NoC with Near-Ideal Express Virtual Channels Using Global-Line Communication. - Tushar Krishna; Amit Kumar 002; Patrick Chiang 001; Mattan Erez; Li-Shiuan Peh (Hot Interconnects, 2008)

Texture filter memory: a power-efficient and scalable texture memory architecture for mobile graphics processors. - B. V. N. Silpa; Anjul Patney; Tushar Krishna; Preeti Ranjan Panda; G. S. Visweswaran (ICCAD, 2008)

GARNET: A detailed on-chip network model inside a full-system simulator. - Niket Agarwal; Tushar Krishna; Li-Shiuan Peh; Niraj K. Jha (ISPASS, 2009)

Express Virtual Channels with Capacitively Driven Global Links. - Tushar Krishna; Amit Kumar 002; Li-Shiuan Peh; Jacob Postman; Patrick Chiang 001; Mattan Erez (IEEE Micro, 2009)

SWIFT: A SWing-reduced interconnect for a Token-based Network-on-Chip in 90nm CMOS. - Tushar Krishna; Jacob Postman; Christopher Edmonds; Li-Shiuan Peh; Patrick Chiang 001 (ICCD, 2010)

Physical vs. Virtual Express Topologies with Low-Swing Links for Future Many-Core NoCs. - Chia-Hsin Owen Chen; Niket Agarwal; Tushar Krishna; Kyung-Hoae Koo; Li-Shiuan Peh; Krishna Saraswat (NOCS, 2010)

A low-swing crossbar and link generator for low-power networks-on-chip. - Chia-Hsin Owen Chen; Sunghyun Park 002; Tushar Krishna; Li-Shiuan Peh (ICCAD, 2011)

Towards the ideal on-chip fabric for 1-to-many and many-to-1 communication. - Tushar Krishna; Li-Shiuan Peh; Bradford M. Beckmann; Steven K. Reinhardt (MICRO, 2011)

The gem5 simulator. - Nathan L. Binkert; Bradford M. Beckmann; Gabriel Black; Steven K. Reinhardt; Ali G. Saidi; Arkaprava Basu; Joel Hestness; Derek Hower; Tushar Krishna; Somayeh Sardashti; Rathijit Sen; Korey Sewell; et al. (SIGARCH Comput. Archit. News, 2011)

Approaching the theoretical limits of a mesh NoC with a 16-node chip prototype in 45nm SOI. - Sunghyun Park 002; Tushar Krishna; Chia-Hsin Owen Chen; Bhavya K. Daya; Anantha P. Chandrakasan; Li-Shiuan Peh (DAC, 2012)

SMART: a single-cycle reconfigurable NoC for SoC applications. - Chia-Hsin Owen Chen; Sunghyun Park 002; Tushar Krishna; Suvinay Subramanian; Anantha P. Chandrakasan; Li-Shiuan Peh (DATE, 2013)

Breaking the on-chip latency barrier using SMART. - Tushar Krishna; Chia-Hsin Owen Chen; Woo-Cheol Kwon; Li-Shiuan Peh (HPCA, 2013)

Single-Cycle Multihop Asynchronous Repeated Traversal: A SMART Future for Reconfigurable On-Chip Networks. - Tushar Krishna; Chia-Hsin Owen Chen; Sunghyun Park 002; Woo-Cheol Kwon; Suvinay Subramanian; Anantha P. Chandrakasan; Li-Shiuan Peh (Computer, 2013)

SWIFT: A Low-Power Network-On-Chip Implementing the Token Flow Control Router Architecture With Swing-Reduced Interconnects. - Jacob Postman; Tushar Krishna; Christopher Edmonds; Li-Shiuan Peh; Patrick Chiang 001 (IEEE Trans. Very Large Scale Integr. Syst., 2013)

Locality-oblivious cache organization leveraging single-cycle multi-hop NoCs. - Woo-Cheol Kwon; Tushar Krishna; Li-Shiuan Peh (ASPLOS, 2014)

SCORPIO: 36-core shared memory processor demonstrating snoopy coherence on a mesh interconnect. - Chia-Hsin Owen Chen; Sunghyun Park 002; Suvinay Subramanian; Tushar Krishna; Bhavya K. Daya; Woo-Cheol Kwon; Brett Wilkerson; John Arends; Anantha P. Chandrakasan; Li-Shiuan Peh (Hot Chips Symposium, 2014)

