Edgar Solomonik

For More Information

• Website
• Website mirror

Education

• Ph.D., Computer Science, University of California Berkeley, 2014
• B.S., Computer Science, University of Illinois Urbana-Champaign, 2010

Academic Positions

• Assistant Professor, Department of Computer Science, University of Illinois Urbana-Champaign, 2016-2022
• Postdoctoral Fellow, Department of Computer Science, ETH Zurich, 2014-2016

Research Interests

• tensor computations
• numerical optimization
• numerical linear algebra
• parallel and high performance computing
• communication-avoiding algorithms
• communication lower bounds
• electronic structure calculations
• graph algorithms
• quantum computing

Chapters in Books

• Laxmikant Kale and Edgar Solomonik; Parallel sorting; Encyclopedia of Parallel Computing, Springer Verlag, David Padua, Ed., 2011.

Selected Articles in Journals

• Linjian Ma, Matthew Fishman, Edwin Miles Stoudenmire, and Edgar Solomonik. Tensor rank and other multipartite entanglement measures of graph states Quantum 8, 2024.
• Louis Schatzki, Linjian Ma, Edgar Solomonik, Eric Chitambar Tensor rank and other multipartite entanglement measures of graph states Physical Review A 110.3, 2024.
• Yang Gao, Phillip Helms, Garnet Kin-Lic Chan, and Edgar Solomonik. Automatic transformation of irreducible representations for efficient contraction of tensors with cyclic group symmetry. SciPost Physics Codebases, September 2023.
• Caleb Ju, Yifan Zhang, and Edgar Solomonik Communication lower bounds for nested bilinear algorithms Foundations of Computational Mathematics (FoCM), 2023.
• Navjot Singh and Edgar Solomonik. Alternating Mahalanobis distance minimization for stable and accurate CP decomposition SIAM Journal of Scientific Computing (SISC), 2023.
• Yang Gao, Phillip Helms, Garnet Kin-Lic Chan, and Edgar Solomonik. Automatic transformation of irreducible representations for efficient contraction of tensors with cyclic group symmetry SciPost Physics Codebases, September 2022.
• Samah Karim and Edgar Solomonik. Efficient preconditioners for interior point methods via a new Schur-complement-based strategy. SIAM Journal on Matrix Analysis and Applications (SIMAX), 2022.
• Linjian Ma and Edgar Solomonik; Accelerating alternating least squares for tensor decomposition by pairwise perturbation; Numerical Linear Algebra with Applications (NLAA), 27 pages, 2022.
• Navjot Singh, Zecheng Zhang, Xiaoxiao Wu, Naijing Zhang, Siyuan Zhang, and Edgar Solomonik; Distributed-memory tensor completion for generalized loss functions in Python using new sparse tensor kernels; Journal of Parallel and Distributed Computing (JPDC), 29 pages, 2022.
• Edgar Solomonik, James Demmel, and Torsten Hoefler; Communication lower bounds of bilinear algorithms for symmetric tensor contractions; SIAM Journal of Scientific Computing (SISC), 28 pages, 2021.
• Navjot Singh, Linjian Ma, Hongru Yang, and Edgar Solomonik. Comparison of accuracy and scalability of Gauss-Newton and alternating least squares for CP decomposition. SIAM Journal of Scientific Computing (SISC), 20 pages, 2021.
• Caleb Ju and Edgar Solomonik; Derivation and analysis of fast bilinear algorithms for convolution; SIAM Review, 34 pages, 2020.
• Edgar Solomonik and James Demmel; Fast bilinear algorithms for symmetric tensor contractions; Computational Methods in Applied Mathematics (CMAM), pages 211-231, February 2020.
• Edgar Solomonik, Erin Carson, Nicholas Knight, and James Demmel; Trade-offs between synchronization, communication, and computation in parallel linear algebra computations; ACM Transactions on Parallel Computing (TOPC), pages 1-47, June 2016.
• Edgar Solomonik, Devin Matthews, Jeff R. Hammond, John F. Stanton, and James Demmel; A massively parallel tensor contraction framework for coupled-cluster computations; Journal of Parallel and Distributed Computing (JPDC), pages 3176-3190, June 2014.
• Abhinav Bhatele, Lukasz Wesolowski, Eric Bohm, Edgar Solomonik, and Laxmikant V. Kale; Understanding application performance via micro-benchmarks on three large supercomputers: Intrepid, Ranger and Jaguar; International Journal of High Performance Computing Applications (IJHPCA), pages: 411-427, November 2010.

