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James Demmel
James Weldon Demmel – Jim Demmel
Person information
- affiliation: University of California, Berkeley, USA
- award (2014): Paris Kanellakis Award
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2020 – today
- 2024
- [j94]Hengrui Luo
, Younghyun Cho
, James Weldon Demmel, Igor Kozachenko, Xiaoye S. Li
, Yang Liu
:
Non-smooth Bayesian optimization in tuning scientific applications. Int. J. High Perform. Comput. Appl. 38(6): 633-657 (2024) - [j93]Michael Christ, James Demmel, Nicholas Knight, Thomas Scanlon, Katherine A. Yelick:
On Multilinear Inequalities of Holder-Brascamp-Lieb Type for Torsion-Free Discrete Abelian Groups. J. Log. Anal. 16 (2024) - [j92]Chaoyu Gong
, Jim Demmel
, Yang You
:
Scalable Evidential K-Nearest Neighbor Classification on Big Data. IEEE Trans. Big Data 10(3): 226-237 (2024) - [j91]Chaoyu Gong
, Jim Demmel
, Yang You
:
Distributed and Joint Evidential K-Nearest Neighbor Classification. IEEE Trans. Knowl. Data Eng. 36(11): 5972-5985 (2024) - [c117]Tianyu Liang, Riley Murray, Aydin Buluç, James Demmel:
Fast multiplication of random dense matrices with sparse matrices. IPDPS 2024: 52-62 - [c116]Vivek Bharadwaj
, Osman Asif Malik
, Riley Murray
, Aydin Buluç
, James Demmel
:
Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition. SPAA 2024: 155-168 - [i57]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) - [i56]Ziming Liu, Shaoyu Wang, Shenggan Cheng, Zhongkai Zhao, Xuanlei Zhao, James Demmel, Yang You:
WallFacer: Guiding Transformer Model Training Out of the Long-Context Dark Forest with N-body Problem. CoRR abs/2407.00611 (2024) - [i55]Ahmad Abdelfattah, Willow Ahrens, Hartwig Anzt, Chris Armstrong, Ben Brock, Aydin Buluç, Federico Busato, Terry Cojean, Timothy A. Davis, Jim Demmel, Grace Dinh, David Gardener, Jan Fiala, Mark Gates, Azzam Haider, Toshiyuki Imamura, Pedro Valero-Lara, José E. Moreira, Xiaoye Sherry Li, Piotr Luszczek, Max Melichenko, Jose Moeira, Yvan Mokwinski, Riley Murray, Spencer Patty, Slaven Peles, Tobias Ribizel, E. Jason Riedy, Siva Rajamanickam, Piyush Sao, Manu Shantharam, Keita Teranishi, Stan Tomov, Yu-Hsiang Tsai, Heiko K. Weichelt:
Interface for Sparse Linear Algebra Operations. CoRR abs/2411.13259 (2024) - 2023
- [j90]James Demmel:
Nearly Optimal Block-Jacobi Preconditioning. SIAM J. Matrix Anal. Appl. 44(1): 408-413 (2023) - [j89]James Demmel, Laura Grigori, Alexander Rusciano
:
An Improved Analysis and Unified Perspective on Deterministic and Randomized Low-Rank Matrix Approximation. SIAM J. Matrix Anal. Appl. 44(2): 559-591 (2023) - [c115]Younghyun Cho, James Weldon Demmel, Jacob King
, Xiaoye S. Li, Yang Liu, Hengrui Luo:
Harnessing the Crowd for Autotuning High-Performance Computing Applications. IPDPS 2023: 635-645 - [c114]Vivek Bharadwaj, Osman Asif Malik, Riley Murray, Laura Grigori, Aydin Buluç, James Demmel:
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition. NeurIPS 2023 - [i54]Vivek Bharadwaj, Osman Asif Malik, Riley Murray, Laura Grigori, Aydin Buluç
, James Demmel:
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition. CoRR abs/2301.12584 (2023) - [i53]Riley Murray
, James Demmel, Michael W. Mahoney, N. Benjamin Erichson, Maksim Melnichenko, Osman Asif Malik, Laura Grigori, Piotr Luszczek, Michal Derezinski
