Aravind Sukumaran-Rajam

56 papers A* 4A 15B 12Misc 2Journal 13Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Comparative Analysis of Loosely and Tightly Coupled Accelerator Architectures for Machine Learning. IEEE Micro Amin Firoozshahian, Joel Coburn, Ajit Punj, Aravind Sukumaran-Rajam, Colby Boyer, Rakesh Nattoji, Mahima Bathla, Bob Dreyer, Sujith Srinivasan, Harshitha Pilla, Michael Rotzin, Surendra Rajupalem, K. Rajesh Jagannath, Krishna Noru, Harikrishna Reddy, Chris Yang, Charlie Hong-Men Su, Charlie Cheng
2025	A*	`conf`	Meta's Second Generation AI Chip: Model-Chip Co-Design and Productionization Experiences. ISCA Joel Coburn, Chunqiang Tang, Sameer Abu Asal, Neeraj Agrawal, Raviteja Chinta, Harish Dattatraya Dixit, Brian Dodds, Saritha Dwarakapuram, Amin Firoozshahian, Cao Gao, Kaustubh Gondkar, Tyler Graf, Junhan Hu, Jian Huang, Sterling Hughes, Adam Hutchin, Bhasker Jakka, Guoqiang Jerry Chen, Indu Kalyanaraman, Ashwin Kamath, Pankaj Kansal, Erum Kazi, Roman Levenstein, Mahesh Maddury, Alex Mastro, Siji Medaiyese, Pritesh Modi, Jack Montgomery, Nadathur Satish, Amit Nagpal, Ashwin Narasimha, Maxim Naumov, Eleanor Ozer, Jongsoo Park, Poorvaja Ramani, Harikrishna Reddy, David Reiss, Deboleena Roy, Sathish Sekar, Arushi Sharma, Pavan Shetty, Aravind Sukumaran-Rajam, Eran Tal, Mike Tsai, Shreya Varshini, Richard Wareing, Olívia Wu, Xiaolong Xie, Jinghan Yang, Hangchen Yu, Tanmay Zargar, Zitong Zeng, Feixiong Zhang, Ajit Mathews, Xun Jiao, Jiyuan Zhang, Emmanuel Menage, Truls Edvard Stokke, Mohammed Sourouri
2025	J	`jnl`	ScaWL: Scaling k-WL (Weisfeiler-Lehman) Algorithms in Memory and Performance on Shared and Distributed-Memory Systems. ACM Trans. Archit. Code Optim. Coby Soss, Aravind Sukumaran-Rajam, Janet Layne, Edoardo Serra, Mahantesh Halappanavar, Assefaw H. Gebremedhin
2025	J	`jnl`	cuTeSpMM: Accelerating Sparse-Dense Matrix Multiplication using GPU Tensor Cores. CoRR Lizhi Xiang, Omid Asudeh, Gerald Sabin, Aravind Sukumaran-Rajam, P. Sadayappan
2024	B	`ed.`	Proceedings of the 33rd ACM SIGPLAN International Conference on Compiler Construction, CC 2024, Edinburgh, United Kingdom, March 2-3, 2024 CC Gabriel Rodríguez, P. Sadayappan, Aravind Sukumaran-Rajam
2023	—	`conf`	A Performance Portability Study Using Tensor Contraction Benchmarks. IPDPS Workshops M. Emin Ozturk, Omid Asudeh, Gerald Sabin, P. Sadayappan, Aravind Sukumaran-Rajam
2023	J	`jnl`	Accelerating Graph Computations on 3D NoC-Enabled PIM Architectures. ACM Trans. Design Autom. Electr. Syst. Dwaipayan Choudhury, Lizhi Xiang, Aravind Sukumaran-Rajam, Anantharaman Kalyanaraman, Partha Pratim Pande
2023	A	`conf`	Communication Optimization for Distributed Execution of Graph Neural Networks. IPDPS Süreyya Emre Kurt, Jinghua Yan, Aravind Sukumaran-Rajam, Prashant Pandey, P. Sadayappan
2023	B	`conf`	TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition. PPoPP Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam, P. Sadayappan, Bo Yuan, Dingwen Tao
2023	—	`conf`	cuAlign: Scalable Network Alignment on GPU Accelerators. SC Workshops Lizhi Xiang, Arif M. Khan, S. M. Ferdous, Aravind Sukumaran-Rajam, Mahantesh Halappanavar
2022	A	`conf`	Comprehensive Accelerator-Dataflow Co-design Optimization for Convolutional Neural Networks. CGO Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan
2022	B	`conf`	Effective Performance Modeling and Domain-Specific Compiler Optimization of CNNs for GPUs. PACT Yufan Xu, Qiwei Yuan, Erik Curtis Barton, Rui Li, P. Sadayappan, Aravind Sukumaran-Rajam
2022	B	`conf`	High-Performance Architecture Aware Sparse Convolutional Neural Networks for GPUs. PACT Lizhi Xiang, P. Sadayappan, Aravind Sukumaran-Rajam
