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Samuel Williams 0001
Samuel W. Williams
Person information
- affiliation: Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- affiliation (PhD 2008): University of California at Berkeley, CA, USA
Other persons with the same name
- Samuel Williams — disambiguation page
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2020 – today
- 2024
- [j27]Nan Ding
, Pieter Maris, Hai Ah Nam, Taylor L. Groves
Evaluating the potential of disaggregated memory systems for HPC applications. Concurr. Comput. Pract. Exp. 36(19) (2024) - [j26]Mahesh Lakshminarasimhan
Bricks: A high-performance portability layer for computations on block-structured grids. Int. J. High Perform. Comput. Appl. 38(6): 549-567 (2024) - [c72]Mahesh Lakshminarasimhan
BrickDL: Graph-Level Optimizations for DNNs with Fine-Grained Data Blocking on GPUs. ICPP 2024: 576-586 - [i10]Zhe Bai, Xishuo Wei, William Tang, Leonid Oliker, Zhihong Lin, Samuel Williams:
FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural Networks. CoRR abs/2404.17466 (2024) - [i9]Xuan Jiang, Raja Sengupta, James Demmel, Samuel Williams:
LPSim: Large Scale Multi-GPU Parallel Computing based Regional Scale Traffic Simulation Framework. CoRR abs/2406.08496 (2024) - [i8]Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji:
Comprehensive Performance Modeling and System Design Insights for Foundation Models. CoRR abs/2410.00273 (2024) - 2023
- [c71]Yang Liu
Unified Communication Optimization Strategies for Sparse Triangular Solver on CPU and GPU Clusters. SC 2023: 50:1-50:15 - [c70]Oscar Antepara
Performance Portability Evaluation of Blocked Stencil Computations on GPUs. SC Workshops 2023: 1005-1018 - [c69]Nan Ding
Evaluating the Performance of One-sided Communication on CPUs and GPUs. SC Workshops 2023: 1059-1069 - [c68]Oscar Antepara
Performance-Portable GPU Acceleration of the EFIT Tokamak Plasma Equilibrium Reconstruction Code. SC Workshops 2023: 1939-1948 - [i7]Nan Ding, Pieter Maris, Hai Ah Nam, Taylor L. Groves, Muaaz Gul Awan, LeAnn Lindsey
Evaluating the Potential of Disaggregated Memory Systems for HPC applications. CoRR abs/2306.04014 (2023) - 2022
- [j25]Nan Ding
Instruction Roofline: An insightful visual performance model for GPUs. Concurr. Comput. Pract. Exp. 34(20) (2022) - [j24]Tan Nguyen
FPGA-based HPC accelerators: An evaluation on performance and energy efficiency. Concurr. Comput. Pract. Exp. 34(20) (2022) - [j23]Marco Siracusa
A Comprehensive Methodology to Optimize FPGA Designs via the Roofline Model. IEEE Trans. Computers 71(8): 1903-1915 (2022) - [c67]Benjamin Sepanski, Tuowen Zhao, Hans Johansen
Maximizing Performance Through Memory Hierarchy-Driven Data Layout Transformations. MCHPC@SC 2022: 1-10 - [c66]Taylor L. Groves, Christopher S. Daley, Rahulkumar Gayatri, Hai Ah Nam, Nan Ding, Lenny Oliker, Nicholas J. Wright, Samuel Williams
A Methodology for Evaluating Tightly-integrated and Disaggregated Accelerated Architectures. PMBS@SC 2022: 71-81 - [i6]Sridutt Bhalachandra, Brian Austin, Samuel Williams
Understanding the Impact of Input Entropy on FPU, CPU, and GPU Power. CoRR abs/2212.08805 (2022) - 2021
- [c65]Nan Ding, Yang Liu, Samuel Williams, Xiaoye S. Li:
A Message-Driven, Multi-GPU Parallel Sparse Triangular Solver. ACDA 2021: 147-159 - [c64]Douglas Doerfler
Experiences Porting the SU3_Bench Microbenchmark to the Intel Arria 10 and Xilinx Alveo U280 FPGAs. IWOCL 2021: 1:1-1:9 - [c63]Khaled Z. Ibrahim, Tan Nguyen, Hai Ah Nam, Wahid Bhimji