, Miles E. Lopes, Tianyu Liang, Hengrui Luo, Jack J. Dongarra:
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software. CoRR abs/2302.11474 (2023) - [i52]James Demmel, Ioana Dumitriu, Ryan Schneider:
Generalized Pseudospectral Shattering and Inverse-Free Matrix Pencil Diagonalization. CoRR abs/2306.03700 (2023) - [i51]Daniel Zou, Xinchen Jin, Xueyang Yu, Hao Zhang, James Demmel:
Computron: Serving Distributed Deep Learning Models with Model Parallel Swapping. CoRR abs/2306.13835 (2023) - [i50]Younghyun Cho, James Weldon Demmel, Michal Derezinski
, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley J. Murray:
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems. CoRR abs/2308.15720 (2023) - [i49]Tianyu Liang, Riley Murray
, Aydin Buluç
, James Demmel:
Fast multiplication of random dense matrices with fixed sparse matrices. CoRR abs/2310.15419 (2023) - [i48]Maksim Melnichenko, Oleg Balabanov, Riley Murray
, James Demmel, Michael W. Mahoney, Piotr Luszczek:
CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT). CoRR abs/2311.08316 (2023) - 2022
- [c113]James Demmel, Jack J. Dongarra, Mark Gates
, Greg Henry, Julien Langou
, Xiaoye S. Li, Piotr Luszczek, Weslley S. Pereira, E. Jason Riedy, Cindy Rubio-González:
Proposed Consistent Exception Handling for the BLAS and LAPACK. Correctness@SC 2022: 1-9 - [c112]Vivek Bharadwaj
, Aydin Buluç
, James Demmel:
Distributed-Memory Sparse Kernels for Machine Learning. IPDPS 2022: 47-58 - [c111]Anthony Chen
, James Demmel, Grace Dinh, Mason Haberle, Olga Holtz
:
Communication bounds for convolutional neural networks. PASC 2022: 1:1-1:10 - [i47]Vivek Bharadwaj, Aydin Buluç
, James Demmel:
Distributed-Memory Sparse Kernels for Machine Learning. CoRR abs/2203.07673 (2022) - [i46]Anthony Chen, James Demmel, Grace Dinh, Mason Haberle, Olga Holtz:
Communication Bounds for Convolutional Neural Networks. CoRR abs/2204.08279 (2022) - [i45]Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu:
Hybrid Models for Mixed Variables in Bayesian Optimization. CoRR abs/2206.01409 (2022) - [i44]James Demmel, Jack J. Dongarra, Mark Gates
, Greg Henry, Julien Langou, Xiaoye S. Li, Piotr Luszczek, Weslley da Silva Pereira, E. Jason Riedy, Cindy Rubio-González:
Proposed Consistent Exception Handling for the BLAS and LAPACK. CoRR abs/2207.09281 (2022) - [i43]Vivek Bharadwaj, Osman Asif Malik, Riley Murray
, Aydin Buluç
, James Demmel:
Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition. CoRR abs/2210.05105 (2022) - 2021
- [j88]Yang You
, Jingyue Huang
, Cho-Jui Hsieh, Richard W. Vuduc, James Demmel:
Communication-avoiding kernel ridge regression on parallel and distributed systems. CCF Trans. High Perform. Comput. 3(3): 252-270 (2021) - [j87]Edgar Solomonik
, James Demmel:
Fast Bilinear Algorithms for Symmetric Tensor Contractions. Comput. Methods Appl. Math. 21(1): 211-231 (2021) - [j86]Swapnil Das, James Demmel, Kimon Fountoulakis, Laura Grigori, Michael W. Mahoney, Shenghao Yang
:
Parallel and Communication Avoiding Least Angle Regression. SIAM J. Sci. Comput. 43(2): C154-C176 (2021) - [j85]Edgar Solomonik, James Demmel, Torsten Hoefler:
Communication Lower Bounds of Bilinear Algorithms for Symmetric Tensor Contractions. SIAM J. Sci. Comput. 43(5): A3328-A3356 (2021) - [c110]Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar:
