Aravind Sukumaran-Rajam

发表

Analytical cache modeling and tilesize optimization for tensor contractions

Richard Veras, Tze Meng Low, P. Sadayappan, 2019, SC.

Richard W. Vuduc, P. Sadayappan, Aravind Sukumaran-Rajam, 2019, 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Parallel LDA with Over-Decomposition

P. Sadayappan, Aravind Sukumaran-Rajam, Gordon E. Moon, 2017, 2017 IEEE 24th International Conference on High Performance Computing Workshops (HiPCW).

On Optimizing Complex Stencils on GPUs

P. Sadayappan, Aravind Sukumaran-Rajam, Atanas Rountev, 2019, 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

The Polyhedral Model of Nonlinear Loops

Philippe Clauss, Aravind Sukumaran-Rajam, 2016, ACM Trans. Archit. Code Optim..

Efficient sparse-matrix multi-vector product on GPUs

Srinivasan Parthasarathy, P. Sadayappan, Aravind Sukumaran-Rajam, 2018, HPDC.

APOLLO: Automatic speculative POLyhedral Loop Optimizer

Manuel Selva, Philippe Clauss, Aravind Sukumaran-Rajam, 2017 .

ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization

P. Sadayappan, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, 2020, KDD.

Performance modeling for GPUs using abstract kernel emulation

Sriram Krishnamoorthy, P. Sadayappan, Aravind Sukumaran-Rajam, 2018, PPOPP.

Adaptive sparse tiling for sparse matrix multiplication

P. Sadayappan, Aravind Sukumaran-Rajam, Israt Nisa, 2019, PPoPP.

On improving performance of sparse matrix-matrix multiplication on GPUs

P. Sadayappan, Aravind Sukumaran-Rajam, Israt Nisa, 2017, ICS.

A Code Generator for High-Performance Tensor Contractions on GPUs

Sriram Krishnamoorthy, P. Sadayappan, Aravind Sukumaran-Rajam, 2019, 2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO).

Speculative Program Parallelization with Scalable and Decentralized Runtime Verification

Philippe Clauss, Aravind Sukumaran-Rajam, Juan Manuel Martinez Caamaño, 2014, RV.

Analytical characterization and design space exploration for optimization of CNNs

Rui Li, P. Sadayappan, Aravind Sukumaran-Rajam, 2021, ASPLOS.

Parallel CCD++ on GPU for Matrix Factorization

P. Sadayappan, Aravind Sukumaran-Rajam, Israt Nisa, 2017, GPGPU@PPoPP.

POSTER: Statement Reordering to Alleviate Register Pressure for Stencils on GPUs

P. Sadayappan, Aravind Sukumaran-Rajam, Fabrice Rastello, 2017, 2017 26th International Conference on Parallel Architectures and Compilation Techniques (PACT).

PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization pdf

Srinivasan Parthasarathy, P. Sadayappan, Aravind Sukumaran-Rajam, 2019, ArXiv.

An efficient mixed-mode representation of sparse tensors

Sriram Krishnamoorthy, P. Sadayappan, Aravind Sukumaran-Rajam, 2019, SC.

Domain-Specific Optimization and Generation of High-Performance GPU Code for Stencil Computations

P. Sadayappan, Aravind Sukumaran-Rajam, Atanas Rountev, 2018, Proceedings of the IEEE.

Parallel Latent Dirichlet Allocation on GPUs

Srinivasan Parthasarathy, P. Sadayappan, Aravind Sukumaran-Rajam, 2018, ICCS.

Characterization of Data Movement Requirements for Sparse Matrix Computations on GPUs

P. Sadayappan, Aravind Sukumaran-Rajam, Changwan Hong, 2017, 2017 IEEE 24th International Conference on High Performance Computing (HiPC).

Research Program - Profiling and Execution Behavior Modeling

Philippe Clauss, Aravind Sukumaran-Rajam, Alain Ketterlin, 2015 .

P. Sadayappan, Aravind Sukumaran-Rajam, Fabrice Rastello, 2018, PPoPP.

Effective Machine Learning Based Format Selection and Performance Modeling for SpMV on GPUs

P. Sadayappan, Aravind Sukumaran-Rajam, Abhinav Vishnu, 2018, 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings

P. Sadayappan, Aravind Sukumaran-Rajam, Jinsung Kim, 2019, 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC).

Sampled Dense Matrix Multiplication for High-Performance Machine Learning

P. Sadayappan, Aravind Sukumaran-Rajam, Israt Nisa, 2018, 2018 IEEE 25th International Conference on High Performance Computing (HiPC).

Optimizing Tensor Contractions in CCSD(T) for Efficient Execution on GPUs

Sriram Krishnamoorthy, P. Sadayappan, Aravind Sukumaran-Rajam, 2018, ICS.

Beyond the Realm of the Polyhedral Model: Combining Speculative Program Parallelization with Polyhedral Compilation. (Au delà des limites du modèle polyédrique: en combinant la parallélisation spéculative de programmes et la compilation polyédrique)

Aravind Sukumaran-Rajam, 2015 .

GPU code optimization using abstract kernel emulation and sensitivity analysis

Sriram Krishnamoorthy, P. Sadayappan, Aravind Sukumaran-Rajam, 2018, PLDI.

New Results - Automatic Parallelization of Nonlinear Loops

Philippe Clauss, Aravind Sukumaran-Rajam, P. Clauss, 2015 .

MultiGraph: Efficient Graph Processing on GPUs

P. Sadayappan, Aravind Sukumaran-Rajam, Jinsung Kim, 2017, 2017 26th International Conference on Parallel Architectures and Compilation Techniques (PACT).

Online Dynamic Dependence Analysis for Speculative Polyhedral Parallelization

Philippe Clauss, Aravind Sukumaran-Rajam, Juan Manuel Martinez Caamaño, 2013, Euro-Par.

Speculative Runtime Parallelization of Loop Nests: Towards Greater Scope and Efficiency

Philippe Clauss, Aravind Sukumaran-Rajam, Juan Manuel Martinez Caamaño, 2015, 2015 IEEE International Parallel and Distributed Processing Symposium Workshop.

Associative Instruction Reordering to Alleviate Register Pressure

P. Sadayappan, Aravind Sukumaran-Rajam, Fabrice Rastello, 2018, SC18: International Conference for High Performance Computing, Networking, Storage and Analysis.

TTLG - An Efficient Tensor Transposition Library for GPUs

Sriram Krishnamoorthy, P. Sadayappan, Aravind Sukumaran-Rajam, 2018, 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

High-Performance and Energy-Efficient 3D Manycore GPU Architecture for Accelerating Graph Analytics

Partha Pratim Pande, Anantharaman Kalyanaraman, Aravind Sukumaran-Rajam, 2021, ACM Journal on Emerging Technologies in Computing Systems.

Efficient Distributed Algorithms for Convolutional Neural Networks

Aravind Sukumaran-Rajam, Atanas Rountev, P Sadayappan, 2021, SPAA.

Analytical characterization and design space exploration for optimization of CNNs

Rui Li, P. Sadayappan, Aravind Sukumaran-Rajam, 2021, ASPLOS.

cuTS: Scaling Subgraph Isomorphism on Distributed Multi-GPU Systems Using Trie Based Data Structure

Aravind Sukumaran-Rajam, Edoardo Serra, Mahantesh Halappanavar, 2021, SC21: International Conference for High Performance Computing, Networking, Storage and Analysis.