Roshan Dathathri

Roshan Dathathri

Researcher in Computer Science

Publications

You can also find my articles on my Google Scholar profile.

Kimbap: A Node-Property Map System for Distributed Graph Analytics

Published in ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2024

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Recommended citation: Hochan Lee, Roshan Dathathri, Keshav Pingali, “Kimbap: A Node-Property Map System for Distributed Graph Analytics,” Proceedings of the ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), April 2024. https://doi.org/10.1145/3620665.3640421

Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining

Published in ACM International Conference on Supercomputing (ICS), 2021

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Recommended citation: Xuhao Chen, Roshan Dathathri, Gurbinder Gill, Loc Hoang, and Keshav Pingali, "Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining", Proceedings of the ACM International Conference on Supercomputing (ICS), June 2021. https://dl.acm.org/doi/10.1145/3447818.3460359

Distributed Training of Embeddings using Graph Analytics

Published in IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2021

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Recommended citation: Gurbinder Gill, Roshan Dathathri, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Olli Saarikivi, “Distributed Training of Embeddings using Graph Analytics,” Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2021.

A Study of APIs for Graph Analytics Workloads

Published in Proceedings of the IEEE International Symposium on Workload Characterization (IISWC), 2020

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Recommended citation: Hochan Lee, David Wong, Loc Hoang, Roshan Dathathri, Gurbinder Gill, Vishwesh Jatala, David Kuck, and Keshav Pingali, “A Study of APIs for Graph Analytics Workloads,” Proceedings of the 2020 IEEE International Symposium on Workload Characterization (IISWC), October 2020.

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

Published in Proceedings of the IEEE International Symposium on Workload Characterization (IISWC), 2020

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Recommended citation: Ariful Azad, Mohsen Mahmoudi Aznaveh, Scott Beamer, Mark Blanco, Jinhao Chen, Luke D’Alessandro, Roshan Dathathri, Tim Davis, Kevin Deweese, Jesun Firoz, Henry A Gabb, Gurbinder Gill, Balint Hegyi, Scott Kolodzie, Tze Meng Low, Andrew Lumsdaine, Tugsbayasgalan Manlaibaatar, Timothy G Mattson, Scott McMillan, Ramesh Peri, Keshav Pingali, Upasana Sridhar, Gabor Szarnyas, Yunming Zhang, Yongzhe Zhang, “Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite,” Proceedings of the 2020 IEEE International Symposium on Workload Characterization (IISWC), October 2020.

EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation

Published in ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2020

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Recommended citation: Roshan Dathathri, Blagovesta Kostova, Olli Saarikivi, Wei Dai, Kim Laine, Madan Musuvathi, “EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation,” Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation (PLDI), June 2020. https://doi.org/10.1145/3385412.3386023

A Study of Graph Analytics for Massive Datasets on Distributed Multi-GPUs

Published in IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

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Recommended citation: Vishwesh Jatala, Roshan Dathathri, Gurbinder Gill, Loc Hoang, V. Krishna Nandivada, Keshav Pingali, “A Study of Graph Analytics for Massive Datasets on Distributed GPUs,” Proceedings of the 34th IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2020.

Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU

Published in Proceedings of the International Conference on Very Large Data Bases (PVLDB), 2020

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Recommended citation: Xuhao Chen, Roshan Dathathri, Gurbinder Gill, Keshav Pingali, “Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU,” Proceedings of the 46th International Conference on Very Large Data Bases (PVLDB), 13(8), April 2020. https://doi.org/10.14778/3389133.3389137

Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory

Published in Proceedings of the International Conference on Very Large Data Bases (PVLDB), 2020

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Recommended citation: Gurbinder Gill, Roshan Dathathri, Loc Hoang, Ramesh Peri, Keshav Pingali, “Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory,” Proceedings of the 46th International Conference on Very Large Data Bases (PVLDB), 13(8), April 2020. https://doi.org/10.14778/3389133.3389145

Gluon-Async: A Bulk-Asynchronous System for Distributed and Heterogeneous Graph Analytics

Published in ACM/IEEE International Conference on Parallel Architectures and Compilation Techniques (PACT), 2019

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Recommended citation: Roshan Dathathri, Gurbinder Gill, Loc Hoang, Hoang-Vu Dang, Vishwesh Jatala, V. Krishna Nandivada, Marc Snir, Keshav Pingali, “Gluon-Async: A Bulk-Asynchronous System for Distributed and Heterogeneous Graph Analytics,” Proceedings of the 28th IEEE International Conference on Parallel Architectures and Compilation Techniques (PACT), September 2019.