Articles in Conference Proceedings

• Raghavendra Kanakagiri and Edgar Solomonik. Minimum cost loop nests for contraction of a sparse tensor with a tensor network. ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), June 2024.
• Andreas Irmler, Raghavendra Kanakagiri, Sebastian T. Ohlmann, Edgar Solomonik, and Andreas Grueneis Optimizing distributed tensor contractions using node-aware processor grids Lecture Notes in Computer Science, Euro-Par, August 2023.
• Edward Hutter and Edgar Solomonik. High-dimensional performance modeling via tensor completion ACM/IEEE Supercomputing Conference (SC), November 2023.
• Wentao Yang, Vipul Harsh, and Edgar Solomonik. Optimal round and sample-size complexity for partitioning in parallel sorting. ACM Symposium on Parallelism in Algorithms and Architectures, June 2023.
• Toluwanimi O. Odemuyiwa, Hadi Asghari-Moghaddam, Michael Pellauer, Kartik Hegde, Po-An Tsai, Neal C. Crago, Aamer Jaleel, Edgar Solomonik, Joel S. Emer, and Christopher W. Fletcher Accelerating sparse data orchestration via dynamic reflexive tiling. ACM International Conference on Architectural Support for Programming Languages and Operating Systems, March 2023.
• Chaoqi Yang, Cheng Qian, Navjot Singh, Cao Xiao, Brandon Westover, Edgar Solomonik, Jimeng Sun; ATD: Augmenting CP Tensor Decomposition by Self Supervision; Conference on Neural Information Processing Systems (NeurIPS), 2022.  
• Linjian Ma and Edgar Solomonik. Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs. Conference on Neural Information Processing Systems (NeurIPS), 2022.
• Tim Baer, Raghavendra Kanakagiri, and Edgar Solomonik; Parallel minimum spanning forest computation using sparse matrix kernels; SIAM Conference of Parallel Processing for Scientific Computing (SIAM PP), 11 pages, February 2022.
• Linjian Ma and Edgar Solomonik; Fast and accurate randomized algorithms for low-rank tensor decompositions; Conference on Neural Information Processing Systems (NeurIPS), 13 pages, November 2021. Acceptance rate: 27%
• Chaoqi Yang, Navjot Singh, Cao Xiao, Cheng Qian, Edgar Solomonik, Jimeng Sun; MTC: Multiresolution tensor completion from partial and coarse observations; ACM SIGKDD Conference, 11 pages, June 2021.
• Edward Hutter and Edgar Solomonik; Confidence-based approximation for performance prediction using execution path analysis; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 12 pages, May 2021.
• Linjian Ma and Edgar Solomonik; Efficient parallel CP decomposition with pairwise perturbation and multi-sweep dimension tree; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 11 pages, May 2021.
• Yuchen Pang, Tianyi Hao, Annika Dugad, Yiqing Zhou, and Edgar Solomonik; Efficient 2D tensor network simulation of quantum systems; ACM/IEEE Supercomputing Conference (SC), 13 pages, November 2020. Acceptance Rate: 25%
• Ryan Levy, Edgar Solomonik, and Bryan Clark; Distributed-memory DMRG via sparse and dense parallel tensor contractions; ACM/IEEE Supercomputing Conference (SC), 13 pages, November 2020. Acceptance Rate: 25%
• Linjian Ma, Jiayu Ye, and Edgar Solomonik; AutoHOOT: Automatic High-Order Optimization for Tensors. International Conference on Parallel Architectures and Compilation Techniques (PACT), 18 pages, October 2020. Acceptance Rate: 23%
• Maciej Besta, Raghavendra Kanakagiri, Harun Mustafa, Mikhail Karasikov, Gunnar Rätsch, Torsten Hoefler, and Edgar Solomonik; Communication-efficient Jaccard similarity for high-performance distributed genome comparisons; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 11 pages, New Orleans, USA; May 2020. Acceptance Rate: 25%
• Kartik Hegde, Hadi Asghari-Moghaddam, Michael Pellauer, Neal Crago, Aamer Jaleel, Edgar Solomonik, Joel Emer, and Christopher W. Fletcher; ExTensor: An accelerator for sparse tensor algebra; IEEE/ACM International Symposium on Microarchitecture (MICRO), Pages 319–333, October 2019. Acceptance Rate: 23%
• Vipul Harsh, Laxmikant Kale, and Edgar Solomonik. Histogram sort with sampling. ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pages 201–212, June 2019. Acceptance rate: 33%