SCORPIO: A 36-core research chip demonstrating snoopy coherence on a scalable mesh NoC with in-network ordering. - Bhavya K. Daya; Chia-Hsin Owen Chen; Suvinay Subramanian; Woo-Cheol Kwon; Sunghyun Park 002; Tushar Krishna; Jim Holt; Anantha P. Chandrakasan; Li-Shiuan Peh (ISCA, 2014)

Single-cycle collective communication over a shared network fabric. - Tushar Krishna; Li-Shiuan Peh (NOCS, 2014)

Smart: Single-Cycle Multihop Traversals over a Shared Network on Chip. - Tushar Krishna; Chia-Hsin Owen Chen; Woo-Cheol Kwon; Li-Shiuan Peh (IEEE Micro, 2014)

Enabling dedicated single-cycle connections over a shared network-on-chip. - Tushar Krishna (2014)

Efficient Control and Communication Paradigms for Coarse-Grained Spatial Architectures. - Michael Pellauer; Angshuman Parashar; Michael Adler; Bushra Ahsan; Randy L. Allmon; Neal Clayton Crago; Kermin Fleming; Mohit Gambhir; Aamer Jaleel; Tushar Krishna; Daniel Lustig; Stephen Maresh; et al. (ACM Trans. Comput. Syst., 2015)

14.5 Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks. - Yu-Hsin Chen; Tushar Krishna; Joel S. Emer; Vivienne Sze (ISSCC, 2016)

Automatic place-and-route of emerging LED-driven wires within a monolithically-integrated CMOS-III-V process. - Tushar Krishna; Arya Balachandran; Siau Ben Chiah; Li Zhang; Bing Wang; Cong Wang; Kenneth Eng-Kian Lee; Jürgen Michel; Li-Shiuan Peh (DATE, 2017)

Static Bubble: A Framework for Deadlock-Free Irregular On-chip Topologies. - Aniruddh Ramrakhyani; Tushar Krishna (HPCA, 2017)

A case for low frequency single cycle multi hop NoCs for energy efficiency and high performance. - Monodeep Kar; Tushar Krishna (ICCAD, 2017)

OpenSMART: Single-cycle multi-hop NoC generator in BSV and Chisel. - Hyoukjun Kwon; Tushar Krishna (ISPASS, 2017)

Lightweight Emulation of Virtual Channels using Swaps. - Mayank Parasar; Tushar Krishna (NoCArc@MICRO, 2017)

Adaptive Manycore Architectures for Big Data Computing. - Janardhan Rao Doppa; Ryan Gary Kim; Mihailo Isakov; Michel A. Kinsy; Hyoukjun Kwon; Tushar Krishna (NOCS, 2017)

Rethinking NoCs for Spatial Neural Network Accelerators. - Hyoukjun Kwon; Ananda Samajdar; Tushar Krishna (NOCS, 2017)

VESPA: VIPT Enhancements for Superpage Accesses. - Mayank Parasar; Abhishek Bhattacharjee; Tushar Krishna (CoRR, 2017)

FASHION: Fault-Aware Self-Healing Intelligent On-chip Network. - Pengju Ren; Michel A. Kinsy; Mengjiao Zhu; Shreeya Khadka; Mihailo Isakov; Aniruddh Ramrakhyani; Tushar Krishna; Nanning Zheng 001 (CoRR, 2017)

Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks. - Yu-Hsin Chen; Tushar Krishna; Joel S. Emer; Vivienne Sze (IEEE J. Solid State Circuits, 2017)

On-Chip Networks, Second Edition - Natalie D. Enright Jerger; Tushar Krishna; Li-Shiuan Peh (Morgan & Claypool Publishers, 2017)

LATR: Lazy Translation Coherence. - Mohan Kumar; Steffen Maass; Sanidhya Kashyap; Ján Veselý; Zi Yan; Taesoo Kim; Abhishek Bhattacharjee; Tushar Krishna (ASPLOS, 2018)

MAERI: Enabling Flexible Dataflow Mapping over DNN Accelerators via Reconfigurable Interconnects. - Hyoukjun Kwon; Ananda Samajdar; Tushar Krishna (ASPLOS, 2018)