CHET: An Optimizing Compiler for Fully-Homomorphic Neural-Network Inferencing

Published in ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2019

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Recommended citation: Roshan Dathathri, Olli Saarikivi, Hao Chen, Kim Laine, Kristin Lauter, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, “CHET: An Optimizing Compiler for Fully-Homomorphic Neural-Network Inferencing,” Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2019. https://doi.org/10.1145/3314221.3314628

CuSP: A Customizable Streaming Edge Partitioner for Distributed Graph Analytics

Published in IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2019

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Recommended citation: Loc Hoang, Roshan Dathathri, Gurbinder Gill, Keshav Pingali, “CuSP: A Customizable Streaming Edge Partitioner for Distributed Graph Analytics,” Proceedings of the 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2019.

Phoenix: A Substrate for Resilient Distributed Graph Analytics

Published in ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2019

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Recommended citation: Roshan Dathathri, Gurbinder Gill, Loc Hoang, Keshav Pingali, “Phoenix: A Substrate for Resilient Distributed Graph Analytics,” Proceedings of the 24th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), April 2019. https://doi.org/10.1145/3297858.3304056

A Round-Efficient Distributed Betweenness Centrality Algorithm

Published in ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2019

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Recommended citation: Loc Hoang, Matteo Pontecorvi, Roshan Dathathri, Gurbinder Gill, Bozhi You, Keshav Pingali, Vijaya Ramachandran, “A Round-Efficient Distributed Betweenness Centrality Algorithm,” Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), February 2019. https://doi.org/10.1145/3293883.3295729

A Study of Partitioning Policies for Graph Analytics on Large-scale Distributed Platforms

Published in Proceedings of the International Conference on Very Large Data Bases (PVLDB), 2018

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Recommended citation: Gurbinder Gill, Roshan Dathathri, Loc Hoang, Keshav Pingali, “A Study of Partitioning Policies for Graph Analytics on Large-scale Distributed Platforms,” Proceedings of the 45th International Conference on Very Large Data Bases (PVLDB), 12(4): 321-334, December 2018. https://doi.org/10.14778/3297753.3297754

Abelian: A Compiler for Graph Analytics on Distributed, Heterogeneous Platforms

Published in International European Conference on Parallel and Distributed Computing (Euro-Par), 2018

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Recommended citation: Gurbinder Gill, Roshan Dathathri, Loc Hoang, Andrew Lenharth, Keshav Pingali, “Abelian: A Compiler for Graph Analytics on Distributed, Heterogeneous Platforms,” Proceedings of the 24th International European Conference on Parallel and Distributed Computing (Euro-Par), August 2018. https://link.springer.com/chapter/10.1007/978-3-319-96983-1_18

Gluon: A Communication-Optimizing Substrate for Distributed Heterogeneous Graph Analytics

Published in ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2018

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Recommended citation: Roshan Dathathri, Gurbinder Gill, Loc Hoang, Hoang-Vu Dang, Alex Brooks, Nikoli Dryden, Marc Snir, Keshav Pingali, “Gluon: A Communication-Optimizing Substrate for Distributed Heterogeneous Graph Analytics,” Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2018. https://dl.acm.org/authorize?N668550

A Lightweight Communication Runtime for Distributed Graph Analytics

Published in IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2018

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Recommended citation: Hoang-Vu Dang, Roshan Dathathri, Gurbinder Gill, Alex Brooks, Nikoli Dryden, Andrew Lenharth, Loc Hoang, Keshav Pingali, Marc Snir, “A Lightweight Communication Runtime for Distributed Graph Analytics,” Proceedings of the 32nd IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2018. https://ieeexplore.ieee.org/abstract/document/8425251/

Distributed memory code generation for mixed irregular/regular computations

Published in ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2015

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Recommended citation: Mahesh Ravishankar, Roshan Dathathri, Venmugil Elango, Louis-Noel Pouchet, J Ramanujam, Atanas Rountev, P Sadayappan, “Distributed memory code generation for mixed irregular/regular computations,” Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), January 2015. https://dl.acm.org/authorize?N658061

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Published in International Conference on Parallel Architectures and Compilation Techniques (PACT), 2013

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Recommended citation: Roshan Dathathri, Chandan Reddy, Thejas Ramashekar, Uday Bondhugula, “Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory,” Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques (PACT), September 2013. https://dl.acm.org/citation.cfm?id=2523771