Sudarshan Srinivasan

66 papers A* 6A 3B 4C 6Misc 2Journal 28Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Leveraging large language models to automate the identification of healthcare access barriers for veterans. Int. J. Medical Informatics Sudarshan Srinivasan, Caitlin Rizy, Maria Mahbub, David Bolme, Alina Peluso, Jodie Trafton, Ioana Danciu
2026	J	`jnl`	Visual Word Sense Disambiguation with CLIP through Dual-Channel Text Prompting and Image Augmentations. CoRR Shamik Bhattacharya, Daniel Perkins, Yaren Dogan, Vineeth Konjeti, Sudarshan Srinivasan, Edmon Begoli
2025	A*	`conf`	FRED: A Wafer-scale Fabric for 3D Parallel DNN Training. ISCA Saeed Rashidi, William Won, Sudarshan Srinivasan, Puneet Gupta, Tushar Krishna
2025	J	`jnl`	HARNESS: Human-Agent Risk Navigation and Event Safety System for Proactive Hazard Forecasting in High-Risk DOE Environments. CoRR Ran Elgedawy, Sanjay Das, Ethan Seefried, Gavin M. Wiggins, Ryan Burchfield, Dana Hewit, Sudarshan Srinivasan, Todd Thomas, Prasanna Balaprakash, Tirthankar Ghosal
2025	J	`jnl`	Understanding and Optimizing Multi-Stage AI Inference Pipelines. CoRR Abhimanyu Rajeshkumar Bambhaniya, Hanjiang Wu, Suvinay Subramanian, Sudarshan Srinivasan, Souvik Kundu, Amir Yazdanbakhsh, Midhilesh Elavazhagan, Madhu Kumar, Tushar Krishna
2024	J	`jnl`	A Compound Data Poisoning Technique with Significant Adversarial Effects on Transformer-based Sentiment Classification Tasks. ACM J. Data Inf. Qual. Edmon Begoli, Maria Mahbub, Linsey Passarella, Sudarshan Srinivasan
2024	J	`jnl`	Advancing NLP Security by Leveraging LLMs as Adversarial Engines. CoRR Sudarshan Srinivasan, Maria Mahbub, Amir Sadovnik
2024	J	`jnl`	Demystifying Platform Requirements for Diverse LLM Inference Use Cases. CoRR Abhimanyu Bambhaniya, Ritik Raj, Geonhwa Jeong, Souvik Kundu, Sudarshan Srinivasan, Midhilesh Elavazhagan, Madhu Kumar, Tushar Krishna
2024	J	`jnl`	Dynamic Q&A of Clinical Documents with Large Language Models. CoRR Ran Elgedawy, Sudarshan Srinivasan, Ioana Danciu
2024	J	`jnl`	FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Models. CoRR Saeed Rashidi, William Won, Sudarshan Srinivasan, Puneet Gupta, Tushar Krishna
2024	J	`jnl`	Highly Efficient Self-checking Matrix Multiplication on Tiled AMX Accelerators. ACM Trans. Archit. Code Optim. Chandra Sekhar Mummidi, Victor da Cruz Ferreira, Sudarshan Srinivasan, Sandip Kundu
2024	B	`conf`	LIBRA: Enabling Workload-Aware Multi-Dimensional Network Topology Optimization for Distributed Training of Large AI Models. ISPASS William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna
2024	J	`jnl`	Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approach. CoRR Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan, Caitlin Rizy, Ioana Danciu, Jodie Trafton, Kathryn Knight
2024	—	`conf`	Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models. AISec@CCS Camila Roa, Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli, Amir Sadovnik
2024	A*	`conf`	TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Machine Learning. MICRO William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Swati Gupta, Tushar Krishna
2023	A	`conf`	A Novel Fault-Tolerant Architecture for Tiled Matrix Multiplication. DATE Sandeep Bal, Chandra Sekhar Mummidi, Victor da Cruz Ferreira, Sudarshan Srinivasan, Sandip Kundu
2023	B	`conf`	ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale. ISPASS William Won, Taekyung Heo, Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna
2023	J	`jnl`	ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale. CoRR William Won, Taekyung Heo, Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna
2023	J	`jnl`	Question-Answering System Extracts Information on Injection Drug Use from Clinical Progress Notes. CoRR Maria Mahbub, Ian Goethert, Ioana Danciu, Kathryn Knight, Sudarshan Srinivasan, Suzanne Tamang, Karine Rozenberg-Ben-Dror, Hugo Solares, Susana B. Martins, Edmon Begoli, Gregory D. Peterson
2023	J	`jnl`	TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training. CoRR William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Ajaya Durg, Swati Gupta, Tushar Krishna
