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P. (Saday) Sadayappan University of Utah Salt Lake City, UT 84112-9205 Email:saday_at_cs.utah.edu |
Teaching
Current/Recent Projects
Data Locality Optimization for Sparse Matrix/Tensor Computations
NSF, 2020-2023.
A framework for solution of coupled partial differential equations on heterogeneous parallel systems
(PI: Hari Sundar)
NSF, 2020-2023.
Parallel Algorithm by Blocks - A Data-centric Compiler/runtime System for Productive Programming of Scalable Parallel Systems
NSF, 2019-2022.
Tools for Productive High-Performance Computing with GPUs
NSF, 2018-2021.
Performance Portable Framework for Developing Graph Applications
DARPA SBIR-Phase 2 (with RNET Technologies, Dayton, OH), 2017-2021.
Towards Automated Characterization of the Data-Movement Complexity of Large Scale Analytics Applications,
NSF, 2016-2019.
PARAGRAPH: Parallel, Scalable Graph Analytics,
NSF, 2016-2019.
Whole-Program Adaptive Error Detection and Mitigation,
DOE, 2015-2019 (Project PI: Sriram Krishnamoorthy, PNNL).
Improving Vectorization,
NSF, 2014-2018.
Compiler/Runtime Support for Developing Scalable Parallel Multi-Scale Multi-Physics Applications,
NSF, 2014-2018.
Selected Publications [More complete and up-to-date list from
(DBLP)
or
(Google Scholar)
]
ASPLOS '21 |
Analytical Characterization and Design Space Exploration for Optimization of CNNs
(preprint)
Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan |
SC '20 |
Efficient Tiled Sparse Matrix Multiplication Through Matrix Signatures
Sureyya Emre Kurt, Aravind Sukumaran-Rajam, Fabrice Rastello, and P. Sadayappan |
SC '20 |
Scalable Heterogeneous Execution of a Coupled-Cluster Model with Perturbative Triples
Jinsung Kim, Ajay Panyala, Bo Peng, Karol Kowalski, P. Sadayappan, and Sriram Krishnamoorthy |
SC '20 |
Compiling Generalized Histograms for GPU
Troels Henriksen, Sune Hellfritzsch, P. Sadayappan, and Cosmin Oancea |
PLDI '20 |
Automated Derivation of Parametric Data Movement Lower Bounds for Affine Programs
Auguste Olivry, Julien Langou, Louis-Noel Pouchet, P. Sadayappan, and Fabrice Rastello |
KDD '20 |
ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization
Gordon E. Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, and P. Sadayappan |
SC '19 |
Analytical Cache Modeling and Tilesize Optimization for Tensor Contractions
Rui Li, Aravind Sukumaran-Rajam, Richard Veras, Tze Meng Low, Fabrice Rastello, Atanas Rountev, and P. Sadayappan |
SC '19 |
An Efficient Mixed-mode Representation of Sparse Tensors
Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Prashant Singh Rawat, Sriram Krishnamoorthy, and P. Sadayappan |
CGO '19 |
A Code Generator for High-Performance Tensor Contractions on GPUs
Jinsung Kim, Aravind Sukumaran-Rajam, Vineeth Thumma, Sriram Krishnamoorthy, Ajay Panyala, Louis-Noel Pouchet, Atanas Rountev, and P. Sadayappan |
PPOPP '19 |
Adaptive Sparse Tiling for Sparse Matrix Multiplication
Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, and P. Sadayappan |
PLDI '18 |
GPU Code Optimization using Abstract Kernel Emulation and Sensitivity Analysis
Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noel Pouchet, Fabrice Rastello, and P. Sadayappan |
HPDC '18 |
Efficient Sparse-Matrix Multi-Vector Product on GPUs
Changwan Hong, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Jinsung Kim, Sureyya Emre Kurt, Israt Nisa, Shivani Sabhlok, Umit Catalyu¼rek, Srinivasan Parthasarathy, and P. Sadayappan |
ICS '18 |
Optimizing Tensor Contractions in CCSD(T) for Efficient Execution on GPUs
Jinsung Kim, Aravind Sukumaran Rajam, Changwan Hong, Ajay Panyala, Rohit Srivastava, Sriram Krishnamoorthy, and P. Sadayappan |
PPOPP '18 |
Register optimizations for stencils on GPUs
Prashant Rawat, Fabrice Rastello, Louis-Noel Pouchet, Atanas Rountev, and P. Sadayappan |
POPL '18 |
Analytical Modeling of Cache Behavior for Affine Programs
Wenlei Bao, Sriram Krishnamoorthy, Louis-Noel Pouchet, Fabrice Rastello, and P. Sadayappan |
PACT '17 |
MultiGraph: Efficient Graph Processing on GPUs
Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, and P. Sadayappan |
ICS '17 |
On Improving Performance of Sparse Matrix-Matrix Multiplication on GPUs
Rakshith Kunchum, Ankur Chaudhry, Aravind Sukumaran-Rajam, Qingpeng Niu, Israt Nisa, and P. Sadayappan |
