi: 10.1016/j.jpdc.2009.04.002

Kamesh Madduri, Williams, Ethier, Oliker, Shalf, Strohmaier, Katherine A. Yelick, Memory-efficient optimization of Gyrokinetic particle-to-grid interpolation for multicore processors, Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), 2009,

2008

S. Williams, Auto-tuning Performance on Multicore Computers, Ph.D. Thesis Dissertation Talk, University of California at Berkeley, 2008,

Lin-Wang Wang, Byounghak Lee, Hongzhang Shan, Zhengji Zhao, Juan Meza, Erich Strohmaier, David H. Bailey, "Linearly scaling 3D fragment method for large-scale electronic structure calculations", Proceedings of SC08, November 2008,

K. Datta, M. Murphy, V. Volkov, S. Williams, J. Carter, L. Oliker, D. Patterson, J. Shalf, K. Yelick, "Stencil Computation Optimization and Auto-Tuning on State-of-the-Art Multicore Architectures", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), November 2008, doi: 10.1109/SC.2008.5222004

Samuel Webb Williams, Andrew Waterman, David A. Patterson, "Roofline: An Insightful Visual Performance Model for Floating-Point Programs and Multicore Architectures", EECS Tech Report UCB/EECS-2008-134, October 2008,

S. Williams, et al, "Auto-tuning and the Roofline model", View From the Top: Craig Mundie (Ph.D student poster session), 2008,

S. Williams, et al., The Roofline Model: A Pedagogical Tool for Auto-tuning Kernels on Multicore Architectures, Hot Chips 20, August 10, 2008,

S. Williams, et al., A Vision for Integrating Performance Counters into the Roofline model, UPCRC PMU Workshop (Performance Counters), 2008,

D. Bailey, J. Chame, C. Chen, J. Dongarra, M. Hall, J. Hollingsworth, P. Hovland, S. Moore, K. Seymour, J. Shin, A. Tiwari, S. Williams, H. You, "PERI Auto-tuning", SciDAC PI Meeting, Journal of Physics: Conference Series, 125 012001, 2008,

S. Williams, K. Datta, J. Carter, L. Oliker, J. Shalf, K. Yelick, D. Bailey, "PERI: Auto-tuning Memory Intensive Kernels for Multicore", SciDAC PI Meeting, Journal of Physics: Conference Series, 125 012038, July 2008, doi: 10.1088/1742-6596/125/1/012038

S. Williams, J. Carter, J. Demmel, L. Oliker, D. Patterson, J. Shalf, K. Yelick, R. Vuduc, "Autotuning Scientific Kernels on Multicore Systems", ASCR PI Meeting, 2008,

S. Williams, et al., PERI: Auto-tuning Memory Intensive Kernels for Multicore, SciDAC PI Meeting, 2008,

S. Williams, et al., The Roofline Model: A Pedagogical Tool for Program Analysis and Optimization, ParLab Summer Retreat, 2008,

S. Zhou, D. Duffy, T. Clune, M. Suarez, S. Williams, M. Halem, "Impacts of the IBM Cell Processor on Supporting Climate Models", International Supercomputing Conference (ISC), 2008,

K. Datta, S. Williams, V. Volkov, M. Murphy, "Autotuning Structured Grid Kernels", ParLab Summer Retreat, 2008,

S. Williams, et. al, "The Roofline Model: A Pedagogical Tool for Program Analysis and Optimization", Parlab Summer Retreat, 2008,

S. Williams, J. Carter, L. Oliker, J. Shalf, K. Yelick, "Lattice Boltzmann Simulation Optimization on Leading Multicore Platforms", IEEE International Symposium on Parallel and Distributed Processing. BEST PAPER AWARD - Applications Track, 2008, doi: 10.1109/IPDPS.2008.4536295

Shoaib Kamil, Shalf, Erich Strohmaier, "Power efficiency in high performance computing", IPDPS, 2008, 1-8,

Samuel Williams, Oliker, W. Vuduc, Shalf, A. Yelick, James Demmel, "Optimization of sparse matrix-vector multiplication on emerging multicore platforms", Parallel Computing, 2008, 35:38, doi: 10.1016/j.parco.2008.12.006