Architectural Requirements for Deep Learning Workloads in HPC Environments. PMBS 2021: 7-17 - [c62]Tuowen Zhao
Improving communication by optimizing on-node data movement with data layout. PPoPP 2021: 304-317 - [c61]Charlene Yang, Yunsong Wang
Hierarchical Roofline Performance Analysis for Deep Learning Applications. SAI (2) 2021: 473-491 - 2020
- [j22]Wenjing Ma, Yulong Ao, Chao Yang
Solving a trillion unknowns per second with HPGMG on Sunway TaihuLight. Clust. Comput. 23(2): 493-507 (2020) - [j21]Charlene Yang
Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC-9 Perlmutter system. Concurr. Comput. Pract. Exp. 32(20) (2020) - [c60]Marco Siracusa
A CAD-based methodology to optimize HLS code via the Roofline model. ICCAD 2020: 116:1-116:9 - [c59]Anastasiia Butko, George Michelogiannakis
Understanding Quantum Control Processor Capabilities and Limitations through Circuit Characterization. ICRC 2020: 66-75 - [c58]Christopher S. Daley
A Case Study of Porting HPGMG from CUDA to OpenMP Target Offload. IWOMP 2020: 37-51 - [c57]Tan Nguyen, Samuel Williams
The Performance and Energy Efficiency Potential of FPGAs in Scientific Computing. PMBS@SC 2020: 8-19 - [c56]Taylor L. Groves, Ben Brock, Yuxin Chen, Khaled Z. Ibrahim, Lenny Oliker, Nicholas J. Wright
Performance Trade-offs in GPU Communication: A Study of Host and Device-initiated Approaches. PMBS@SC 2020: 126-137 - [c55]Nan Ding, Samuel Williams, Yang Liu, Xiaoye S. Li:
Leveraging One-Sided Communication for Sparse Triangular Solvers. PP 2020: 93-105 - [c54]Yunsong Wang
Time-Based Roofline for Deep Learning Performance Analysis. DLS@SC 2020: 10-19 - [c53]Jonathan R. Madsen, Muaaz G. Awan, Hugo Brunie, Jack Deslippe, Rahulkumar Gayatri, Leonid Oliker, Yunsong Wang
Timemory: Modular Performance Analysis for HPC. ISC 2020: 434-452 - [i5]Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams:
Time-Based Roofline for Deep Learning Performance Analysis. CoRR abs/2009.04598 (2020) - [i4]Yunsong Wang, Charlene Yang, Steven Farrell, Thorsten Kurth, Samuel Williams:
Hierarchical Roofline Performance Analysis for Deep Learning Applications. CoRR abs/2009.05257 (2020)
2010 – 2019
- 2019
- [j20]Bei Wang, Stéphane Ethier, William M. Tang
Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers. Int. J. High Perform. Comput. Appl. 33(1) (2019) - [j19]Weiqun Zhang
AMReX: a framework for block-structured adaptive mesh refinement. J. Open Source Softw. 4(37): 1370 (2019) - [c52]Khaled Z. Ibrahim, Samuel Williams
Performance Analysis of GPU Programming Models Using the Roofline Scaling Trajectories. Bench 2019: 3-19 - [c51]Nan Ding, Samuel Williams
An Instruction Roofline Model for GPUs. PMBS@SC 2019: 7-18 - [c50]Tuowen Zhao
Exploiting reuse and vectorization in blocked stencil computations on CPUs and GPUs. SC 2019: 52:1-52:44 - 2018
- [c49]Khaled Z. Ibrahim, Samuel Williams
Roofline Scaling Trajectories: A Method for Parallel Application and Architectural Performance Analysis. HPCS 2018: 350-358 - [c48]Tuowen Zhao
SIMD code generation for stencils on brick decompositions. PPoPP 2018: 423-424 - [c47]Hongzhang Shan, Samuel Williams
Improving MPI Reduction Performance for Manycore Architectures with OpenMP and Data Compression. PMBS@SC 2018: 1-11 - [c46]Tuomas Koskela
A Novel Multi-level Integrated Roofline Model Approach for Performance Characterization. ISC 2018: 226-245 - 2017
- [j18]Nicholas Chaimov
Reaching bandwidth saturation using transparent injection parallelization. Int. J. High Perform. Comput. Appl. 31(5): 405-421 (2017) - [j17]Khaled Z. Ibrahim, Evgeny Epifanovsky, Samuel Williams
Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends. J. Parallel Distributed Comput. 106: 92-105 (2017) - [j16]Protonu Basu, Samuel Williams
Compiler-based code generation and autotuning for geometric multigrid on GPU-accelerated supercomputers. Parallel Comput. 64: 50-64 (2017) - [j15]Hasan Metin Aktulga
A High Performance Block Eigensolver for Nuclear Configuration Interaction Calculations. IEEE Trans. Parallel Distributed Syst. 28(6): 1550-1563 (2017) - [c45]Nathan Zhang, Michael B. Driscoll, Charles Markley, Samuel Williams
Snowflake: A Lightweight Portable Stencil DSL. IPDPS Workshops 2017: 795-804 - [c44]Bryce Adelstein-Lelbach, Hans Johansen
Simultaneously Solving Swarms of Small Sparse Systems on SIMD Silicon. IPDPS Workshops 2017: 1128-1137 - [c43]Hongzhang Shan, Samuel Williams
A Locality-Based Threading Algorithm for the Configuration-Interaction Method. IPDPS Workshops 2017: 1178-1187 - [c42]Philip C. Roth, Hongzhang Shan, David Riegner, Nikolas Antolin, Sarat Sreepathi
Performance analysis and optimization of the RAMPAGE metal alloy potential generation software. SEPS@SPLASH 2017: 11-20 - [c41]Thorsten Kurth, William Arndt, Taylor Barnes, Brandon Cook, Jack Deslippe, Douglas Doerfler
Analyzing Performance of Selected NESAP Applications on the Cori HPC System. ISC Workshops 2017: 334-347 - [c40]Brandon Cook, Thorsten Kurth, Brian Austin, Samuel Williams
Performance Variability on Xeon Phi. ISC Workshops 2017: 419-429 - 2016
- [j14]Pieter Ghysels, Xiaoye S. Li, François-Henry Rouet, Samuel Williams
An Efficient Multicore Implementation of a Novel HSS-Structured Multifrontal Solver Using Randomized Sampling. SIAM J. Sci. Comput. 38(5) (2016) - [j13]Ariful Azad, Grey Ballard
Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication. SIAM J. Sci. Comput. 38(6) (2016) - [c39]Zhaoyi Meng, Alice Koniges
OpenMP Parallelization and Optimization of Graph-Based Machine Learning Algorithms. IWOMP 2016: 17-31 - [c38]Hongzhang Shan, Samuel Williams
Experiences of Applying One-Sided Communication to Nearest-Neighbor Communication. PAW@SC 2016: 17-24 - [c37]Taylor Barnes, Brandon Cook, Jack Deslippe, Douglas Doerfler
Evaluating and Optimizing the NERSC Workload on Knights Landing. PMBS@SC 2016: 43-53 - [c36]William M. Tang
Extreme scale plasma turbulence simulations on top supercomputers worldwide. SC 2016: 502-513 - [c35]Douglas Doerfler
Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor. ISC Workshops 2016: 339-353 - 2015
- [j12]Didem Unat
ExaSAT: An exascale co-design tool for performance modeling. Int. J. High Perform. Comput. Appl. 29(2): 209-232 (2015) - [j11]Adam Lugowski
Parallel processing of filtered queries in attributed semantic graphs. J. Parallel Distributed Comput. 79-80: 115-131 (2015) - [c34]Abhinav Sarje, Sukhyun Song, Douglas Jacobsen, Kevin A. Huck
Parallel Performance Optimizations on Unstructured Mesh-based Simulations. ICCS 2015: 2016-2025 - [c33]Protonu Basu, Mary W. Hall
Compiler-Directed Transformation for Higher-Order Stencils. IPDPS 2015: 313-323 - [c32]Alex Druinsky, Pieter Ghysels, Xiaoye S. Li, Osni Marques, Samuel Williams
Comparative Performance Analysis of Coarse Solvers for Algebraic Multigrid on Multicore and Manycore Architectures. PPAM (1) 2015: 116-127 - [c31]Hongzhang Shan, Samuel Williams
Thread-level parallelization and optimization of NWChem for the Intel MIC architecture. PMAM@PPoPP 2015: 58-67 - [c30]Nicholas Chaimov
