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Performance and Algorithms Research
Performance and Algorithms Research

Khaled Ibrahim

khaled
Khaled Z Ibrahim
Computer Scientist
Phone: +1 510 486 7467
Fax: +1 510 486 6900
Office: 59 3016
Mailing address: M/S 59R3022B, One Cyclotron Road
Berkeley, CA 94720 us

Khaled Ibrahim is a scientist with the Computational Research Division. He joined Lawrence Berkeley Laboratory in Jan. 2009. He obtained his PhD in computer engineering from North Carolina State University in 2003.

His research interests are:

  • Parallel Computer Architectures and High Performance Computing Machines.
  • Code optimization for high performance computing and the use of accelerators for cost/power effective supercomputing.
  • Virtualization and cloud computing environments for high performance computing.
  • Speculation techniques in shared-memory multiprocessor system.
  • Architectural support for secure computing on multiprocessor systems.
  • Performance modeling and simulation acceleration.
  • Power-aware scheduling of embedded applications on multiprocessor system-on-chip.

Journal Articles

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

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

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

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.

Nicholas Chaimov, Khaled Ibrahim, Samuel Williams, Costin Iancu, "Exploiting Communication Concurrency on High Performance Computing Systems", IJHPCA, April 17, 2015,

Khaled Z. Ibrahim, Steven Hofmeyr, Costin Iancu, "The Case for Partitioning Virtual Machines on Manycore Architectures", IEEE TPDS, April 17, 2014,

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

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

Khaled Z. Ibrahim, F. Bodin, "Efficient SIMDization and Data Management of the Lattice QCD Computation on the Cell Broadband Engine", Journal of Scientific computing, 2009, 17:153--172,

Khaled Z. Ibrahim, F. Bodin, Olivier Pene, "Fine-grained Parallelization of Lattice QCD Kernel Routine on GPUs", Journal of Parallel and Distributed Computing, 2008, 68:1350-1359,

Khaled Z. Ibrahim, Smail Niar, "Power-aware Bus Coscheduling for Periodic Realtime Applications Running on Multiprocessor SoC", Transactions on High-Performance Embedded Architectures and Compilers, 2007, 4:170--192,

Conference Papers

K. Ibrahim, L. Oliker,, "Preprocessing Pipeline Optimization for Scientific Deep-Learning Workloads", IPDPS 22, June 3, 2022,

Khaled Z. Ibrahim, Tan Nguyen, Hai Ah Nam, Wahid Bhimji, Steven Farrell, Leonid Oliker, Michael Rowan, Nicholas J. Wright, Samuel Williams, "Architectural Requirements for Deep Learning Workloads in HPC Environments", (BEST PAPER), Performance Modeling, Benchmarking, and Simulation (PMBS), November 2021,

T Groves, B Brock, Y Chen, KZ Ibrahim, L Oliker, NJ Wright, S Williams, K Yelick, "Performance Trade-offs in GPU Communication: A Study of Host and Device-initiated Approaches", Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis, January 2020, 126--137, doi: 10.1109/PMBS51919.2020.00016

Khaled Ibrahim, Samuel Williams, Leonid Oliker, "Performance Analysis of GPU Programming Models using the Roofline Scaling Trajectories", International Symposium on Benchmarking, Measuring and Optimizing (Bench), BEST PAPER AWARD, November 2019,

Khaled Ibrahim, Samuel Williams, Leonid Oliker, "Roofline Scaling Trajectories: A Method for Parallel Application and Architectural Performance Analysis", HPCS Special Session on High Performance Computing Benchmarking and Optimization (HPBench), July 2018,

George Michelogiannakis, Khaled Z. Ibrahim, John Shalf, Jeremiah J. Wilke, Samuel Knight, Joseph P. Kenny, "APHiD: Hierarchical Task Placement to Enable a Tapered Fat Tree Topology for Lower Power and Cost in HPC Networks", 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, IEEE, May 2017, LBNL 1007126,

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,

Nicholas Chaimov, Allen Malony, Shane Canon, Costin Iancu, Khaled Ibrahim, Jay Srinivasan, "Scaling Spark on HPC Systems", High Performance and Distributed Computing (HPDC), February 5, 2016,

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,

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,

Khaled Ibrahim, Paul Hargrove, Costin Iancu, Katherine Yelick, "A Performance Evaluation of One-Sided and Two-Sided Communication Paradigms on Relaxed-Ordering Interconnect", IPDPS 2014, April 17, 2014,

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

Miao Luo, Dhabaleswar K. Panda, Khaled Z. Ibrahim, Costin Iancu, "Congestion avoidance on manycore high performance computing systems", International Conference on Supercomputing (ICS), 2012,

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

KZ Ibrahim, S Hofmeyr, C Iancu, E Roman, "Optimized pre-copy live migration for memory intensive applications", Proceedings of 2011 SC - International Conference for High Performance Computing, Networking, Storage and Analysis, 2011, doi: 10.1145/2063384.2063437