Optimizing the data placement and transformation for multi-bank CGRA computing system. - Zhongyuan Zhao 004; Yantao Liu; Weiguang Sheng; Tushar Krishna; Qin Wang 009; Zhigang Mao (DATE, 2018)

FastTrack: Exploiting Fast FPGA Wiring for Implementing NoC Shortcuts (Abstract Only). - Nachiket Kapre; Tushar Krishna (FPGA, 2018)

Spoofing Prevention via RF Power Profiling in Wireless Network-on-Chip. - Brian Lebiednik; Sergi Abadal; Hyoukjun Kwon; Tushar Krishna (AISTECS@HiPEAC, 2018)

Merge Network for a Non-Von Neumann Accumulate Accelerator in a 3D Chip. - Anirudh Jain; Sriseshan Srikanth; Erik P. DeBenedictis; Tushar Krishna (ICRC, 2018)

FastTrack: Leveraging Heterogeneous FPGA Wires to Design Low-Cost High-Performance Soft NoCs. - Nachiket Kapre; Tushar Krishna (ISCA, 2018)

SEESAW: Using Superpages to Improve VIPT Caches. - Mayank Parasar; Abhishek Bhattacharjee; Tushar Krishna (ISCA, 2018)

Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube. - Ramyad Hadidi; Bahar Asgari; Jeffrey S. Young 001; Burhan Ahmad Mudassar; Kartikay Garg; Tushar Krishna; Hyesoon Kim (ISPASS, 2018)

Scalable Distributed Last-Level TLBs Using Low-Latency Interconnects. - Srikant Bharadwaj; Guilherme Cox; Tushar Krishna; Abhishek Bhattacharjee (MICRO, 2018)

GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware. - Ananda Samajdar; Parth Mannan; Kartikay Garg; Tushar Krishna (MICRO, 2018)

Architecting a Secure Wireless Network-on-Chip. - Brian Lebiednik; Sergi Abadal; Hyoukjun Kwon; Tushar Krishna (NOCS, 2018)

Brownian Bubble Router: Enabling Deadlock Freedom via Guaranteed Forward Progress. - Mayank Parasar; Ankit Sinha; Tushar Krishna (NOCS, 2018)

MAESTRO: An Open-source Infrastructure for Modeling Dataflows within Deep Learning Accelerators. - Hyoukjun Kwon; Michael Pellauer; Tushar Krishna (CoRR, 2018)

SCALE-Sim: Systolic CNN Accelerator. - Ananda Samajdar; Yuhao Zhu 001; Paul N. Whatmough; Matthew Mattina; Tushar Krishna (CoRR, 2018)

A Communication-Centric Approach for Designing Flexible DNN Accelerators. - Hyoukjun Kwon; Ananda Samajdar; Tushar Krishna (IEEE Micro, 2018)

Architecture, Chip, and Package Co-design Flow for 2.5D IC Design Enabling Heterogeneous IP Reuse. - Jinwoo Kim; Gauthaman Murali; Heechun Park; Eric Qin 001; Hyoukjun Kwon; Venkata Chaitanya Krishna Chekuri; Nihar Dasari; Arvind Singh; Minah Lee; Hakki Mert Torun; Kallol Roy; Madhavan Swaminathan; et al. (DAC, 2019)

Scaling the Cascades: Interconnect-Aware FPGA Implementation of Machine Learning Problems. - Ananda Samajdar; Tushar Garg; Tushar Krishna; Nachiket Kapre (FPL, 2019)

Understanding the Impact of On-chip Communication on DNN Accelerator Performance. - Robert Guirado; Hyoukjun Kwon; Eduard Alarcón; Sergi Abadal; Tushar Krishna (ICECS, 2019)

Characterizing the Deployment of Deep Neural Networks on Commercial Edge Devices. - Ramyad Hadidi; Jiashen Cao; Yilun Xie; Bahar Asgari; Tushar Krishna; Hyesoon Kim (IISWC, 2019)

mRNA: Enabling Efficient Mapping Space Exploration for a Reconfiguration Neural Accelerator. - Zhongyuan Zhao 004; Hyoukjun Kwon; Sachit Kuhar; Weiguang Sheng; Zhigang Mao; Tushar Krishna (ISPASS, 2019)

A communication-centric approach for designing flexible DNN accelerators. - Tushar Krishna (NoCArc@MICRO, 2019)

Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach. - Hyoukjun Kwon; Prasanth Chatarasi; Michael Pellauer; Angshuman Parashar; Vivek Sarkar; Tushar Krishna (MICRO, 2019)

SWAP: Synchronized Weaving of Adjacent Packets for Network Deadlock Resolution. - Mayank Parasar; Natalie D. Enright Jerger; Paul V. Gratz; Joshua San Miguel; Tushar Krishna (MICRO, 2019)

Reinforcement learning based interconnection routing for adaptive traffic optimization. - Sheng-Chun Kao; Chao-Han Huck Yang; Pin-Yu Chen; Xiaoli Ma; Tushar Krishna (NOCS, 2019)

BINDU: deadlock-freedom with one bubble in the network. - Mayank Parasar; Tushar Krishna (NOCS, 2019)

HERALD: Optimizing Heterogeneous DNN Accelerators for Edge Devices. - Hyoukjun Kwon; Liangzhen Lai; Tushar Krishna; Vikas Chandra (CoRR, 2019)

Synchronized Progress in Interconnection Networks (SPIN): A New Theory for Deadlock Freedom. - Aniruddh Ramrakhyani; Paul V. Gratz; Tushar Krishna (IEEE Micro, 2019)

Kite: A Family of Heterogeneous Interposer Topologies Enabled via Accurate Interconnect Modeling. - Srikant Bharadwaj; Jieming Yin; Bradford M. Beckmann; Tushar Krishna (DAC, 2020)

Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. - Lei Yang 018; Zheyu Yan; Meng Li 004; Hyoukjun Kwon; Liangzhen Lai; Tushar Krishna; Vikas Chandra; Weiwen Jiang; Yiyu Shi 001 (DAC, 2020)

Scalable Distributed Training of Recommendation Models: An ASTRA-SIM + NS3 case-study with TCP/IP transport. - Saeed Rashidi; Pallavi Shurpali; Srinivas Sridharan 002; Naader Hassani; Dheevatsa Mudigere; Krishnakumar Nair; Misha Smelyanskiy; Tushar Krishna (Hot Interconnects, 2020)

ALRESCHA: A Lightweight Reconfigurable Sparse-Computation Accelerator. - Bahar Asgari; Ramyad Hadidi; Tushar Krishna; Hyesoon Kim; Sudhakar Yalamanchili (HPCA, 2020)

DRAIN: Deadlock Removal for Arbitrary Irregular Networks. - Mayank Parasar; Hossein Farrokhbakht; Natalie D. Enright Jerger; Paul V. Gratz; Tushar Krishna; Joshua San Miguel (HPCA, 2020)

SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training. - Eric Qin 001; Ananda Samajdar; Hyoukjun Kwon; Vineet Nadella; Sudarshan Srinivasan; Dipankar Das 002; Bharat Kaul; Tushar Krishna (HPCA, 2020)

GAMMA: Automating the HW Mapping of DNN Models on Accelerators via Genetic Algorithm. - Sheng-Chun Kao; Tushar Krishna (ICCAD, 2020)

CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices. - Parth Mannan; Ananda Samajdar; Tushar Krishna (ISPASS, 2020)

ASTRA-SIM: Enabling SW/HW Co-Design Exploration for Distributed DL Training Platforms. - Saeed Rashidi; Srinivas Sridharan 002; Sudarshan Srinivasan; Tushar Krishna (ISPASS, 2020)

A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim. - Ananda Samajdar; Jan Moritz Joseph; Yuhao Zhu 001; Paul N. Whatmough; Matthew Mattina; Tushar Krishna (ISPASS, 2020)

ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning. - Sheng-Chun Kao; Geonhwa Jeong; Tushar Krishna (MICRO, 2020)

Breaking Barriers: Maximizing Array Utilization for Compute in-Memory Fabrics. - Brian Crafton; Samuel Spetalnick; Gauthaman Murali; Tushar Krishna; Sung Kyu Lim; Arijit Raychowdhury (VLSI-SOC, 2020)

Statistical Array Allocation and Partitioning for Compute In-Memory Fabrics. - Brian Crafton; Samuel Spetalnick; Gauthaman Murali; Tushar Krishna; Sung Kyu Lim; Arijit Raychowdhury (VLSI-SoC (Selected Papers), 2020)