Exploiting communication concurrency on high performance computing systems. PMAM@PPoPP 2015: 132-143 - [c29]Hongzhang Shan, Samuel Williams
Parallel implementation and performance optimization of the configuration-interaction method. SC 2015: 9:1-9:12 - [i3]Pieter Ghysels, Xiaoye S. Li, François-Henry Rouet, Samuel Williams, Artem Napov:
An efficient multi-core implementation of a novel HSS-structured multifrontal solver using randomized sampling. CoRR abs/1502.07405 (2015) - [i2]Ariful Azad, Grey Ballard, Aydin Buluç, James Demmel, Laura Grigori, Oded Schwartz, Sivan Toledo, Samuel Williams:
Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication. CoRR abs/1510.00844 (2015) - [i1]Bei Wang, Stéphane Ethier, William M. Tang, Khaled Z. Ibrahim, Kamesh Madduri, Samuel Williams, Leonid Oliker:
Modern Gyrokinetic Particle-In-Cell Simulation of Fusion Plasmas on Top Supercomputers. CoRR abs/1510.05546 (2015) - 2014
- [c28]Khaled Z. Ibrahim, Samuel W. Williams
Analysis and tuning of libtensor framework on multicore architectures. HiPC 2014: 1-10 - [c27]George Michelogiannakis
Collective memory transfers for multi-core chips. ICS 2014: 343-352 - [c26]Samuel Williams
s-Step Krylov Subspace Methods as Bottom Solvers for Geometric Multigrid. IPDPS 2014: 1149-1158 - [c25]Hasan Metin Aktulga
Optimizing Sparse Matrix-Multiple Vectors Multiplication for Nuclear Configuration Interaction Calculations. IPDPS 2014: 1213-1222 - [c24]Hongzhang Shan, Amir Kamil
Evaluation of PGAS Communication Paradigms with Geometric Multigrid. PGAS 2014: 8:1-8:12 - [c23]Yu Jung Lo, Samuel Williams
Roofline Model Toolkit: A Practical Tool for Architectural and Program Analysis. PMBS@SC 2014: 129-148 - 2013
- [j10]Khaled Z. Ibrahim, Kamesh Madduri
Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms. Int. J. High Perform. Comput. Appl. 27(4): 454-473 (2013) - [c22]Protonu Basu, Anand Venkat, Mary W. Hall
Compiler generation and autotuning of communication-avoiding operators for geometric multigrid. HiPC 2013: 452-461 - [c21]Aydin Buluç
High-Productivity and High-Performance Analysis of Filtered Semantic Graphs. IPDPS 2013: 237-248 - [c20]Christopher D. Krieger, Michelle Mills Strout, Catherine Olschanowsky, Andrew Stone, Stephen M. Guzik, Xinfeng Gao, Carlo Bertolli, Paul H. J. Kelly, Gihan R. Mudalige
Loop Chaining: A Programming Abstraction for Balancing Locality and Parallelism. IPDPS Workshops 2013: 375-384 - [c19]Bei Wang
Kinetic turbulence simulations at extreme scale on leadership-class systems. SC 2013: 82:1-82:12 - 2012
- [j9]Kamesh Madduri
Optimization of Parallel Particle-to-Grid Interpolation on Leading Multicore Platforms. IEEE Trans. Parallel Distributed Syst. 23(10): 1915-1922 (2012) - [c18]Aydin Buluç
High-performance analysis of filtered semantic graphs. PACT 2012: 463-464 - [c17]Samuel Williams
Optimization of geometric multigrid for emerging multi- and manycore processors. SC 2012: 96 - [c16]Bei Wang
Abstract: Advances in Gyrokinetic Particle in Cell Simulation for Fusion Plasmas to Extreme Scale. SC Companion 2012: 1439-1440 - [c15]Bei Wang, Stéphane Ethier, William M. Tang, Khaled Z. Ibrahim, Kamesh Madduri, Samuel W. Williams, Leonid Oliker, Timothy J. Williams:
Poster: Advances in Gyrokinetic Particle in Cell Simulation for Fusion Plasmas to Extreme Scale. SC Companion 2012: 1441 - 2011
- [j8]Kamesh Madduri
Gyrokinetic particle-in-cell optimization on emerging multi- and manycore platforms. Parallel Comput. 37(9): 501-520 (2011) - [c14]Aydin Buluç