S. Williams, J. Carter, L. Oliker, J. Shalf, K. Yelick, Lattice Boltzmann simulation optimization on leading multicore platforms, IEEE International Symposium on Parallel & Distributed Processing (IPDPS)., Pages: 1-14 2008,

K. Datta, S. Williams, S. Kamil, "Autotuning Structured Grid Kernels", Parlab Winter Retreat, 2008,

S. Williams, et al., Autotuning Sparse and Structured Grid Kernels, Parlab Winter Retreat, 2008,

S. Williams, K. Datta, J. Carter, L. Oliker, J. Shalf, K. Yelick, D. Bailey, PERI -- Auto-tuning Memory-intensive Kernels for Multicore, Journal of Physics: Conference Series, Pages: 012038 2008,

2007

S. Williams, et al., Optimization of Sparse Matrix-Vector Multiplication on Emerging Multicore Platforms, DOE/DOD Workshop on Emerging High-Performance Architectures and Applications, 2007,

S. Williams, L. Oliker, R. Vuduc, J. Shalf, K. Yelick, J. Demmel, "Optimization of Sparse Matrix-Vector Multiplication on Emerging Multicore Platforms", Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC), November 2007, doi: 10.1145/1362622.1362674

S. Williams, et al., Optimization of Sparse Matrix-Vector Multiplication on Emerging Multicore Platforms, Supercomputing (SC), 2007,

S. Williams, et al., Tuning Sparse Matrix Vector Multiplication for multi-core processors, Center for Scalable Application Development Software (CScADS), 2007,

S. Williams, et al., Tuning Sparse Matrix Vector Multiplication for multi-core SMPs, Parlab Seminar, 2007,

Costin Iancu, Erich Strohmaier, "Optimizing communication overlap for high-speed networks", Principles and Practice of Parallel Programming (PPoPP), 2007,

Leonid Oliker, Julian Borrill, Hongzhang Shan, John Shalf, Investigation Of Leading HPC I/O Performance Using A Scientific-Application Derived Benchmark., 2007,

Samuel Williams, Shalf, Oliker, Kamil, Husbands, Katherine A. Yelick, "Scientific Computing Kernels on the Cell Processor", International Journal of Parallel Programming, January 2007, 35:263-298, doi: 10.1007/s10766-007-0034-5

J. Shalf, L. Oliker, M. Lijewski, S. Kamil, J. Carter, A. Canning, S. Ethier, "Performance Characteristics of Potential Petascale Scientific Applications", Chapman & Hall/CRC Computational Science, (CRC Press: 2007) Pages: 1

Book Chapter

J. Carter, L. Oliker, J. Shalf, "Performance Evaluation of Scientific Applications on Modern Parallel Vector Systems", Extended Version: Lecture Notes in Computer Science, 2007,

Leonid Oliker, Canning, Carter, Iancu, Lijewski, Kamil, Shalf, Shan, Strohmaier, Ethier, Tom Goodale, "Scientific Application Performance on Candidate PetaScale Platforms", IEEE International Symposium on Parallel & Distributed Processing (IPDPS). BEST PAPER AWARD - application track., 2007, 1-12, doi: 10.1109/IPDPS.2007.370259

J. Carter, Y. He, J. Shalf, H. Shan, E. Strohmaier, H. Wasserman, "The Performance Effect of Multi-core on Scientific Applications", Proceedings of Cray User Group, 2007, LBNL 62662,

J. Levesque, J. Larkin, M. Foster, J. Glenski, G. Geissler, S. Whalen, B. Waldecker, J. Carter, D. Skinner, Y. He, H. Wasserman, J. Shalf, H. Shan, E. Strohmaier, "Understanding and Mitigating Multicore Performance Issues on the AMD Opteron Architecture", 2007, LBNL 62500,

John Shalf, Shoaib Kamil, David Bailey, Erich Strohmaier, Power Efficiency and the Top500, 2007,

L. Oliker, A. Canning, J. Carter, C. Iancu, M. Lijewski, S. Kamil, J. Shalf, H. Shan, E. Strohmaier, S. Ethier, T. Goodale, "Performance Characteristics of Potential Petascale Scientific Applications", Petascale Computing: Algorithms and Applications. Chapman & Hall/CRC Computational Science Series (Hardcover), edited by David A. Bader, ( 2007)