MARVEL: A Decoupled Model-driven Approach for Efficiently Mapping Convolutions on Spatial DNN Accelerators. - Prasanth Chatarasi; Hyoukjun Kwon; Natesh Raina; Saurabh Malik; Vaisakh Haridas; Tushar Krishna; Vivek Sarkar (CoRR, 2020)

Generative Design of Hardware-aware DNNs. - Sheng-Chun Kao; Arun Ramamurthy; Tushar Krishna (CoRR, 2020)

Conditional Neural Architecture Search. - Sheng-Chun Kao; Arun Ramamurthy; Reed Williams; Tushar Krishna (CoRR, 2020)

STONNE: A Detailed Architectural Simulator for Flexible Neural Network Accelerators. - Francisco Muñoz-Martínez; José L. Abellán; Manuel E. Acacio; Tushar Krishna (CoRR, 2020)

Efficient Communication Acceleration for Next-Gen Scale-up Deep Learning Training Platforms. - Saeed Rashidi; Srinivas Sridharan 002; Sudarshan Srinivasan; Matthew Denton; Tushar Krishna (CoRR, 2020)

The gem5 Simulator: Version 20.0+. - Jason Lowe-Power; Abdul Mutaal Ahmad; Ayaz Akram; Mohammad Alian; Rico Amslinger; Matteo Andreozzi; Adrià Armejach; Nils Asmussen; Srikant Bharadwaj; Gabe Black; Gedare Bloom; Bobby R. Bruce; et al. (CoRR, 2020)

Restructuring, Pruning, and Adjustment of Deep Models for Parallel Distributed Inference. - Afshin Abdi; Saeed Rashidi; Faramarz Fekri; Tushar Krishna (CoRR, 2020)

MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings. - Hyoukjun Kwon; Prasanth Chatarasi; Vivek Sarkar; Tushar Krishna; Michael Pellauer; Angshuman Parashar (IEEE Micro, 2020)

ECOTLB: Eventually Consistent TLBs. - Steffen Maass; Mohan Kumar Kumar; Taesoo Kim; Tushar Krishna; Abhishek Bhattacharjee (ACM Trans. Archit. Code Optim., 2020)

Architecture, Chip, and Package Codesign Flow for Interposer-Based 2.5-D Chiplet Integration Enabling Heterogeneous IP Reuse. - Jinwoo Kim; Gauthaman Murali; Heechun Park; Eric Qin 001; Hyoukjun Kwon; Venkata Chaitanya Krishna Chekuri; Nael Mizanur Rahman; Nihar Dasari; Arvind Singh; Minah Lee; Hakki Mert Torun; Kallol Roy; et al. (IEEE Trans. Very Large Scale Integr. Syst., 2020)

Data Orchestration in Deep Learning Accelerators - Tushar Krishna; Hyoukjun Kwon; Angshuman Parashar; Michael Pellauer; Ananda Samajdar (Morgan & Claypool Publishers, 2020)

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. - Geonhwa Jeong; Gokcen Kestor; Prasanth Chatarasi; Angshuman Parashar; Po-An Tsai; Sivasankaran Rajamanickam; Roberto Gioiosa; Tushar Krishna (PACT, 2021)

Dataflow-Architecture Co-Design for 2.5D DNN Accelerators using Wireless Network-on-Package. - Robert Guirado; Hyoukjun Kwon; Sergi Abadal; Eduard Alarcón; Tushar Krishna (ASP-DAC, 2021)

Bridging the Frequency Gap in Heterogeneous 3D SoCs through Technology-Specific NoC Router Architectures. - Jan Moritz Joseph; Lennart Bamberg; Geonhwa Jeong; Ruei-Ting Chien; Rainer Leupers; Alberto García-Ortiz; Tushar Krishna; Thilo Pionteck (ASP-DAC, 2021)

RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU. - Geonhwa Jeong; Eric Qin 001; Ananda Samajdar; Christopher J. Hughes; Sreenivas Subramoney; Hyesoon Kim; Tushar Krishna (DAC, 2021)

Pitstop: Enabling a Virtual Network Free Network-on-Chip. - Hossein Farrokhbakht; Henry Kao; Kamran Hasan; Paul V. Gratz; Tushar Krishna; Joshua San Miguel; Natalie D. Enright Jerger (HPCA, 2021)