• Edward Hutter and Edgar Solomonik; Communication-avoiding Cholesky-QR2 for rectangular matrices; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 12 pages, Rio de Janeiro, Brazil, May 2019.
• Edgar Solomonik, Maciej Besta, Flavio Vella, and Torsten Hoefler; Scaling betweenness centrality using communication-efficient sparse matrix multiplication; ACM/IEEE Supercomputing Conference, pages 1–14, Denver, Colorado, November 2017. Acceptance Rate: 18%
• Maciej Besta, Michal Podstawski, Linus Groner, Edgar Solomonik, and Torsten Hoefler; To push or to pull: on reducing communication and synchronization in graph computations; 26th ACM Symposium on High Performance Parallel and Distributed Computing (HPDC), ACM, New York, NY, USA, 93-104, June 2017. Acceptance Rate: 19%
• Tobias Wicky, Edgar Solomonik, and Torsten Hoefler; Communication-avoiding parallel algorithms for solving triangular systems of linear equations; IEEE International Parallel and Distributed Processing Symposium (IPDPS), Orlando, FL, June 2017, pp. 678-687. Acceptance Rate: 22%
• Maciej Besta, Florian Marending, Edgar Solomonik and Torsten Hoefler; SlimSell: A vectorizable graph representation for breadth-first search; IEEE International Parallel and Distributed Processing Symposium (IPDPS), pages 32-41, Orlando, FL, June 2017, pp. 32-41. Acceptance Rate: 22%
• Edgar Solomonik, Grey Ballard, James Demmel, and Torsten Hoefler; A communication-avoiding parallel algorithm for the symmetric eigenvalue problem 29th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), ACM, New York, NY, USA, 111-121, July 2017. Acceptance Rate: 25%
• Edgar Solomonik, Erin Carson, Nicholas Knight, and James Demmel; Tradeoffs between synchronization, communication, and work in parallel linear algebra computations; 26th ACM Symposium on Parallelism in Algorithms and Architectures, pages 307–318, Prague, Czech Republic, June 2014. Acceptance Rate: 25%
• Grey Ballard, James Demmel, Laura Grigori, Mathias Jacquelin, Hong Diep Nguyen, and Edgar Solomonik; Reconstructing Householder vectors from Tall-Skinny QR; IEEE International Parallel and Distributed Processing Symposium (IPDPS), pages 1159–1170, Phoenix, AZ, May 2014. Acceptance Rate: 21%
• Edgar Solomonik, Devin Matthews, Jeff Hammond, and James Demmel; Cyclops Tensor Framework: reducing communication and eliminating load imbalance in massively parallel contractions; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 12 pages, Boston, MA, May 2013. Acceptance Rate: 21%
• Edgar Solomonik, Aydin Buluc, and James Demmel; Minimizing communication in all-pairs shortest-paths; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 12 pages, Boston, MA, May 2013. Acceptance Rate: 21%
• Michael Driscoll, Evangelos Georganas, Penporn Koanantakool, Edgar Solomonik, and Katherine Yelick; A communication-optimal n-body algorithm for direct interactions; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 10 pages, Boston, MA, May 2013. Acceptance Rate: 21%
• Evangelos Georganas, Jorge Gonzalez-Dominguez, Edgar Solomonik, Yili Zheng, Juan Tourino and Katherine Yelick; Communication avoiding and overlapping for numerical linear algebra; ACM/IEEE Supercomputing Conference, 11 pages, Salt Lake City, Utah, November 2012. Acceptance Rate: 21%
• Edgar Solomonik, Abhinav Bhatele, and James Demmel; Improving communication performance in dense linear algebra via topology aware collectives; ACM/IEEE Supercomputing Conference 2011, pages 1–11, Seattle, WA, November 2011. Acceptance Rate: 21%
• Edgar Solomonik and James Demmel; Matrix multiplication on multidimensional torus networks, Springer Lecture Notes in Computer Science (LNCS), Proceedings of VECPAR, Kobe, Japan, July 2012.
• Edgar Solomonik and James Demmel; Communication-optimal parallel 2.5D matrix multiplication and LU factorization algorithms; Lecture Notes in Computer Science, Euro-Par, Bordeaux, France, August 2011. Acceptance Rate: 30%
• Edgar Solomonik and Laxmikant V. Kale; Highly scalable parallel sorting; IEEE International Parallel and Distributed Processing Symposium (IPDPS), 12 pages, Atlanta, GA, April 2010. Acceptance Rate: 24%.
• Vivek Kale and Edgar Solomonik; Parallel sorting pattern; Workshop on Parallel Programming Patterns (ParaPLOP), pages 1-12, March 2010.