PPOPP '17 |
Optimizing the Four-Index Integral Transform Using Data Movement Lower Bounds Analysis
Samyam Rajbhandari, Fabrice Rastello, Karol Kowalski, Sriram Krishnamoorthy, and P. Sadayappan |
PACT '16 |
Resource Conscious Reuse-Driven Tiling for GPUs
Prashant Rawat, Changwan Hong, Mahesh Ravishankar, Vinod Grover, Louis-Noel Pouchet, Atanas Rountev, and P. Sadayappan |
SC '16 |
A Domain-Specific Compiler for a Parallel Multiresolution Adaptive Numerical Simulation Environment
Samyam Rajbhandari, Jinsung Kim, Sriram Krishnamoorthy, Louis-Noel Pouchet, Fabrice Rastello, Robert J. Harrison, and P. Sadayappan |
PLDI '16 |
Effective Padding of Multidimensional Arrays to Avoid Cache Conflict Misses
C. Hong, W. Bao, A. Cohen, S. Krishnamoorthy, L.-N. Pouchet, F. Rastello, J. Ramanujam, and P. Sadayappan |
POPL '16 | PolyCheck: Dynamic Verification of Iteration Space Transformations on Affine Programs
Wenlei Bao, Sriram Krishnamoorthy, Louis-Noel Pouchet, Fabrice Rastello, and P. Sadayappan |
POPL '15 | On Characterizing the Data Access Complexity of Programs
Venmugil Elango, Fabrice Rastello, Louis-Noel Pouchet, J. Ramanujam, and P. Sadayappan |
PPOPP '15 | Distributed Memory Code Generation for Mixed Irregular/Regular Computations
Mahesh Ravishankar, Roshan Dathathri, Venmugil Elango, Louis-Noel Pouchet, J. Ramanujam, Atanas Rountev, and P. Sadayappan |
PPOPP '15 | On Optimizing Machine Learning Workloads via Kernel Fusion
Arash Ashari, Shirish Tatikonda, Matthias Boehm, Berthold Reinwald, Keith Campbell, John Keenleyside, and P. Sadayappan |
SC '14 | A Communication-Optimal Framework for Contracting Distributed Tensors
Samyam Rajbhandari, Akshay Nikam, Pai-Wei Lai, Kevin Stock, Sriram Krishnamoorthy, and P. Sadayappan |
PLDI '14 | A Framework for Enhancing Data Reuse via Associative Reordering
Kevin Stock, Martin Kong, Tobias Grosser, Louis-Noel Pouchet, Fabrice Rastello, J. Ramanujam, and P. Sadayappan |
PLDI '14 | Compiler-Assisted Detection of Transient Memory Errors
Sanket Tavarageri, Sriram Krishnamoorthy, and P. Sadayappan |
SPAA '14 | On Characterizing the Data Movement Complexity of Computational DAGs for Parallel Execution
Venmugil Elango, Fabrice Rastello, Louis-Noel Pouchet, J. Ramanujam, and P. Sadayappan |
SC '13 | A Framework for Load Balancing of Tensor Contraction Expressions via Dynamic Task Partitioning
Pai-Wei Lai, Kevin Stock, Samyam Rajbhandari, Sriram Krishnamoorthy, and P. Sadayappan |
PLDI '13 | When Polyhedral Transformations Meet SIMD Code Generation
Martin Kong, Richard Veras, Kevin Stock, Franz Franchetti, Louis-Noel Pouchet, and P. Sadayappan |
PLDI '12 | Dynamic Trace-Based Analysis of Vectorization Potential of Applications
Justin Holewinski, Ragavendar Ramamurthi, Mahesh Ravishankar, Naznin Fauzia, Louis-Noel Pouchet, Atanas Rountev, and P. Sadayappan |
POPL '11 | Loop Transformations: Convexity, Pruning and Optimization
Louis-Noel Pouchet, Uday Bondhugula, Cedric Bastoul, Albert Cohen, J. Ramanujam, P. Sadayappan, and Nicolas Vasilache |
CC '10 | Automatic C-to-CUDA Code Generation for Affine Programs
Muthu Baskaran, J. Ramanujam, and P. Sadayappan |
SC '09 | Scalable Work Stealing
James Dinan, Brian Larkins, Sriram Krishnamoorthy, Jarek Nieplocha, and P. Sadayappan |
ICS '08 | A Compiler Framework for Optimization of Affine Loop Nests for GPGPUs
Muthu Baskaran, Uday Bondhugula, Sriram Krishnamoorthy, J. Ramanujam, Atanas Rountev, and P. Sadayappan |
PLDI '08 | A Practical Automatic Polyhedral Parallelizer and Locality Optimizer
(recipient of ACM SIGPLAN Most Influential PLDI Paper Award in 2018)
Uday Bondhugula, Albert Hartono, J. Ramanujam, and P. Sadayappan |
PLDI '07 | Effective Automatic Parallelization of Stencil Computations
Sriram Krishnamoorthy, Muthu Baskaran, Uday Bondhugula, J. Ramanujam, Atanas Rountev, and P. Sadayappan |
Proceedings IEEE '05 | Synthesis of High-Performance Parallel Programs for a Class of Ab Initio Quantum Chemistry Models
Gerald Baumgartner, Alexander Auer, David E Bernholdt, Alina Bibireata, Venkatesh Choppella, Daniel Cociorva, Xiaoyang Gao, Robert J Harrison, So Hirata, Sriram Krishnamoorthy, Sandhya Krishnan, Chi-Chung Lam, Qingda Lu, Marcel Nooijen, Russell M Pitzer, J Ramanujam, Alex Sibiryakov, and P. Sadayappan |
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