2022	C	`conf`	A Highly-Efficient Error Detection Technique for General Matrix Multiplication using Tiled Processing on SIMD Architecture. ICCD Chandra Sekhar Mummidi, Sandeep Bal, Brunno F. Goldstein, Sudarshan Srinivasan, Sandip Kundu
2022	J	`jnl`	BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Task. CoRR Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli, Gregory D. Peterson
2022	J	`jnl`	BioADAPT-MRC: adversarial learning-based domain adaptation improves biomedical machine reading comprehension task. Bioinform. Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli, Gregory D. Peterson
2022	A*	`conf`	Improving Efficiency and Robustness of Transformer-based Information Retrieval Systems. SIGIR Edmon Begoli, Sudarshan Srinivasan, Maria Mahbub
2022	A*	`conf`	Themis: a network bandwidth-aware collective scheduling policy for distributed training of DL models. ISCA Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna
2021	—	`conf`	A Lightweight Error-Resiliency Mechanism for Deep Neural Networks. ISQED Brunno F. Goldstein, Victor da Cruz Ferreira, Sudarshan Srinivasan, Dipankar Das, Alexandre Solon Nery, Sandip Kundu, Felipe M. G. França
2021	A*	`conf`	Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms. ISCA Saeed Rashidi, Matthew Denton, Srinivas Sridharan, Sudarshan Srinivasan, Amoghavarsha Suresh, Jade Nie, Tushar Krishna
2021	J	`jnl`	Exploring Multi-dimensional Hierarchical Network Topologies for Efficient Distributed Training of Trillion Parameter DL Models. CoRR William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna
2021	A	`conf`	Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. IPDPS Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
2021	J	`jnl`	Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. CoRR Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
2021	—	`conf`	Nomen est Omen - The Role of Signatures in Ascribing Email Author Identity with Transformer Neural Networks. SP (Workshops) Sudarshan Srinivasan, Edmon Begoli, Maria Mahbub, Kathryn Knight
2021	—	`conf`	Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments. IEEE BigData Edmon Begoli, Seung-Hwan Lim, Sudarshan Srinivasan
2021	J	`jnl`	The Sensitivity of Word Embeddings-based Author Detection Models to Semantic-preserving Adversarial Perturbations. CoRR Jeremiah Duncan, Fabian Fallas, Chris Gropp, Emily Herron, Maria Mahbub, Paula Olaya, Eduardo Ponce, Tabitha K. Samuel, Daniel Schultz, Sudarshan Srinivasan, Maofeng Tang, Viktor Zenkov, Quan Zhou, Edmon Begoli
2021	J	`jnl`	Themis: A Network Bandwidth-Aware Collective Scheduling Policy for Distributed Training of DL Models. CoRR Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna
2020	B	`conf`	ASTRA-SIM: Enabling SW/HW Co-Design Exploration for Distributed DL Training Platforms. ISPASS Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna
2020	J	`jnl`	Efficient Communication Acceleration for Next-Gen Scale-up Deep Learning Training Platforms. CoRR Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Matthew Denton, Tushar Krishna
2020	J	`jnl`	Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures. CoRR Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
2020	A	`conf`	Optimizing deep learning recommender systems training on CPU cluster architectures. SC Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
2020	—	`conf`	Reliability Evaluation of Compressed Deep Learning Models. LASCAS Brunno F. Goldstein, Sudarshan Srinivasan, Dipankar Das, Kunal Banerjee, Leandro Santiago de Araújo, Victor da Cruz Ferreira, Alexandre Solon Nery, Sandip Kundu, Felipe M. G. França
2020	A*	`conf`	SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training. HPCA Eric Qin, Ananda Samajdar, Hyoukjun Kwon, Vineet Nadella, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul, Tushar Krishna
2020	—	`conf`	The Transformers for Polystores - The Next Frontier for Polystore Research. Poly/DMAH@VLDB Edmon Begoli, Sudarshan Srinivasan, Maria Mahbub
2019	J	`jnl`	A Study of BFLOAT16 for Deep Learning Training. CoRR Dhiraj D. Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey
2019	J	`jnl`	High Performance Scalable FPGA Accelerator for Deep Neural Networks. CoRR Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble, Sasikanth Avancha, Dipankar Das, Naveen Mellempudi, Bharat Daga, Martin Langhammer, Gregg Baeckler, Bharat Kaul