KZ Ibrahim, S Hofmeyr, C Iancu, "Characterizing the performance of parallel applications on multi-socket virtual machines", Proceedings - 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2011, 2011, 1--12, doi: 10.1109/CCGrid.2011.50

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,

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,

Khaled Z. Ibrahim, "Bridging the Gap Between Complex Software Paradigms and Power-efficient Parallel Architectures", International Conference on Green Computing, 2010, 417-424,

Khaled Z. Ibrahim, J. Jaeger, Z. Liu, L.N. Pouchet, P. Lesnicki, L. Djoudi, D.Barthou, F. Bodin, C. Eisenbeis, G. Grosdidier, O. Pene, P. Roudeau, "Simulation of the Lattice QCD and Technological Trends in Computation", The 14th International Workshop on Compilers for Parallel Computers (CPC 09), 2009,

Khaled Z. Ibrahim, F. Bodin, "Implementing Wilson-Dirac Operator on the Cell Broadband Engine", The 22nd ACM/SIGARCH International Conference on Supercomputing, 2008, 4--14,

Melhem Tawk, Khaled Z. Ibrahim, Smail Niar, "Multi-granularity Sampling for Simulating Concurrent Heterogeneous Applications", CASES 08: The 2008 international conference on Compilers, architectures and synthesis for embedded systems, 2008, 217--226,

Khaled Z. Ibrahim, F. Bodin, Olivier Pene, "Fine-grained Parallelization of Lattice QCD Kernel Routine on GPU", First Workshop on General Purpose Processing on Graphics Processing Units, 2007,

Melhem Tawk, Khaled Z. Ibrahim, Smail Niar, "Adaptive Sampling for Efficient MPSoC Architecture Simulation", The 15th IEEE international Symposium on Modeling Analysis, and Simulation of Computer and Telecommunication Systems, 2007, 186-192,

Melhem Tawk, Khaled Z. Ibrahim, Smail Niar, "Simulation acceleration for MPSOC Performance and Power Consumption Evaluation", Architectures and Compilers for Embedded Systems (ACES) Symposium, 2006,

Khaled Z. Ibrahim, "Efficient Architectural Support for Secure Bus-based Shared Memory Multiprocessor", The tenth Asia-Pacific Computer Systems Architecture Conference (ACSAC 05), 2005,

Khaled Z. Ibrahim, "Correlation between Detailed and Simplified Simulations in Studying Multiprocessor Architecture", The IEEE International Conference in Computer Design (ICCD 05), 2005, 387--392,

Khaled Z. Ibrahim, Gregory T. Byrd, "Extending OpenMP to Support Slipstream Execution Mode", The 17th International Parallel and Distributed Processing Symposium (IPDPS 03), 2003, 36--44,

Khaled Z. Ibrahim, Gregory T. Byrd, Eric Rotenberg, "Slipstream Execution Mode for CMP-based Multiprocessors", The 9th International Conference on High-Performance Computer Architecture (HPCA 03), 2003, 179--190,

Khaled Z. Ibrahim, Gregory T. Byrd, "On the Exploitation of Value Prediction and Producer Identification to Reduce Barrier Synchronization Time", The 15th International Parallel and Distributed Processing Symposium (IPDPS 01), 2001, 43--50,

Book Chapters

Khaled Z. Ibrahim, editors: I. Ahmad, S. Ranka, "Code Development and Migration of High Performance Applications to Power-efficient Architectures", (Handbook on Energy-Aware and Green Computing:Chapman and Hall/CRC Press: 2012)

Presentation/Talks

Khaled Ibrahim, Roofline on GPUs (advanced topics), ECP Annual Meeting, April 2021,

Reports

Roel Van Beeumen, Khaled Z. Ibrahim, Gregory D. Kahanamoku-Meyer, Norman Y. Yao, Chao Yang, "Enhancing Scalability of a Matrix-Free Eigensolver for Studying Many-Body Localization", December 1, 2020,

John Bachan, Scott Baden, Dan Bonachea, Paul H. 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 H. 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 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, Brian van Straalen, "UPC++ Programmer’s Guide, v1.0-2017.9", Lawrence Berkeley National Laboratory Tech Report, September 2017, LBNL 2001065, doi: 10.2172/1398522

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 H. 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

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.

Khaled Z. Ibrahim, Evgeny Epifanovsky, Samuel Williams, Anna I. Krylov, "Cross-scale Efficient Tensor Contractions for Coupled Cluster Computations Through Multiple Programming Model Backends (tech report version)", LBNL. - Report Number: LBNL-1005853, July 1, 2016, LBNL 1005853, doi: 10.2172/1274416

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,

Posters

Samuel Williams, Charlene Yang, Khaled Ibrahim, Thorsten Kurth, Nan Ding, Jack Deslippe, Leonid Oliker, "Performance Analysis using the Roofline Model", SciDAC PI Meeting, July 2019,

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 (ECP'18)", 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", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'17) Research Poster, November 2017,

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,

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,

Others

Khaled Z. Ibrahim, Slipstream execution mode for cmp-based shared memory systems, PHD Thesis, NCSU, 2003,

Last edited: 06/27/2022
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