Aravind Sukumaran-Rajam

According to our database, Aravind Sukumaran-Rajam authored at least 47 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Accelerating Graph Computations on 3D NoC-Enabled PIM Architectures.

Dwaipayan Choudhury, Lizhi Xiang, Aravind Sukumaran-Rajam, Anantharaman Kalyanaraman, Partha Pratim Pande

ACM Trans. Design Autom. Electr. Syst., 2023

cuAlign: Scalable Network Alignment on GPU Accelerators.

Lizhi Xiang, Arif M. Khan, S. M. Ferdous, Aravind Sukumaran-Rajam, Mahantesh Halappanavar

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition.

Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam, P. Sadayappan, Bo Yuan, Dingwen Tao

Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2023

A Performance Portability Study Using Tensor Contraction Benchmarks.

M. Emin Ozturk, Omid Asudeh, Gerald Sabin, P. Sadayappan, Aravind Sukumaran-Rajam

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Communication Optimization for Distributed Execution of Graph Neural Networks.

Süreyya Emre Kurt, Jinghua Yan, Aravind Sukumaran-Rajam, Prashant Pandey, P. Sadayappan

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

2022

Software/Hardware Co-design of 3D NoC-based GPU Architectures for Accelerated Graph Computations.

Dwaipayan Choudhury, Reet Barik, Aravind Sukumaran-Rajam, Ananth Kalyanaraman, Partha Pratim Pande

ACM Trans. Design Autom. Electr. Syst., 2022

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

Dwaipayan Choudhury, Aravind Sukumaran-Rajam, Ananth Kalyanaraman, Partha Pratim Pande

ACM J. Emerg. Technol. Comput. Syst., 2022

Sparsity-Aware Tensor Decomposition.

Süreyya Emre Kurt, Saurabh Raje, Aravind Sukumaran-Rajam, P. Sadayappan

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

Comprehensive Accelerator-Dataflow Co-design Optimization for Convolutional Neural Networks.

Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2022

Training of deep learning pipelines on memory-constrained GPUs via segmented fused-tiled execution.

Yufan Xu, Saurabh Raje, Atanas Rountev, Gerald Sabin, Aravind Sukumaran-Rajam, P. Sadayappan

Proceedings of the CC '22: 31st ACM SIGPLAN International Conference on Compiler Construction, Seoul, South Korea, April 2, 2022

Effective Performance Modeling and Domain-Specific Compiler Optimization of CNNs for GPUs.

Yufan Xu, Qiwei Yuan, Erik Curtis Barton, Rui Li, P. Sadayappan, Aravind Sukumaran-Rajam

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

High-Performance Architecture Aware Sparse Convolutional Neural Networks for GPUs.

Lizhi Xiang, P. Sadayappan, Aravind Sukumaran-Rajam

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

2021

Efficient Distributed Algorithms for Convolutional Neural Networks.

Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan

Proceedings of the SPAA '21: 33rd ACM Symposium on Parallelism in Algorithms and Architectures, 2021

cuTS: scaling subgraph isomorphism on distributed multi-GPU systems using trie based data structure.

Lizhi Xiang, Arif Khan, Edoardo Serra, Mahantesh Halappanavar, Aravind Sukumaran-Rajam

Proceedings of the International Conference for High Performance Computing, 2021

Analytical characterization and design space exploration for optimization of CNNs.

Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan

Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021

2020

Efficient tiled sparse matrix multiplication through matrix signatures.

Süreyya Emre Kurt, Aravind Sukumaran-Rajam, Fabrice Rastello, P. Sadayappan

Proceedings of the International Conference for High Performance Computing, 2020

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

Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

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

Gordon Euhyun Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan

CoRR, 2019

An efficient mixed-mode representation of sparse tensors.

Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Prashant Singh Rawat, Sriram Krishnamoorthy, P. Sadayappan

Proceedings of the International Conference for High Performance Computing, 2019

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

Gordon Euhyun Moon, Denis Newman-Griffis, Jinsung Kim, Aravind Sukumaran-Rajam, Eric Fosler-Lussier, P. Sadayappan

Proceedings of the 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2019

Analytical cache modeling and tilesize optimization for tensor contractions.

Rui Li, Aravind Sukumaran-Rajam, Richard Veras, Tze Meng Low, Fabrice Rastello, Atanas Rountev, P. Sadayappan

Proceedings of the International Conference for High Performance Computing, 2019

Adaptive sparse tiling for sparse matrix multiplication.

Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, P. Sadayappan

Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2019

On Optimizing Complex Stencils on GPUs.

Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan

Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

Load-Balanced Sparse MTTKRP on GPUs.

Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Richard W. Vuduc, P. Sadayappan

Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

A Code Generator for High-Performance Tensor Contractions on GPUs.