2019	J	`jnl`	K-TanH: Hardware Efficient Activations For Deep Learning. CoRR Abhisek Kundu, Sudarshan Srinivasan, Eric C. Qin, Dhiraj D. Kalamkar, Naveen K. Mellempudi, Dipankar Das, Kunal Banerjee, Bharat Kaul, Pradeep Dubey
2019	J	`jnl`	Mixed Precision Training With 8-bit Floating Point. CoRR Naveen Mellempudi, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul
2019	C	`conf`	Training Google Neural Machine Translation on an Intel CPU Cluster. CLUSTER Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke
2018	—	`conf`	Evaluating Text Analytic Frameworks for Mental Health Surveillance. ICDE Workshops Benjamin Mayer, Joshua Arnold, Edmon Begoli, Everett Neil Rush, Michael Drewry, Kris Brown, Eduardo Ponce, Sudarshan Srinivasan
2018	—	`conf`	SynthNotes: A Generator Framework for High-volume, High-fidelity Synthetic Mental Health Notes. IEEE BigData Edmon Begoli, Kris Brown, Sudarshan Srinivasan, Suzanne Tamang
2016	Misc	`conf`	Dynamic Reconfiguration vs. DVFS: A Comparative Study on Power Efficiency of Processors. VLSID Sudarshan Srinivasan, Nithesh Kurella, Israel Koren, Sandip Kundu
2016	J	`jnl`	Exploring Heterogeneity within a Core for Improved Power Efficiency. IEEE Trans. Parallel Distributed Syst. Sudarshan Srinivasan, Nithesh Kurella, Israel Koren, Sandip Kundu
2016	C	`conf`	Improving performance per Watt of non-monotonic Multicore Processors via bottleneck-based online program phase classification. ICCD Sudarshan Srinivasan, Israel Koren, Sandip Kundu
2015	—	`conf`	A new scalable fault tolerant routing algorithm for networks-on-chip. MWSCAS Hamed Sajjadi Kia, Cristinel Ababei, Sudarshan Srinivasan, Shaista Jabeen
2015	C	`conf`	Online mechanism for reliability and power-efficiency management of a dynamically reconfigurable core. ICCD Sudarshan Srinivasan, Israel Koren, Sandip Kundu
2014	—	`conf`	A cleanup algorithm for implementing storage constraints in scientific workflow executions. WORKS@SC Sudarshan Srinivasan, Gideon Juve, Rafael Ferreira da Silva, Karan Vahi, Ewa Deelman
2014	B	`conf`	A runtime support mechanism for fast mode switching of a self-morphing core for power efficiency. PACT Sudarshan Srinivasan, Nithesh Kurella, Israel Koren, Rance Rodrigues, Sandip Kundu
2014	—	`conf`	A systematic approach to transforming system requirements into model checking specifications. ICSE Companion Daniel Aceituna, Hyunsook Do, Sudarshan Srinivasan
2014	—	`conf`	Descriptive Data Analysis of File Transfer Data. XSEDE Sudarshan Srinivasan, Victor Hazlewood, Gregory D. Peterson
2013	—	`conf`	A study on polymorphing superscalar processor dynamically to improve power efficiency. ISVLSI Sudarshan Srinivasan, Rance Rodrigues, Arunachalam Annamalai, Israel Koren, Sandip Kundu
2013	Misc	`conf`	Impact of Clock-Gating on Power Distribution Network Using Wavelet Analysis. VLSI Design Vinay C. Patil, Sudarshan Srinivasan, Wayne P. Burleson, Sandip Kundu
2013	C	`conf`	On dynamic polymorphing of a superscalar core for improving energy efficiency. ICCD Sudarshan Srinivasan, Rance Rodrigues, Arunachalam Annamalai, Israel Koren, Sandip Kundu
2013	—	`conf`	Program phase duration prediction and its application to fine-grain power management. ISVLSI Sudarshan Srinivasan, Raghavan Kumar, Sandip Kundu
2012	J	`jnl`	A Wavelet-Based Spatio-Temporal Heat Dissipation Model for Reordering of Program Phases to Produce Temperature Extremes in a Chip. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Sudarshan Srinivasan, Kunal P. Ganeshpure, Sandip Kundu
2012	C	`conf`	Cross-level protection of circuits against faults and malicious attacks. IOLTS Victor Tomashevich, Sudarshan Srinivasan, Fabian Foerg, Ilia Polian
2012	—	`conf`	Functional test pattern generation for maximizing temperature in 3D IC chip stack. ISQED Sudarshan Srinivasan, Sandip Kundu
2011	—	`conf`	Maximizing hotspot temperature: Wavelet based modelling of heating and cooling profile of functional workloads. ISQED Sudarshan Srinivasan, Kunal P. Ganeshpure, Sandip Kundu
2011	—	`conf`	Stress aware switching activity driven low power design of critical paths in nanoscale CMOS circuits. ACM Great Lakes Symposium on VLSI Sudarshan Srinivasan, Bharath Phanibhushana, Arunkumar Vijayakumar, Sandip Kundu