Heterogeneous Dataflow Accelerators for Multi-DNN Workloads. - Hyoukjun Kwon; Liangzhen Lai; Michael Pellauer; Tushar Krishna; Yu-Hsin Chen; Vikas Chandra (HPCA, 2021)

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. - Eric Qin 001; Geonhwa Jeong; William Won; Sheng-Chun Kao; Hyoukjun Kwon; Sudarshan Srinivasan; Dipankar Das 002; Gordon Euhyun Moon; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2021)

Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms. - Saeed Rashidi; Matthew Denton; Srinivas Sridharan 002; Sudarshan Srinivasan; Amoghavarsha Suresh; Jade Nie; Tushar Krishna (ISCA, 2021)

E3: A HW/SW Co-design Neuroevolution Platform for Autonomous Learning in Edge Device. - Sheng-Chun Kao; Tushar Krishna (ISPASS, 2021)

Architecture, Dataflow and Physical Design Implications of 3D-ICs for DNN-Accelerators. - Jan Moritz Joseph; Ananda Samajdar; Lingjun Zhu; Rainer Leupers; Sung Kyu Lim; Thilo Pionteck; Tushar Krishna (ISQED, 2021)

Technology-aware Router Architectures for On-Chip-Networks in Heterogeneous Technologies. - Lennart Bamberg; Tushar Krishna; Jan Moritz Joseph (NANOCOM, 2021)

DUB: dynamic underclocking and bypassing in nocs for heterogeneous GPU workloads. - Srikant Bharadwaj; Shomit Das; Yasuko Eckert; Mark Oskin; Tushar Krishna (NOCS, 2021)

A novel network fabric for efficient spatio-temporal reduction in flexible DNN accelerators. - Francisco Muñoz-Martínez; José L. Abellán; Manuel E. Acacio; Tushar Krishna (NOCS, 2021)

SEEC: stochastic escape express channel. - Mayank Parasar; Natalie D. Enright Jerger; Paul V. Gratz; Joshua San Miguel; Tushar Krishna (SC, 2021)

Flexion: A Quantitative Metric for Flexibility in DNN Accelerators. - Hyoukjun Kwon; Michael Pellauer; Angshuman Parashar; Tushar Krishna (IEEE Comput. Archit. Lett., 2021)

STONNE: Enabling Cycle-Level Microarchitectural Simulation for DNN Inference Accelerators. - Francisco Muñoz-Martínez; José L. Abellán; Manuel E. Acacio; Tushar Krishna (IEEE Comput. Archit. Lett., 2021)

Self-Adaptive Reconfigurable Arrays (SARA): Using ML to Assist Scaling GEMM Acceleration. - Ananda Samajdar; Michael Pellauer; Tushar Krishna (CoRR, 2021)

A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators. - Raveesh Garg; Eric Qin 001; Francisco Muñoz-Martínez; Robert Guirado; Akshay Jain 001; Sergi Abadal; José L. Abellán; Manuel E. Acacio; Eduard Alarcón; Sivasankaran Rajamanickam; Tushar Krishna (CoRR, 2021)

Domain-specific Genetic Algorithm for Multi-tenant DNNAccelerator Scheduling. - Sheng-Chun Kao; Tushar Krishna (CoRR, 2021)

ATTACC the Quadratic Bottleneck of Attention Layers. - Sheng-Chun Kao; Suvinay Subramanian; Gaurav Agrawal; Tushar Krishna (CoRR, 2021)

AIRCHITECT: Learning Custom Architecture Design and Mapping Space. - Ananda Samajdar; Jan Moritz Joseph; Matthew Denton; Tushar Krishna (CoRR, 2021)

Exploring Multi-dimensional Hierarchical Network Topologies for Efficient Distributed Training of Trillion Parameter DL Models. - William Won; Saeed Rashidi; Sudarshan Srinivasan; Tushar Krishna (CoRR, 2021)

Efficiently Solving Partial Differential Equations in a Partially Reconfigurable Specialized Hardware. - Bahar Asgari; Ramyad Hadidi; Tushar Krishna; Hyesoon Kim; Sudhakar Yalamanchili (IEEE Trans. Computers, 2021)