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. IPDPS Workshops 2021: 947-950 - [c109]Qijing Huang
, Aravind Kalaiah, Minwoo Kang, James Demmel, Grace Dinh, John Wawrzynek, Thomas Norell, Yakun Sophia Shao:
CoSA: Scheduling by Constrained Optimization for Spatial Accelerators. ISCA 2021: 554-566 - [c108]Younghyun Cho, James Demmel, Xiaoye S. Li, Yang Liu, Hengrui Luo:
Enhancing Autotuning Capability with a History Database. MCSoC 2021: 249-257 - [c107]Yang Liu, Wissam M. Sid-Lakhdar, Osni Marques, Xinran Zhu
, Chang Meng, James Weldon Demmel, Xiaoye S. Li:
GPTune: multitask learning for autotuning exascale applications. PPoPP 2021: 234-246 - [c106]Ruobing Han, Min Si, James Demmel, Yang You:
Dynamic scaling for low-precision learning. PPoPP 2021: 480-482 - [c105]Ruobing Han, James Demmel, Yang You:
Auto-Precision Scaling for Distributed Deep Learning. ISC 2021: 79-97 - [i42]Qijing Huang, Minwoo Kang, Grace Dinh, Thomas Norell, Aravind Kalaiah, James Demmel, John Wawrzynek, Yakun Sophia Shao:
CoSA: Scheduling by Constrained Optimization for Spatial Accelerators. CoRR abs/2105.01898 (2021) - [i41]Hengrui Luo, James Weldon Demmel, Younghyun Cho, Xiaoye S. Li, Yang Liu:
Non-smooth Bayesian Optimization in Tuning Problems. CoRR abs/2109.07563 (2021) - 2020
- [j84]Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel:
Fast LSTM by dynamic decomposition on cloud and distributed systems. Knowl. Inf. Syst. 62(11): 4169-4197 (2020) - [j83]Osni Marques, James Demmel, Paulo B. Vasconcelos
:
Bidiagonal SVD Computation via an Associated Tridiagonal Eigenproblem. ACM Trans. Math. Softw. 46(2): 14:1-14:25 (2020) - [j82]Willow Ahrens
, James Demmel, Hong Diep Nguyen:
Algorithms for Efficient Reproducible Floating Point Summation. ACM Trans. Math. Softw. 46(3): 22:1-22:49 (2020) - [c104]Aditya Devarakonda
, James Demmel:
Avoiding Communication in Logistic Regression. HiPC 2020: 91-100 - [c103]Arissa Wongpanich, Yang You, James Demmel:
Rethinking the Value of Asynchronous Solvers for Distributed Deep Learning. HPC Asia 2020: 52-60 - [c102]Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, Cho-Jui Hsieh:
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes. ICLR 2020 - [c101]Grace Dinh, James Demmel:
Communication-Optimal Tilings for Projective Nested Loops with Arbitrary Bounds. SPAA 2020: 523-525 - [i40]Grace Dinh, James Demmel:
Communication-Optimal Tilings for Projective Nested Loops with Arbitrary Bounds. CoRR abs/2003.00119 (2020) - [i39]Yang You, Yuhui Wang, Huan Zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh:
The Limit of the Batch Size. CoRR abs/2006.08517 (2020) - [i38]Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar:
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. CoRR abs/2011.00071 (2020) - [i37]Aditya Devarakonda, James Demmel:
Avoiding Communication in Logistic Regression. CoRR abs/2011.08281 (2020)
2010 – 2019
- 2019
- [j81]Aditya Devarakonda
, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding Communication in Primal and Dual Block Coordinate Descent Methods. SIAM J. Sci. Comput. 41(1): C1-C27 (2019) - [j80]Yang You
, Zhao Zhang
, Cho-Jui Hsieh, James Demmel, Kurt Keutzer:
Fast Deep Neural Network Training on Distributed Systems and Cloud TPUs. IEEE Trans. Parallel Distributed Syst. 30(11): 2449-2462 (2019) - [c100]Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel:
Fast LSTM Inference by Dynamic Decomposition on Cloud Systems. ICDM 2019: 748-757 - [c99]Yang You, Jonathan Hseu, Chris Ying, James Demmel, Kurt Keutzer, Cho-Jui Hsieh:
Large-batch training for LSTM and beyond. SC 2019: 9:1-9:16 - [i36]Yang You, Jonathan Hseu, Chris Ying, James Demmel, Kurt Keutzer, Cho-Jui Hsieh:
Large-Batch Training for LSTM and Beyond. CoRR abs/1901.08256 (2019) - [i35]Yang You, Jing Li, Jonathan Hseu, Xiaodan Song, James Demmel, Cho-Jui Hsieh:
Reducing BERT Pre-Training Time from 3 Days to 76 Minutes. CoRR abs/1904.00962 (2019) - [i34]Swapnil Das, Jim Demmel, Kimon Fountoulakis, Laura Grigori, Michael W. Mahoney:
Parallel and Communication Avoiding Least Angle Regression. CoRR abs/1905.11340 (2019) - [i33]Wissam M. Sid-Lakhdar, Mohsen Mahmoudi Aznaveh, Xiaoye S. Li, James Weldon Demmel:
Multitask and Transfer Learning for Autotuning Exascale Applications. CoRR abs/1908.05792 (2019) - [i32]Grey Ballard
, James Demmel, Ioana Dumitriu, Alexander Rusciano:
A Generalized Randomized Rank-Revealing Factorization. CoRR abs/1909.06524 (2019) - [i31]James Demmel, Laura Grigori, Alexander Rusciano:
An improved analysis and unified perspective on deterministic and randomized low rank matrix approximations. CoRR abs/1910.00223 (2019) - [i30]Ruobing Han, Yang You, James Demmel:
Auto-Precision Scaling for Distributed Deep Learning. CoRR abs/1911.08907 (2019) - 2018
- [j79]Laura Grigori, Sébastien Cayrols, James Weldon Demmel:
Low Rank Approximation of a Sparse Matrix Based on LU Factorization with Column and Row Tournament Pivoting. SIAM J. Sci. Comput. 40(2) (2018) - [c98]E. Jason Riedy
, James Demmel:
Augmented Arithmetic Operations Proposed for IEEE-754 2018. ARITH 2018: 45-52 - [c97]Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer:
ImageNet Training in Minutes. ICPP 2018: 1:1-1:10 - [c96]Saeed Soori, Aditya Devarakonda
, Zachary Blanco, James Demmel, Mert Gürbüzbalaban, Maryam Mehri Dehnavi:
Reducing Communication in Proximal Newton Methods for Sparse Least Squares Problems. ICPP 2018: 22:1-22:10 - [c95]Yang You, James Demmel, Cho-Jui Hsieh, Richard W. Vuduc
:
Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems. ICS 2018: 307-317 - [c94]Aditya Devarakonda
, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization. IPDPS 2018: 409-418 - [c93]Grey Ballard
, James Demmel, Laura Grigori, Mathias Jacquelin, Nicholas Knight:
A 3D Parallel Algorithm for QR Decomposition. SPAA 2018: 55-65 - [i29]James Demmel, Grace Dinh:
Communication-Optimal Convolutional Neural Nets. CoRR abs/1802.06905 (2018) - [i28]Yang You, James Demmel, Cho-Jui Hsieh, Richard W. Vuduc:
Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems. CoRR abs/1805.00569 (2018) - [i27]Grey Ballard, James Demmel, Laura Grigori, Mathias Jacquelin, Nicholas Knight:
A 3D Parallel Algorithm for QR Decomposition. CoRR abs/1805.05278 (2018) - 2017
- [j78]Yang You, James Demmel, Kent Czechowski, Le Song, Rich Vuduc:
Design and Implementation of a Communication-Optimal Classifier for Distributed Kernel Support Vector Machines. IEEE Trans. Parallel Distributed Syst. 28(4): 974-988 (2017) - [c92]Yang You, James Demmel:
