| CGO '22
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Comprehensive Accelerator-Dataflow Co-Design Optimization for Convolutional Neural Networks
Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan
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| PLDI '21
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IOOpt: Automatic Derivation of I/O Complexity Bounds for Affine Programs
Auguste Olivry, Guillaume Iooss, Nicolas Tollenaere, Atanas Rountev, P. Sadayappan, and Fabrice Rastello
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| ASPLOS '21
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Analytical Characterization and Design Space Exploration for Optimization of CNNs
Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan
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| SPAA '21
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Brief Announcement: Efficient Distributed Algorithms for Convolutional Neural Networks
Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan
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| SC '20
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Efficient Tiled Sparse Matrix Multiplication Through Matrix Signatures
Sureyya Emre Kurt, Aravind Sukumaran-Rajam, Fabrice Rastello, and P. Sadayappan
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| SC '20
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Scalable Heterogeneous Execution of a Coupled-Cluster Model with Perturbative Triples
Jinsung Kim, Ajay Panyala, Bo Peng, Karol Kowalski, P. Sadayappan, and Sriram Krishnamoorthy
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| SC '20
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Compiling Generalized Histograms for GPU
Troels Henriksen, Sune Hellfritzsch, P. Sadayappan, and Cosmin Oancea
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| PLDI '20
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Automated Derivation of Parametric Data Movement Lower Bounds for Affine Programs
Auguste Olivry, Julien Langou, Louis-Noel Pouchet, P. Sadayappan, and Fabrice Rastello
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| KDD '20
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ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization
Gordon E. Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, and P. Sadayappan
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| SC '19
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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
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| SC '19
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An Efficient Mixed-mode Representation of Sparse Tensors
Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Prashant Singh Rawat, Sriram Krishnamoorthy, and P. Sadayappan
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| CGO '19
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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
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| PPOPP '19
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Adaptive Sparse Tiling for Sparse Matrix Multiplication
Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, and P. Sadayappan
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| PLDI '18
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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
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| HPDC '18
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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
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| ICS '18
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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
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| PPOPP '18
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Register optimizations for stencils on GPUs
Prashant Rawat, Fabrice Rastello, Louis-Noel Pouchet, Atanas Rountev, and P. Sadayappan
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| POPL '18
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Analytical Modeling of Cache Behavior for Affine Programs
Wenlei Bao, Sriram Krishnamoorthy, Louis-Noel Pouchet, Fabrice Rastello, and P. Sadayappan
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| PACT '17
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MultiGraph: Efficient Graph Processing on GPUs
Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, and P. Sadayappan
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| ICS '17
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On Improving Performance of Sparse Matrix-Matrix Multiplication on GPUs
Rakshith Kunchum, Ankur Chaudhry, Aravind Sukumaran-Rajam, Qingpeng Niu, Israt Nisa, and P. Sadayappan
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| PPOPP '17
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Optimizing the Four-Index Integral Transform Using Data Movement Lower Bounds Analysis
Samyam Rajbhandari, Fabrice Rastello, Karol Kowalski, Sriram Krishnamoorthy, and P. Sadayappan
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| PACT '16
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Resource Conscious Reuse-Driven Tiling for GPUs
Prashant Rawat, Changwan Hong, Mahesh Ravishankar, Vinod Grover, Louis-Noel Pouchet, Atanas Rountev, and P. Sadayappan
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| SC '16
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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
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| PLDI '16
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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
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| POPL '16
| PolyCheck: Dynamic Verification of Iteration Space Transformations on Affine Programs
Wenlei Bao, Sriram Krishnamoorthy, Louis-Noel Pouchet, Fabrice Rastello, and P. Sadayappan
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| POPL '15
| On Characterizing the Data Access Complexity of Programs
Venmugil Elango, Fabrice Rastello, Louis-Noel Pouchet, J. Ramanujam, and P. Sadayappan
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| 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
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| 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
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| SC '14
| A Communication-Optimal Framework for Contracting Distributed Tensors
Samyam Rajbhandari, Akshay Nikam, Pai-Wei Lai, Kevin Stock, Sriram Krishnamoorthy, and P. Sadayappan
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| 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
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| PLDI '14
| Compiler-Assisted Detection of Transient Memory Errors
Sanket Tavarageri, Sriram Krishnamoorthy, and P. Sadayappan
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| 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
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| 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
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| PLDI '13
| When Polyhedral Transformations Meet SIMD Code Generation
Martin Kong, Richard Veras, Kevin Stock, Franz Franchetti, Louis-Noel Pouchet, and P. Sadayappan
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| 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
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| POPL '11
| Loop Transformations: Convexity, Pruning and Optimization
Louis-Noel Pouchet, Uday Bondhugula, Cedric Bastoul, Albert Cohen, J. Ramanujam, P. Sadayappan, and Nicolas Vasilache
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| CC '10
| Automatic C-to-CUDA Code Generation for Affine Programs
Muthu Baskaran, J. Ramanujam, and P. Sadayappan
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| SC '09
| Scalable Work Stealing
James Dinan, Brian Larkins, Sriram Krishnamoorthy, Jarek Nieplocha, and P. Sadayappan
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| 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
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| 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
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| PLDI '07
| Effective Automatic Parallelization of Stencil Computations
Sriram Krishnamoorthy, Muthu Baskaran, Uday Bondhugula, J. Ramanujam, Atanas Rountev, and P. Sadayappan
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| 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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