Sudarshan Srinivasan

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 40

Top Topics

Matrix Multiplication

Top Venues

Publications

Chandra Sekhar Mummidi, Victor da Cruz Ferreira, Sudarshan Srinivasan, Sandip Kundu
Highly Efficient Self-checking Matrix Multiplication on Tiled AMX Accelerators. ACM Trans. Archit. Code Optim. 21 (2) (2024)
Abhimanyu Bambhaniya, Ritik Raj, Geonhwa Jeong, Souvik Kundu, Sudarshan Srinivasan, Midhilesh Elavazhagan, Madhu Kumar, Tushar Krishna
Demystifying Platform Requirements for Diverse LLM Inference Use Cases. CoRR (2024)
William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna
LIBRA: Enabling Workload-Aware Multi-Dimensional Network Topology Optimization for Distributed Training of Large AI Models. ISPASS (2024)
Ran Elgedawy, Sudarshan Srinivasan, Ioana Danciu
Dynamic Q&A of Clinical Documents with Large Language Models. CoRR (2024)
Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan, Caitlin Rizy, Ioana Danciu, Jodie Trafton, Kathryn Knight
Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approach. CoRR (2024)
Saeed Rashidi, William Won, Sudarshan Srinivasan, Puneet Gupta, Tushar Krishna
FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Models. CoRR (2024)
Sandeep Bal, Chandra Sekhar Mummidi, Victor da Cruz Ferreira, Sudarshan Srinivasan, Sandip Kundu
A Novel Fault-Tolerant Architecture for Tiled Matrix Multiplication. DATE (2023)
William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Ajaya Durg, Swati Gupta, Tushar Krishna
TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training. CoRR (2023)
William Won, Taekyung Heo, Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna
ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale. CoRR (2023)
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
Question-Answering System Extracts Information on Injection Drug Use from Clinical Progress Notes. CoRR (2023)
William Won, Taekyung Heo, Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna
ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale. ISPASS (2023)
Edmon Begoli, Sudarshan Srinivasan, Maria Mahbub
Improving Efficiency and Robustness of Transformer-based Information Retrieval Systems. SIGIR (2022)
Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli, Gregory D. Peterson
BioADAPT-MRC: adversarial learning-based domain adaptation improves biomedical machine reading comprehension task. Bioinform. 38 (18) (2022)
Chandra Sekhar Mummidi, Sandeep Bal, Brunno F. Goldstein, Sudarshan Srinivasan, Sandip Kundu
A Highly-Efficient Error Detection Technique for General Matrix Multiplication using Tiled Processing on SIMD Architecture. ICCD (2022)
Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli, Gregory D. Peterson
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Task. CoRR (2022)
Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna
Themis: a network bandwidth-aware collective scheduling policy for distributed training of DL models. ISCA (2022)
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
The Sensitivity of Word Embeddings-based Author Detection Models to Semantic-preserving Adversarial Perturbations. CoRR (2021)
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. CoRR (2021)
Brunno F. Goldstein, Victor da Cruz Ferreira, Sudarshan Srinivasan, Dipankar Das, Alexandre Solon Nery, Sandip Kundu, Felipe M. G. França
A Lightweight Error-Resiliency Mechanism for Deep Neural Networks. ISQED (2021)
William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna
Exploring Multi-dimensional Hierarchical Network Topologies for Efficient Distributed Training of Trillion Parameter DL Models. CoRR (2021)
Edmon Begoli, Seung-Hwan Lim, Sudarshan Srinivasan
Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments. IEEE BigData (2021)
Saeed Rashidi, Matthew Denton, Srinivas Sridharan, Sudarshan Srinivasan, Amoghavarsha Suresh, Jade Nie, Tushar Krishna
Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms. ISCA (2021)
Sudarshan Srinivasan, Edmon Begoli, Maria Mahbub, Kathryn Knight
Nomen est Omen - The Role of Signatures in Ascribing Email Author Identity with Transformer Neural Networks. SP Workshops (2021)
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. IPDPS (2021)
Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna
Themis: A Network Bandwidth-Aware Collective Scheduling Policy for Distributed Training of DL Models. CoRR (2021)
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
Reliability Evaluation of Compressed Deep Learning Models. LASCAS (2020)
Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures. CoRR (2020)
Eric Qin, Ananda Samajdar, Hyoukjun Kwon, Vineet Nadella, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul, Tushar Krishna
SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training. HPCA (2020)
Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna
ASTRA-SIM: Enabling SW/HW Co-Design Exploration for Distributed DL Training Platforms. ISPASS (2020)
Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
Optimizing deep learning recommender systems training on CPU cluster architectures. SC (2020)
Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Matthew Denton, Tushar Krishna
Efficient Communication Acceleration for Next-Gen Scale-up Deep Learning Training Platforms. CoRR (2020)
Edmon Begoli, Sudarshan Srinivasan, Maria Mahbub
The Transformers for Polystores - The Next Frontier for Polystore Research. Poly/DMAH@VLDB (2020)
Naveen Mellempudi, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul
Mixed Precision Training With 8-bit Floating Point. CoRR (2019)
Abhisek Kundu, Sudarshan Srinivasan, Eric C. Qin, Dhiraj D. Kalamkar, Naveen K. Mellempudi, Dipankar Das, Kunal Banerjee, Bharat Kaul, Pradeep Dubey
K-TanH: Hardware Efficient Activations For Deep Learning. CoRR (2019)
Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble, Sasikanth Avancha, Dipankar Das, Naveen Mellempudi, Bharat Daga, Martin Langhammer, Gregg Baeckler, Bharat Kaul
High Performance Scalable FPGA Accelerator for Deep Neural Networks. CoRR (2019)
Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke
Training Google Neural Machine Translation on an Intel CPU Cluster. CLUSTER (2019)
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
A Study of BFLOAT16 for Deep Learning Training. CoRR (2019)
Sudarshan Srinivasan, Nithesh kurella, Israel Koren, Sandip Kundu
Exploring Heterogeneity within a Core for Improved Power Efficiency. IEEE Trans. Parallel Distributed Syst. 27 (4) (2016)
Sudarshan Srinivasan, Israel Koren, Sandip Kundu
Improving performance per Watt of non-monotonic Multicore Processors via bottleneck-based online program phase classification. ICCD (2016)
Sudarshan Srinivasan, Nithesh kurella, Israel Koren, Sandip Kundu
Dynamic Reconfiguration vs. DVFS: A Comparative Study on Power Efficiency of Processors. VLSI Design (2016)
Sudarshan Srinivasan, Israel Koren, Sandip Kundu
Online mechanism for reliability and power-efficiency management of a dynamically reconfigurable core. ICCD (2015)
Hamed Sajjadi Kia, Cristinel Ababei, Sudarshan Srinivasan, Shaista Jabeen
A new scalable fault tolerant routing algorithm for networks-on-chip. MWSCAS (2015)
Daniel Aceituna, Hyunsook Do, Sudarshan Srinivasan
A systematic approach to transforming system requirements into model checking specifications. ICSE Companion (2014)
Sudarshan Srinivasan, Nithesh kurella, Israel Koren, Rance Rodrigues, Sandip Kundu
A runtime support mechanism for fast mode switching of a self-morphing core for power efficiency. PACT (2014)
Sudarshan Srinivasan, Gideon Juve, Rafael Ferreira da Silva, Karan Vahi, Ewa Deelman
A cleanup algorithm for implementing storage constraints in scientific workflow executions. WORKS@SC (2014)
Sudarshan Srinivasan, Victor Hazlewood, Gregory D. Peterson
Descriptive Data Analysis of File Transfer Data. XSEDE (2014)
Sudarshan Srinivasan, Raghavan Kumar, Sandip Kundu
Program phase duration prediction and its application to fine-grain power management. ISVLSI (2013)
Sudarshan Srinivasan, Rance Rodrigues, Arunachalam Annamalai, Israel Koren, Sandip Kundu
A study on polymorphing superscalar processor dynamically to improve power efficiency. ISVLSI (2013)
Vinay C. Patil, Sudarshan Srinivasan, Wayne P. Burleson, Sandip Kundu
Impact of Clock-Gating on Power Distribution Network Using Wavelet Analysis. VLSI Design (2013)
Sudarshan Srinivasan, Rance Rodrigues, Arunachalam Annamalai, Israel Koren, Sandip Kundu
On dynamic polymorphing of a superscalar core for improving energy efficiency. ICCD (2013)
Sudarshan Srinivasan, Kunal P. Ganeshpure, Sandip Kundu
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. 31 (12) (2012)
Sudarshan Srinivasan, Sandip Kundu
Functional test pattern generation for maximizing temperature in 3D IC chip stack. ISQED (2012)
Victor Tomashevich, Sudarshan Srinivasan, Fabian Foerg, Ilia Polian
Cross-level protection of circuits against faults and malicious attacks. IOLTS (2012)
Sudarshan Srinivasan, Kunal P. Ganeshpure, Sandip Kundu
Maximizing hotspot temperature: Wavelet based modelling of heating and cooling profile of functional workloads. ISQED (2011)
Sudarshan Srinivasan, Bharath Phanibhushana, Arunkumar Vijayakumar, Sandip Kundu
Stress aware switching activity driven low power design of critical paths in nanoscale CMOS circuits. ACM Great Lakes Symposium on VLSI (2011)