Runtime Data Layout Scheduling for Machine Learning Dataset. ICPP 2017: 452-461 - [c91]Yang You, Aydin Buluç
, James Demmel:
Scaling deep learning on GPU and knights landing clusters. SC 2017: 9 - [c90]Edgar Solomonik, Grey Ballard
, James Demmel, Torsten Hoefler:
A Communication-Avoiding Parallel Algorithm for the Symmetric Eigenvalue Problem. SPAA 2017: 111-121 - [i26]Edgar Solomonik, James Demmel, Torsten Hoefler:
Communication Lower Bounds of Bilinear Algorithms for Symmetric Tensor Contractions. CoRR abs/1707.04618 (2017) - [i25]Yang You, Aydin Buluç, James Demmel:
Scaling Deep Learning on GPU and Knights Landing clusters. CoRR abs/1708.02983 (2017) - [i24]Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel:
100-epoch ImageNet Training with AlexNet in 24 Minutes. CoRR abs/1709.05011 (2017) - [i23]Saeed Soori, Aditya Devarakonda, James Demmel, Mert Gürbüzbalaban, Maryam Mehri Dehnavi:
Avoiding Communication in Proximal Methods for Convex Optimization Problems. CoRR abs/1710.08883 (2017) - [i22]Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization. CoRR abs/1712.06047 (2017) - 2016
- [j77]Steven I. Gordon
, James Demmel, Lizanne DeStefano, Lorna Rivera:
Implementing a Collaborative Online Course to Extend Access to HPC Skills. Comput. Sci. Eng. 18(1): 73-79 (2016) - [j76]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. SIAM J. Sci. Comput. 38(6) (2016) - [c89]Alex Gittens, Aditya Devarakonda
, Evan Racah, Michael F. Ringenburg
, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat:
Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. IEEE BigData 2016: 204-213 - [c88]Cindy Rubio-González, Cuong Nguyen, Benjamin Mehne, Koushik Sen, James Demmel, William Kahan, Costin Iancu, Wim Lavrijsen, David H. Bailey, David Hough:
Floating-point precision tuning using blame analysis. ICSE 2016: 1074-1085 - [c87]Erin C. Carson
, James Demmel, Laura Grigori, Nicholas Knight, Penporn Koanantakool, Oded Schwartz, Harsha Vardhan Simhadri:
Write-Avoiding Algorithms. IPDPS 2016: 648-658 - [c86]Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh:
Asynchronous Parallel Greedy Coordinate Descent. NIPS 2016: 4682-4690 - [c85]Grey Ballard, James Demmel, Andrew Gearhart, Benjamin Lipshitz
, Yishai Oltchik, Oded Schwartz, Sivan Toledo:
Network Topologies and Inevitable Contention. COMHPC@SC 2016: 39-52 - [i21]Edgar Solomonik, Grey Ballard, James Demmel, Torsten Hoefler:
A communication-avoiding parallel algorithm for the symmetric eigenvalue problem. CoRR abs/1604.03703 (2016) - [i20]Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat:
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. CoRR abs/1607.01335 (2016) - [i19]James Demmel, Alex Rusciano:
Parallelepipeds obtaining HBL lower bounds. CoRR abs/1611.05944 (2016) - [i18]Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding communication in primal and dual block coordinate descent methods. CoRR abs/1612.04003 (2016) - 2015
- [j75]Grey Ballard
, James Demmel, Laura Grigori, Mathias Jacquelin
, Nicholas Knight, Hong Diep Nguyen:
Reconstructing Householder vectors from Tall-Skinny QR. J. Parallel Distributed Comput. 85: 3-31 (2015) - [j74]James Demmel, Laura Grigori, Ming Gu, Hua Xiang:
Communication Avoiding Rank Revealing QR Factorization with Column Pivoting. SIAM J. Matrix Anal. Appl. 36(1): 55-89 (2015) - [j73]Erin C. Carson
, James Weldon Demmel:
Accuracy of the s-Step Lanczos Method for the Symmetric Eigenproblem in Finite Precision. SIAM J. Matrix Anal. Appl. 36(2): 793-819 (2015) - [j72]James Demmel, Hong Diep Nguyen:
Parallel Reproducible Summation. IEEE Trans. Computers 64(7): 2060-2070 (2015) - [j71]Grey Ballard
, James Demmel, Nicholas Knight:
Avoiding Communication in Successive Band Reduction. ACM Trans. Parallel Comput. 1(2): 11:1-11:37 (2015) - [c84]Hong Diep Nguyen, James Demmel:
Reproducible Tall-Skinny QR. ARITH 2015: 152-159 - [c83]Yang You, James Demmel, Kenneth Czechowski, Le Song, Richard W. Vuduc
:
CA-SVM: Communication-Avoiding Support Vector Machines on Distributed Systems. IPDPS 2015: 847-859 - [c82]Steven I. Gordon
, James Demmel, Lizanne DeStefano, Lorna Rivera:
Extending access to HPC skills through a blended online course. XSEDE 2015: 15:1-15:5 - [i17]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) - 2014
- [j70]Grey Ballard
, Erin C. Carson
, James Demmel, Mark Hoemmen, Nicholas Knight, Oded Schwartz:
Communication lower bounds and optimal algorithms for numerical linear algebra. Acta Numer. 23: 1-155 (2014) - [j69]Grey Ballard
, James Demmel, Olga Holtz
, Oded Schwartz:
Communication costs of Strassen's matrix multiplication. Commun. ACM 57(2): 107-114 (2014) - [j68]Edgar Solomonik, Devin Matthews
, Jeff R. Hammond
, John F. Stanton, James Demmel:
A massively parallel tensor contraction framework for coupled-cluster computations. J. Parallel Distributed Comput. 74(12): 3176-3190 (2014) - [j67]Erin C. Carson
, James Demmel:
A Residual Replacement Strategy for Improving the Maximum Attainable Accuracy of s-Step Krylov Subspace Methods. SIAM J. Matrix Anal. Appl. 35(1): 22-43 (2014) - [j66]Grey Ballard
, Dulceneia Becker, James Demmel, Jack J. Dongarra, Alex Druinsky, Inon Peled, Oded Schwartz, Sivan Toledo, Ichitaro Yamazaki:
Communication-Avoiding Symmetric-Indefinite Factorization. SIAM J. Matrix Anal. Appl. 35(4): 1364-1406 (2014) - [c81]Jeff A. Bilmes, Krste Asanovic, Chee-Whye Chin, Jim Demmel:
Author retrospective for optimizing matrix multiply using PHiPAC: a portable high-performance ANSI C coding methodology. ICS 25th Anniversary 2014: 42-44 - [c80]Samuel Williams
, Mike Lijewski, Ann S. Almgren
, Brian van Straalen, Erin C. Carson
, Nicholas Knight, James Demmel:
s-Step Krylov Subspace Methods as Bottom Solvers for Geometric Multigrid. IPDPS 2014: 1149-1158 - [c79]Grey Ballard
, James Demmel, Laura Grigori, Mathias Jacquelin
, Hong Diep Nguyen, Edgar Solomonik:
Reconstructing Householder Vectors from Tall-Skinny QR. IPDPS 2014: 1159-1170 - [c78]Edgar Solomonik, Erin C. Carson
, Nicholas Knight, James Demmel:
Tradeoffs between synchronization, communication, and computation in parallel linear algebra computations. SPAA 2014: 307-318 - [c77]Razvan Carbunescu, Aditya Devarakonda
, James Demmel, Steven I. Gordon
, Jay Alameda
, Susan Mehringer
:
Architecting an autograder for parallel code. XSEDE 2014: 68:1-68:8 - 2013
- [j65]Amal Khabou, James Demmel, Laura Grigori, Ming Gu:
LU Factorization with Panel Rank Revealing Pivoting and Its Communication Avoiding Version. SIAM J. Matrix Anal. Appl. 34(3): 1401-1429 (2013) - [j64]