2022	J	`jnl`	High-Performance and Energy-Efficient 3D Manycore GPU Architecture for Accelerating Graph Analytics. ACM J. Emerg. Technol. Comput. Syst. Dwaipayan Choudhury, Aravind Sukumaran-Rajam, Ananth Kalyanaraman, Partha Pratim Pande
2022	J	`jnl`	Software/Hardware Co-design of 3D NoC-based GPU Architectures for Accelerated Graph Computations. ACM Trans. Design Autom. Electr. Syst. Dwaipayan Choudhury, Reet Barik, Aravind Sukumaran-Rajam, Ananth Kalyanaraman, Partha Pratim Pande
2022	A	`conf`	Sparsity-Aware Tensor Decomposition. IPDPS Süreyya Emre Kurt, Saurabh Raje, Aravind Sukumaran-Rajam, P. Sadayappan
2022	J	`jnl`	TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition. CoRR Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam, P. Sadayappan, Bo Yuan, Dingwen Tao
2022	B	`conf`	Training of deep learning pipelines on memory-constrained GPUs via segmented fused-tiled execution. CC Yufan Xu, Saurabh Raje, Atanas Rountev, Gerald Sabin, Aravind Sukumaran-Rajam, P. Sadayappan
2021	J	`jnl`	Analytical Characterization and Design Space Exploration for Optimization of CNNs. CoRR Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan
2021	A*	`conf`	Analytical characterization and design space exploration for optimization of CNNs. ASPLOS Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan
2021	B	`conf`	Efficient Distributed Algorithms for Convolutional Neural Networks. SPAA Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan
2021	J	`jnl`	Efficient distributed algorithms for Convolutional Neural Networks. CoRR Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan
2021	A	`conf`	cuTS: scaling subgraph isomorphism on distributed multi-GPU systems using trie based data structure. SC Lizhi Xiang, Arif Khan, Edoardo Serra, Mahantesh Halappanavar, Aravind Sukumaran-Rajam
2020	A*	`conf`	ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization. KDD Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
2020	A	`conf`	Efficient tiled sparse matrix multiplication through matrix signatures. SC Süreyya Emre Kurt, Aravind Sukumaran-Rajam, Fabrice Rastello, P. Sadayappan
2019	A	`conf`	A Code Generator for High-Performance Tensor Contractions on GPUs. CGO Jinsung Kim, Aravind Sukumaran-Rajam, Vineeth Thumma, Sriram Krishnamoorthy, Ajay Panyala, Louis-Noël Pouchet, Atanas Rountev, P. Sadayappan
2019	B	`conf`	Adaptive sparse tiling for sparse matrix multiplication. PPoPP Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, P. Sadayappan
2019	A	`conf`	An efficient mixed-mode representation of sparse tensors. SC Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Prashant Singh Rawat, Sriram Krishnamoorthy, P. Sadayappan
2019	A	`conf`	Analytical cache modeling and tilesize optimization for tensor contractions. SC Rui Li, Aravind Sukumaran-Rajam, Richard Veras, Tze Meng Low, Fabrice Rastello, Atanas Rountev, P. Sadayappan
2019	A	`conf`	Load-Balanced Sparse MTTKRP on GPUs. IPDPS Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Richard W. Vuduc, P. Sadayappan
2019	J	`jnl`	Load-Balanced Sparse MTTKRP on GPUs. CoRR Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Richard W. Vuduc, P. Sadayappan
2019	A	`conf`	On Optimizing Complex Stencils on GPUs. IPDPS Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan
2019	J	`jnl`	PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization. CoRR Gordon Euhyun Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
2019	—	`conf`	Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings. MLHPC@SC Gordon Euhyun Moon, Denis Newman-Griffis, Jinsung Kim, Aravind Sukumaran-Rajam, Eric Fosler-Lussier, P. Sadayappan
2018	A	`conf`	Associative instruction reordering to alleviate register pressure. SC Prashant Singh Rawat, Aravind Sukumaran-Rajam, Atanas Rountev, Fabrice Rastello, Louis-Noël Pouchet, P. Sadayappan