Clock Delivery Network Design and Analysis for Interposer-Based 2.5-D Heterogeneous Systems. - Gauthaman Murali; Heechun Park; Eric Qin 001; Hakki Mert Torun; Majid Ahadi Dolatsara; Madhavan Swaminathan; Tushar Krishna; Sung Kyu Lim (IEEE Trans. Very Large Scale Integr. Syst., 2021)

Self adaptive reconfigurable arrays (SARA): learning flexible GEMM accelerator configuration and mapping-space using ML. - Ananda Samajdar; Eric Qin 001; Michael Pellauer; Tushar Krishna (DAC, 2022)

DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. - Sheng-Chun Kao; Michael Pellauer; Angshuman Parashar; Tushar Krishna (DATE, 2022)

Impact of RoCE Congestion Control Policies on Distributed Training of DNNs. - Tarannum Khan; Saeed Rashidi; Srinivas Sridharan 002; Pallavi Shurpali; Aditya Akella; Tushar Krishna (HOTI, 2022)

Stay in your Lane: A NoC with Low-overhead Multi-packet Bypassing. - Hossein Farrokhbakht; Paul V. Gratz; Tushar Krishna; Joshua San Miguel; Natalie D. Enright Jerger (HPCA, 2022)

MAGMA: An Optimization Framework for Mapping Multiple DNNs on Multiple Accelerator Cores. - Sheng-Chun Kao; Tushar Krishna (HPCA, 2022)

Demystifying Map Space Exploration for NPUs. - Sheng-Chun Kao; Angshuman Parashar; Po-An Tsai; Tushar Krishna (IISWC, 2022)

Understanding the Design-Space of Sparse/Dense Multiphase GNN dataflows on Spatial Accelerators. - Raveesh Garg; Eric Qin 001; Francisco Muñoz-Martínez; Robert Guirado; Akshay Jain 001; Sergi Abadal; José L. Abellán; Manuel E. Acacio; Eduard Alarcón; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2022)

Themis: a network bandwidth-aware collective scheduling policy for distributed training of DL models. - Saeed Rashidi; William Won; Sudarshan Srinivasan; Srinivas Sridharan 002; Tushar Krishna (ISCA, 2022)

Understanding Data Compression in Warehouse-Scale Datacenter Services. - Geonhwa Jeong; Bikash Sharma; Nick Terrell; Abhishek Dhanotia; Zhiwei Zhao; Niket Agarwal; Arun Kejariwal; Tushar Krishna (ISPASS, 2022)

MicroEdge: a multi-tenant edge cluster system architecture for scalable camera processing. - Difei Cao; Jinsun Yoo; Zhuangdi Xu; Enrique Saurez; Harshit Gupta; Tushar Krishna; Umakishore Ramachandran (Middleware, 2022)

Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity. - Eric Qin 001; Raveesh Garg; Abhimanyu Bambhaniya; Michael Pellauer; Angshuman Parashar; Sivasankaran Rajamanickam; Cong Hao; Tushar Krishna (CoRR, 2022)

DNNFuser: Generative Pre-Trained Transformer as a Generalized Mapper for Layer Fusion in DNN Accelerators. - Sheng-Chun Kao; Xiaoyu Huang; Tushar Krishna (CoRR, 2022)

Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask. - Sheng-Chun Kao; Amir Yazdanbakhsh; Suvinay Subramanian; Shivani Agrawal; Utku Evci; Tushar Krishna (CoRR, 2022)

COMET: A Comprehensive Cluster Design Methodology for Distributed Deep Learning Training. - Divya Kiran Kadiyala; Saeed Rashidi; Taekyung Heo; Abhimanyu Rajeshkumar Bambhaniya; Tushar Krishna; Alexandros Daglis (CoRR, 2022)

A Formalism of DNN Accelerator Flexibility. - Sheng-Chun Kao; Hyoukjun Kwon; Michael Pellauer; Angshuman Parashar; Tushar Krishna (Proc. ACM Meas. Anal. Comput. Syst., 2022)

Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators. - Prasanth Chatarasi; Hyoukjun Kwon; Angshuman Parashar; Michael Pellauer; Tushar Krishna; Vivek Sarkar (ACM Trans. Archit. Code Optim., 2022)

Guest Editorial: IEEE TC Special Issue: Hardware Acceleration of Machine Learning. - Michael Ferdman; Jorge Albericio; Tushar Krishna; Peter A. Milder (IEEE Trans. Computers, 2022)