Chapter

2006

K. Asanovic, R. Bodik, B. Catanzaro, J. Gebis, P. Husbands, K. Keutzer, D. Patterson, W. Plishker, J. Shalf, S. Williams, K. Yelick, "The Landscape of Parallel Computing Research: A View from Berkeley", EECS Technical Report, December 2006,

Hongzhang Shan, Erich Strohmaier, Ji Qiang, David H. Bailey, Kathy Yelick, "Performance modeling and optimization of a high energy colliding beam simulation code", Proceedings of SC2006, November 2006,

S. Williams, et al., 3D Lattice Boltzmann Magneto-hydrodynamics (LBMHD3D), UTK Summit on Software and Algorithms for the Cell Processor, 2006,

S. Williams, J. Shalf, L. Oliker, P. Husbands, S. Kamil, K. Yelick, "The Potential of the Cell Processor for Scientific Computing", ACM International Conference on Computing Frontiers, 2006, doi: 10.1145/1128022.1128027

S. Williams, et al, The Potential of the Cell Processor for Scientific Computing, presented at Transmeta, 2006,

S. Williams, et al., The Potential of the Cell Processor for Scientific Computing, LBL Scientific Computing Seminar, 2006,

J. Carter, L. Oliker, J. Shalf, "Performance Evaluation of Scientific Applications on Modern Parallel Vector Systems", High Performance Computing for Computational Science., 2006,

Highest Ranked Conference Paper

J. Carter, L. Oliker, J. Shalf, "Performance Evaluation of Scientific Applications on Modern Parallel Vector Systems", VECPAR, 2006,

Jonathan Carter, Oliker, John Shalf, "Performance Evaluation of Scientific Applications on Modern Parallel Vector Systems", VECPAR, Springer Berlin/Heidelberg, 2006, 4395:490-503,

Shoaib Kamil, Datta, Williams, Oliker, Shalf, Katherine A. Yelick, "Implicit and explicit optimizations for stencil computations", Memory System Performance and Correctness, 2006, 51-60, doi: 10.1145/1178597.1178605

Samuel Williams, Shalf, Oliker, Kamil, Husbands, Katherine A. Yelick, The potential of the cell processor for scientific computing, Conf. Computing Frontiers, Pages: 9-20 2006,

2005

S. Williams, J. Shalf, L. Oliker, P. Husbands, K. Yelick, "Dense and Sparse Matrix Operations on the Cell Processor", LBNL Technical Report, 2005,

2004

E. Strohmaier, Hongzhang Shan, "Architecture Independent Performance Characterization and Benchmarking for Scientific Applications", International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Volendam, The Netherlands, October 2004,

Hongzhang Shan, E. Strohmaier, "Performance Characterization of Cray X1 and Their Implications for Application Performance Tuning", International Conference of Supercomputing, Malo, France, June 2004,

H. Shan, E. Strohmaier, L. Oliker, "Optimizing Performance of Superscalar Codes for a Single Cray X1 MSP", Proceedings of the 46th Cray User Group Conference:CUG, 2004,

2002

E. Strohmaier, Performance Characterization and Benchmarking for High Performance Systems and Applications, University of Tennessee, CS Seminar, November 8, 2002,

Erich Strohmaier, Performance Characterization and Benchmarking for High Performance Systems and Applications, CCS Seminar, October 9, 2002,

Erich Strohmaier, Benchmarking for High Performance Systems and Applications, DARPA HPCS Performance Workshop, September 19, 2002,

2001

C. Kozyrakis, D. Judd, J. Gebis, S. Williams, D. Patterson, K. Yelick, "Hardware/Compiler Co-development for an Embedded Media Processor", Proceedings of the IEEE, 2001, doi: 10.1109/5.964446

2000

C. Kozyrakis, J. Gebis, D. Martin, S. Williams, I. Mavroidis, S. Pope, D. Jones, D. Patterson, K. Yelick, Vector IRAM: A media-oriented vector processor with embedded DRAM, Hot Chips 12, 2000,