2018	J	`jnl`	Domain-Specific Optimization and Generation of High-Performance GPU Code for Stencil Computations. Proc. IEEE Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Mahesh Ravishankar, Vinod Grover, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan
2018	—	`conf`	Effective Machine Learning Based Format Selection and Performance Modeling for SpMV on GPUs. IPDPS Workshops Israt Nisa, Charles Siegel, Aravind Sukumaran-Rajam, Abhinav Vishnu, P. Sadayappan
2018	A	`conf`	Efficient sparse-matrix multi-vector product on GPUs. HPDC Changwan Hong, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Jinsung Kim, Süreyya Emre Kurt, Israt Nisa, Shivani Sabhlok, Ümit V. Çatalyürek, Srinivasan Parthasarathy, P. Sadayappan
2018	A*	`conf`	GPU code optimization using abstract kernel emulation and sensitivity analysis. PLDI Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan
2018	A	`conf`	Optimizing Tensor Contractions in CCSD(T) for Efficient Execution on GPUs. ICS Jinsung Kim, Aravind Sukumaran-Rajam, Changwan Hong, Ajay Panyala, Rohit Kumar Srivastava, Sriram Krishnamoorthy, P. Sadayappan
2018	—	`conf`	Parallel Latent Dirichlet Allocation on GPUs. ICCS (2) Gordon Euhyun Moon, Israt Nisa, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Srinivasan Parthasarathy, P. Sadayappan
2018	B	`conf`	Performance modeling for GPUs using abstract kernel emulation. PPoPP Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan
2018	B	`conf`	Register optimizations for stencils on GPUs. PPoPP Prashant Singh Rawat, Fabrice Rastello, Aravind Sukumaran-Rajam, Louis-Noël Pouchet, Atanas Rountev, P. Sadayappan
2018	Misc	`conf`	Sampled Dense Matrix Multiplication for High-Performance Machine Learning. HiPC Israt Nisa, Aravind Sukumaran-Rajam, Süreyya Emre Kurt, Changwan Hong, P. Sadayappan
2018	A	`conf`	TTLG - An Efficient Tensor Transposition Library for GPUs. IPDPS Jyothi Vedurada, Arjun Suresh, Aravind Sukumaran-Rajam, Jinsung Kim, Changwan Hong, Ajay Panyala, Sriram Krishnamoorthy, V. Krishna Nandivada, Rohit Kumar Srivastava, P. Sadayappan
2017	Misc	`conf`	Characterization of Data Movement Requirements for Sparse Matrix Computations on GPUs. HiPC Süreyya Emre Kurt, Vineeth Thumma, Changwan Hong, Aravind Sukumaran-Rajam, P. Sadayappan
2017	B	`conf`	MultiGraph: Efficient Graph Processing on GPUs. PACT Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, P. Sadayappan
2017	A	`conf`	On improving performance of sparse matrix-matrix multiplication on GPUs. ICS Rakshith Kunchum, Ankur Chaudhry, Aravind Sukumaran-Rajam, Qingpeng Niu, Israt Nisa, P. Sadayappan
2017	B	`conf`	POSTER: Statement Reordering to Alleviate Register Pressure for Stencils on GPUs. PACT Prashant Singh Rawat, Aravind Sukumaran-Rajam, Atanas Rountev, Fabrice Rastello, Louis-Noël Pouchet, P. Sadayappan
2017	—	`conf`	Parallel CCD++ on GPU for Matrix Factorization. GPGPU@PPoPP Israt Nisa, Aravind Sukumaran-Rajam, Rakshith Kunchum, P. Sadayappan
2017	—	`conf`	Parallel LDA with Over-Decomposition. HiPC Workshops Gordon Euhyun Moon, Aravind Sukumaran-Rajam, P. Sadayappan
2016	J	`jnl`	The Polyhedral Model of Nonlinear Loops. ACM Trans. Archit. Code Optim. Aravind Sukumaran-Rajam, Philippe Clauss
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
2015	—	`conf`	Speculative Runtime Parallelization of Loop Nests: Towards Greater Scope and Efficiency. IPDPS Workshops Aravind Sukumaran-Rajam, Luis Esteban Campostrini, Juan Manuel Martinez Caamaño, Philippe Clauss
2014	B	`conf`	Speculative Program Parallelization with Scalable and Decentralized Runtime Verification. RV Aravind Sukumaran-Rajam, Juan Manuel Martinez Caamaño, Willy Wolff, Alexandra Jimborean, Philippe Clauss
2013	—	`conf`	Online Dynamic Dependence Analysis for Speculative Polyhedral Parallelization. Euro-Par Alexandra Jimborean, Philippe Clauss, Juan Manuel Martinez Caamaño, Aravind Sukumaran-Rajam