Reports

• Ping-Hsuan Tsai, Paul Fischer, and Edgar Solomonik Accelerating the Galerkin reduced-order model with the tensor decomposition for turbulent flows arXiv:2311.03694 [physics.flu-dyn], November 2023.
• Yifan Zhang and Edgar Solomonik; On stability of tensor networks and canonical forms; arXiv:2001.01191 [math.NA], 24 pages, January 2020.
• Edwin Pednault, John A. Gunnels, Giacomo Nannicini, Lior Horesh, Thomas Magerlein, Edgar Solomonik, Erik Draeger, Eric Holland, and Robert Wisnieff; Breaking the 49-qubit barrier in the simulation of quantum circuits; arXiv:1710.05867 [quant-ph], 44 pages, October 2017.
• Edgar Solomonik and Torsten Hoefler; Sparse tensor algebra as a parallel programming model arXiv preprint, arXiv:1512.00066 [cs.MS], 20 pages, November 2015.
• Edgar Solomonik, Jeff Hammond, and James Demmel; A preliminary analysis of Cyclops Tensor Framework; 12 pages, EECS Department, University of California, Berkeley, March 2012.

Research Honors

• Presidential Early Career Award for Scientists and Engineers (PECASE), 2025 (2025)
• ISC Jack Dongarra Early Career Award, 2024 (2024)
• List of Instructors Ranked as Excellent, Illinois, Spring 2022 (2022)
• C.W. Gear Outstanding Junior Faculty Award, Computer Science, Illinois, 2021 (2021)
• Dean's Award for Excellence in Research, Grainger College of Engineering, Illinois, 2021 (2021)
• List of Instructors Ranked as Excellent, Illinois, Fall 2020 (2020)
• National Science Foundation CAREER Award, 2020 (2020)
• SIAM Activity Group on Supercomputing Early Career Prize, 2020 (2020)
• IEEE-CS Technical Consortium on High Performance Computing (TCHPC) Early Career Researchers Award for Excellence in High Performance Computing, 2018 (2018)
• Alston S. Householder Prize XX, 2017 (2017)
• ETH Zurich Postdoctoral Fellowship, 2014 (2014)
• Berkeley EECS Department David J. Sakrison Memorial Prize, 2014 (2014)
• NERSC Award for Innovative Use of High Performance Computing, 2013 (2013)
• ACM/IEEE-CS George Michael Memorial High Performance Computing Fellowship, 2013 (2013)
• Distinguished Paper Award, Euro-Par, 2011 (2011)
• Department of Energy Computational Science Graduate Fellowship (DOE CSGF), 2010 (2010)