Jinsung Kim, Aravind Sukumaran-Rajam, Vineeth Thumma, Sriram Krishnamoorthy, Ajay Panyala, Louis-Noël Pouchet, Atanas Rountev, P. Sadayappan

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2019

2018

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

Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Mahesh Ravishankar, Vinod Grover, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan

Proc. IEEE, 2018

Associative instruction reordering to alleviate register pressure.

Prashant Singh Rawat, Aravind Sukumaran-Rajam, Atanas Rountev, Fabrice Rastello, Louis-Noël Pouchet, P. Sadayappan

Proceedings of the International Conference for High Performance Computing, 2018

Register optimizations for stencils on GPUs.

Prashant Singh Rawat, Fabrice Rastello, Aravind Sukumaran-Rajam, Louis-Noël Pouchet, Atanas Rountev, P. Sadayappan

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

Performance modeling for GPUs using abstract kernel emulation.

Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

GPU code optimization using abstract kernel emulation and sensitivity analysis.

Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan

Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2018

TTLG - An Efficient Tensor Transposition Library for GPUs.

Jyothi Vedurada, Arjun Suresh, Aravind Sukumaran-Rajam, Jinsung Kim, Changwan Hong, Ajay Panyala, Sriram Krishnamoorthy, V. Krishna Nandivada, Rohit Kumar Srivastava, P. Sadayappan

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

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

Israt Nisa, Charles Siegel, Aravind Sukumaran-Rajam, Abhinav Vishnu, P. Sadayappan

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, 2018

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

Jinsung Kim, Aravind Sukumaran-Rajam, Changwan Hong, Ajay Panyala, Rohit Kumar Srivastava, Sriram Krishnamoorthy, P. Sadayappan

Proceedings of the 32nd International Conference on Supercomputing, 2018

Parallel Latent Dirichlet Allocation on GPUs.

Gordon Euhyun Moon, Israt Nisa, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Srinivasan Parthasarathy, P. Sadayappan

Proceedings of the Computational Science - ICCS 2018, 2018

Efficient sparse-matrix multi-vector product on GPUs.

Changwan Hong, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Jinsung Kim, Süreyya Emre Kurt, Israt Nisa, Shivani Sabhlok, Ümit V. Çatalyürek, Srinivasan Parthasarathy, P. Sadayappan

Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing, 2018

Sampled Dense Matrix Multiplication for High-Performance Machine Learning.

Israt Nisa, Aravind Sukumaran-Rajam, Süreyya Emre Kurt, Changwan Hong, P. Sadayappan

Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

2017

Parallel CCD++ on GPU for Matrix Factorization.

Israt Nisa, Aravind Sukumaran-Rajam, Rakshith Kunchum, P. Sadayappan

Proceedings of the General Purpose GPUs, 2017

On improving performance of sparse matrix-matrix multiplication on GPUs.

Rakshith Kunchum, Ankur Chaudhry, Aravind Sukumaran-Rajam, Qingpeng Niu, Israt Nisa, P. Sadayappan

Proceedings of the International Conference on Supercomputing, 2017

Parallel LDA with Over-Decomposition.

Gordon Euhyun Moon, Aravind Sukumaran-Rajam, P. Sadayappan

Proceedings of the 24th IEEE International Conference on High Performance Computing Workshops, 2017

Characterization of Data Movement Requirements for Sparse Matrix Computations on GPUs.

Süreyya Emre Kurt, Vineeth Thumma, Changwan Hong, Aravind Sukumaran-Rajam, P. Sadayappan

Proceedings of the 24th IEEE International Conference on High Performance Computing, 2017

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

Prashant Singh Rawat, Aravind Sukumaran-Rajam, Atanas Rountev, Fabrice Rastello, Louis-Noël Pouchet, P. Sadayappan

Proceedings of the 26th International Conference on Parallel Architectures and Compilation Techniques, 2017

MultiGraph: Efficient Graph Processing on GPUs.

Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, P. Sadayappan

Proceedings of the 26th International Conference on Parallel Architectures and Compilation Techniques, 2017

2016

The Polyhedral Model of Nonlinear Loops.

Aravind Sukumaran-Rajam, Philippe Clauss

ACM Trans. Archit. Code Optim., 2016

2015

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

PhD thesis, 2015

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

Aravind Sukumaran-Rajam, Luis Esteban Campostrini, Juan Manuel Martinez Caamaño, Philippe Clauss

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium Workshop, 2015

2014

Speculative Program Parallelization with Scalable and Decentralized Runtime Verification.

Aravind Sukumaran-Rajam, Juan Manuel Martinez Caamaño, Willy Wolff, Alexandra Jimborean, Philippe Clauss

Proceedings of the Runtime Verification - 5th International Conference, 2014

2013

Online Dynamic Dependence Analysis for Speculative Polyhedral Parallelization.

Alexandra Jimborean, Philippe Clauss, Juan Manuel Martinez Caamaño, Aravind Sukumaran-Rajam

Proceedings of the Euro-Par 2013 Parallel Processing, 2013