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Brian Van Straalen

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Brian Van Straalen
Computer Systems Engineer
Phone: +1 510 486 4976
Fax: +1 510 486 6900

Brian Van Straalen received his BASc Mechanical Engineering in 1993 and MMath in Applied Mathematics in 1995 from University of Waterloo.  He has been working in the area of scientific computing since he was an undergraduate. He worked with Advanced Scientific Computing Ltd. developing CFD codes written largely in Fortran 77 running on VAX and UNIX workstations.  He then worked as part of the thermal modeling group with Bell Northern Research.  His Master's thesis work was in the area of a posteriori error estimation for Navier-Stokes equations, which is an area that is still relevant to Department of Energy scientific computing.   He worked for Beam Technologies developing the PDESolve package: a combined symbolic manipulation package and finite element solver, running in parallel on some of the earliest NSF and DOE MPP parallel computers.  He came to LBNL in 1998 to work with Phil Colella and start up the Chombo Project, now in its 13th year of development. He is currently working on his PhD in the Computer Science department at UC Berkeley.

Journal Articles

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

Andrew Myers, Phillip Colella, Brian Van Straalen, "A 4th-Order Particle-in-Cell Method with Phase-Space Remapping for the Vlasov-Poisson Equation", submitted to SISC, February 1, 2016,

Andrew Myers, Phillip Colella, Brian Van Straalen, "The Convergence of Particle-in-Cell Schemes for Cosmological Dark Matter Simulations", The Astrophysical Journal, Volume 816, Issue 2, article id. 56, 2016,

A Chien, P Balaji, P Beckman, N Dun, A Fang, H Fujita, K Iskra, Z Rubenstein, Z Zheng, R Schreiber, others, "Versioned Distributed Arrays for Resilience in Scientific Applications: Global View Resilience", Journal of Computational Science, 2015,

Anshu Dubey, Ann Almgren, John Bell, Martin Berzins, Steve Brandt, Greg Bryan, Phillip Colella, Daniel Graves, Michael Lijewski, Frank L\ offler, others, "A survey of high level frameworks in block-structured adaptive mesh refinement packages", Journal of Parallel and Distributed Computing, 2014, 74:3217--3227, doi: 10.1016/j.jpdc.2014.07.001

Vay, J.L., Colella, P., McCorquodale, P., Van Straalen, B., Friedman, A., Grote, D.P., "Mesh Refinement for Particle-in-Cell Plasma Simulations: Applications to and Benefits for Heavy Ion Fusion", Laser and Particle Beams. Vol.20 N.4 (2002), pp. 569-575, 2002,

Conference Papers

John Bachan, Dan Bonachea, Paul H Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian Van Straalen, Scott Baden, "The UPC++ PGAS library for exascale computing", PAW 2017: 2nd Annual PGAS Applications Workshop - Held in conjunction with SC 2017, November 12, 2017, doi: 10.1145/3144779.3169108

We describe UPC++ V1.0, a C++11 library that supports APGAS programming. UPC++ targets distributed data structures where communication is irregular or fine-grained. The key abstractions are global pointers, asynchronous programming via RPC, and futures. Global pointers incorporate ownership information useful in optimizing for locality. Futures capture data readiness state, are useful for scheduling and also enable the programmer to chain operations to execute asynchronously as high-latency dependencies become satisfied, via continuations. The interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and closely resemble those used in modern C++. Communication in UPC++ runs at close to hardware speeds by utilizing the low-overhead GASNet-EX communication library.

Dharshi Devendran, Suren Byna, Bin Dong, Brian van Straalen, Hans Johansen, Noel Keen, and Nagiza Samatova,, "Collective I/O Optimizations for Adaptive Mesh Refinement Data Writes on Lustre File System", Cray User Group (CUG) 2016, May 10, 2016,

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,

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,

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

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,

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

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

Chaopeng Shen, David Trebotich, Sergi Molins, Daniel T Graves, BV Straalen, DT Graves, T Ligocki, CI Steefel, "High performance computations of subsurface reactive transport processes at the pore scale", Proceedings of SciDAC, 2011,

B. Van Straalen, P. Colella, D. T. Graves, N. Keen, "Petascale Block-Structured AMR Applications Without Distributed Meta-data", Euro-Par 2011 Parallel Processing - 17th International Conference, Euro-Par 2011, August 29 - September 2, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6853 Springer 2011, ISBN 978-3-642-23396-8, Bordeaux, France, 2011,

Deines E., Weber, G.H., Garth, C., Van Straalen, B. Borovikov, S., Martin, D.F., and Joy, K.I., "On the computation of integral curves in adaptive mesh refinement vector fields", Proceedings of Dagstuhl Seminar on Scientific Visualization 2009, Schloss Dagstuhl, 2011, 2:73-91, LBNL 4972E,

  • Download File: 7.pdf (pdf: 799 KB)

G. H. Weber, S. Ahern, E.W. Bethel, S. Borovikov, H.R. Childs, E. Deines, C. Garth, H. Hagen, B. Hamann, K.I. Joy, D. Martin, J. Meredith, Prabhat, D. Pugmire, O. Rübel, B. Van Straalen and K. Wu, "Recent Advances in VisIt: AMR Streamlines and Query-Driven Visualization", Numerical Modeling of Space Plasma Flows: Astronum-2009 (Astronomical Society of the Pacific Conference Series, 3185E, 2010, 429:329-334,

B.V. Straalen, J. Shalf, T. Ligocki, N. Keen, and W. Yang, "Scalability Challenges for Massively Parallel AMR Application", 23rd IEEE International Symposium on Parallel and Distributed Processing, 2009., 2009,