Reduced-Bandwidth Multithreaded Algorithms for Sparse Matrix-Vector Multiplication. IPDPS 2011: 721-733 - [c13]Kamesh Madduri
Gyrokinetic toroidal simulations on leading multi- and manycore HPC systems. SC 2011: 23:1-23:12 - [c12]Samuel Williams
Extracting ultra-scale Lattice Boltzmann performance via hierarchical and distributed auto-tuning. SC 2011: 55:1-55:12 - [c11]Jens Krueger, David Donofrio, John Shalf
Hardware/software co-design for energy-efficient seismic modeling. SC 2011: 73:1-73:12 - 2010
- [c10]Aparna Chandramowlishwaran
Optimizing and tuning the fast multipole method for state-of-the-art multicore architectures. IPDPS 2010: 1-12 - [c9]Shoaib Kamil, Cy P. Chan, Leonid Oliker, John Shalf
An auto-tuning framework for parallel multicore stencil computations. IPDPS 2010: 1-12 - [p2]Samuel Williams, Nathan Bell, Jee Whan Choi, Michael Garland, Leonid Oliker, Richard Vu:
Sparse Matrix-Vector Multiplication on Multicore and Accelerators. Scientific Computing with Multicore and Accelerators 2010: 83-109 - [p1]Kaushik Datta, Samuel Williams
Auto-Tuning Stencil Computations on Multicore and Accelerators. Scientific Computing with Multicore and Accelerators 2010: 219-253
2000 – 2009
- 2009
- [j7]Samuel Williams
Roofline: an insightful visual performance model for multicore architectures. Commun. ACM 52(4): 65-76 (2009) - [j6]Shujia Zhou, Daniel C. Duffy, Tom Clune, Max Suarez, Samuel Williams
The impact of IBM Cell technology on the programming paradigm in the context of computer systems for climate and weather models. Concurr. Comput. Pract. Exp. 21(17): 2176-2186 (2009) - [j5]Samuel Williams
Optimization of a lattice Boltzmann computation on state-of-the-art multicore platforms. J. Parallel Distributed Comput. 69(9): 762-777 (2009) - [j4]Samuel Williams
Optimization of sparse matrix-vector multiplication on emerging multicore platforms. Parallel Comput. 35(3): 178-194 (2009) - [j3]Kaushik Datta, Shoaib Kamil, Samuel Williams
Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors. SIAM Rev. 51(1): 129-159 (2009) - [c8]Joseph Gebis, Leonid Oliker, John Shalf
Improving Memory Subsystem Performance Using ViVA: Virtual Vector Architecture. ARCS 2009: 146-158 - [c7]Kamesh Madduri
Memory-efficient optimization of Gyrokinetic particle-to-grid interpolation for multicore processors. SC 2009 - [c6]Marghoob Mohiyuddin, Mark Murphy, Leonid Oliker, John Shalf
A design methodology for domain-optimized power-efficient supercomputing. SC 2009 - 2008
- [c5]Samuel Williams
Lattice Boltzmann simulation optimization on leading multicore platforms. IPDPS 2008: 1-14 - [c4]Kaushik Datta, Mark Murphy, Vasily Volkov, Samuel Williams
Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures. SC 2008: 4 - 2007
- [j2]Samuel Williams
Scientific Computing Kernels on the Cell Processor. Int. J. Parallel Program. 35(3): 263-298 (2007) - [c3]Samuel Williams
Optimization of sparse matrix-vector multiplication on emerging multicore platforms. SC 2007: 38 - 2006
- [c2]Shoaib Kamil, Kaushik Datta, Samuel Williams
Implicit and explicit optimizations for stencil computations. Memory System Performance and Correctness 2006: 51-60 - [c1]Samuel Williams
The potential of the cell processor for scientific computing. Conf. Computing Frontiers 2006: 9-20 - 2001
- [j1]Christoforos E. Kozyrakis, David Judd, Joseph Gebis, Samuel Williams
Hardware/compiler codevelopment for an embedded media processor. Proc. IEEE 89(11): 1694-1709 (2001)
Coauthor Index
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