Brian van Straalen, Shalf, J. Ligocki, Keen, Woo-Sun Yang, "Scalability challenges for massively parallel AMR applications", IPDPS, 2009, 1-12,

G.H. Weber, V. Beckner, H. Childs, T. Ligocki, M. Miller, B. van Straalen, E.W. Bethel, "Visualization of Scalar Adaptive Mesh Refinement Data", Numerical Modeling of Space Plasma Flows: Astronum-2007 (Astronomical Society of the Pacific Conference Series), April 2008, 385:309-320, LBNL 220E,

P. Colella, D. Graves, T. Ligocki, D. Trebotich and B.V. Straalen, "Embedded Boundary Algorithms and Software for Partial Differential Equations", 2008 J. Phys.: Conf. Ser. 125 012084, 2008,

D. Trebotich, B.V. Straalen, D. Graves and P. Colella, "Performance of Embedded Boundary Methods for CFD with Complex Geometry", 2008 J. Phys.: Conf. Ser. 125 012083, 2008,

Phillip Colella, John Bell, Noel Keen, Terry Ligocki, Michael Lijewski, Brian van Straalen, "Performance and Scaling of Locally-Structured Grid Methods for Partial Differential Equations", presented at SciDAC 2007 Annual Meeting, 2007,

Kevin Long, Brian Van Straalen, "PDESolve: an object-oriented PDE analysis environment", Object Oriented Methods for Interoperable Scientific and Engineering Computing: Proceedings of the 1998 SIAM Workshop, 1998, 99:225,

Book Chapters

B. Van Straalen, D. Trebotich, A. Ovsyannikov and D.T. Graves, "Scalable Structured Adaptive Mesh Refinement with Complex Geometry", Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability, edited by Straatsma, T., Antypas, K., Williams, T., (Chapman and Hall/CRC: November 9, 2017)

Presentation/Talks

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

Reports

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", Lawrence Berkeley National Laboratory Tech Report, March 31, 2018, LBNL 2001136, doi: 10.2172/1430693

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Bryce Lelbach, Brian van Straalen,, "UPC++ Specification v1.0, Draft 6", Lawrence Berkeley National Laboratory Tech Report, March 26, 2018, LBNL 2001135, doi: 10.2172/1430689

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Programmer’s Guide, v1.0-2017.9", Lawrence Berkeley National Laboratory Tech Report, September 29, 2017, LBNL 2001065, doi: 10.2172/1398522

This document has been superseded by: UPC++ Programmer’s Guide, v1.0-2018.3.0 (LBNL-2001136)

UPC++ is a C++11 library that provides Asynchronous Partitioned Global Address Space (APGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The APGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, APGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Bryce Lelbach, Brian van Straalen,, "UPC++ Specification v1.0, Draft 4", Lawrence Berkeley National Laboratory Tech Report, September 27, 2017, LBNL 2001066, doi: 10.2172/1398521

This document has been superseded by: UPC++ Specification v1.0, Draft 6 (LBNL-2001135)

UPC++ is a C++11 library providing classes and functions that support Asynchronous Partitioned Global Address Space (APGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

M. Adams, P. Colella, D. T. Graves, J.N. Johnson, N.D. Keen, T. J. Ligocki. D. F. Martin. P.W. McCorquodale, D. Modiano. P.O. Schwartz, T.D. Sternberg, B. Van Straalen, "Chombo Software Package for AMR Applications - Design Document", Lawrence Berkeley National Laboratory Technical Report LBNL-6616E, January 9, 2015,

P. Colella, D. T. Graves, T. J. Ligocki, G.H. Miller , D. Modiano, P.O. Schwartz, B. Van Straalen, J. Pillod, D. Trebotich, M. Barad, "EBChombo Software Package for Cartesian Grid, Embedded Boundary Applications", Lawrence Berkeley National Laboratory Technical Report LBNL-6615E, January 9, 2015,

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, 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,

Brian Van Straalen, David Trebotich, Terry Ligocki, Daniel T. Graves, Phillip Colella, Michael Barad, "An Adaptive Cartesian Grid Embedded Boundary Method for the Incompressible Navier Stokes Equations in Complex Geometry", LBNL Report Number: LBNL-1003767, 2012, LBNL LBNL Report Numb,

We present a second-order accurate projection method to solve the
  incompressible Navier-Stokes equations on irregular domains in two
  and three dimensions.  We use a finite-volume discretization
  obtained from intersecting the irregular domain boundary with a
  Cartesian grid.  We address the small-cell stability problem
  associated with such methods by hybridizing a conservative
  discretization of the advective terms with a stable, nonconservative
  discretization at irregular control volumes, and redistributing the
  difference to nearby cells.  Our projection is based upon a
  finite-volume discretization of Poisson's equation.  We use a
  second-order, $L^\infty$-stable algorithm to advance in time.  Block
  structured local refinement is applied in space.  The resulting
  method is second-order accurate in $L^1$ for smooth problems.  We
  demonstrate the method on benchmark problems for flow past a
  cylinder in 2D and a sphere in 3D as well as flows in 3D geometries
  obtained from image data.

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,

Posters

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian Van Straalen, "UPC++: a PGAS C++ Library", ACM/IEEE Conference on Supercomputing, SC'17, November 2017,

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes", Poster at Exascale Computing Project (ECP) Annual Meeting 2017., January 2017,

Others

A Mignone, C Zanni, P Tzeferacos, B van Straalen, P Colella, G Bodo, The PLUTO code for adaptive mesh computations in astrophysical fluid dynamics, The Astrophysical Journal Supplement Series, Pages: 7 2012,