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. - Gordon Euhyun Moon; Hyoukjun Kwon; Geonhwa Jeong; Prasanth Chatarasi; Sivasankaran Rajamanickam; Tushar Krishna (IEEE Trans. Parallel Distributed Syst., 2022)

Efficient Distributed Inference of Deep Neural Networks via Restructuring and Pruning. - Afshin Abdi; Saeed Rashidi; Faramarz Fekri; Tushar Krishna (AAAI, 2023)

FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks. - Sheng-Chun Kao; Suvinay Subramanian; Gaurav Agrawal; Amir Yazdanbakhsh; Tushar Krishna (ASPLOS (2), 2023)

Flexagon: A Multi-dataflow Sparse-Sparse Matrix Multiplication Accelerator for Efficient DNN Processing. - Francisco Muñoz-Martínez; Raveesh Garg; Michael Pellauer; José L. Abellán; Manuel E. Acacio; Tushar Krishna (ASPLOS (3), 2023)

Proteus : HLS-based NoC Generator and Simulator. - Abhimanyu Rajeshkumar Bambhaniya; Yangyu Chen; Anshuman; Rohan Banerjee; Tushar Krishna (DATE, 2023)

AIrchitect: Automating Hardware Architecture and Mapping Optimization. - Ananda Samajdar; Jan Moritz Joseph; Tushar Krishna (DATE, 2023)

VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs. - Geonhwa Jeong; Sana Damani; Abhimanyu Rajeshkumar Bambhaniya; Eric Qin 001; Christopher J. Hughes; Sreenivas Subramoney; Hyesoon Kim; Tushar Krishna (HPCA, 2023)

SNATCH: Stealing Neural Network Architecture from ML Accelerator in Intelligent Sensors. - Sudarshan Sharma; Uday Kamal; Jianming Tong; Tushar Krishna; Saibal Mukhopadhyay (SENSORS, 2023)

Characterization of Data Compression in Datacenters. - Geonhwa Jeong; Bikash Sharma; Nick Terrell; Abhishek Dhanotia; Zhiwei Zhao; Niket Agarwal; Arun Kejariwal; Tushar Krishna (ISPASS, 2023)

ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale. - William Won; Taekyung Heo; Saeed Rashidi; Srinivas Sridharan 002; Sudarshan Srinivasan; Tushar Krishna (ISPASS, 2023)

Subgraph Stationary Hardware-Software Inference Co-Design. - Payman Behnam; Alexey Tumanov; Tushar Krishna; Pranav Gadikar; Yangyu Chen; Jianming Tong; Yue Pan; Abhimanyu Rajeshkumar Bambhaniya; Alind Khare (MLSys, 2023)

XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. - Hyoukjun Kwon; Krishnakumar Nair; Jamin Seo; Jason Yik; Debabrata Mohapatra; Dongyuan Zhan; Jinook Song; Peter Capak; Peizhao Zhang; Peter Vajda; Colby R. Banbury; Mark Mazumder; et al. (MLSys, 2023)

Mitigating Timing-Based NoC Side-Channel Attacks With LLC Remapping. - Anurag Kar; Xueyang Liu; Yonghae Kim; Gururaj Saileshwar; Hyesoon Kim; Tushar Krishna (IEEE Comput. Archit. Lett., 2023)

Exploiting Inter-Operation Data Reuse in Scientific Applications using GOGETA. - Raveesh Garg; Michael Pellauer; Sivasankaran Rajamanickam; Tushar Krishna (CoRR, 2023)

Perspectives on AI Architectures and Co-design for Earth System Predictability. - Maruti K. Mudunuru; James A. Ang; Mahantesh Halappanavar; Simon D. Hammond; Maya B. Gokhale; James C. Hoe; Tushar Krishna; Sarat Sreepathi; Matthew R. Norman; Ivy Bo Peng; Philip W. Jones (CoRR, 2023)

TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training. - William Won; Midhilesh Elavazhagan; Sudarshan Srinivasan; Ajaya Durg; Swati Gupta 001; Tushar Krishna (CoRR, 2023)

Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces. - Srinivas Sridharan 002; Taekyung Heo; Louis Feng; Zhaodong Wang; Matt Bergeron; Wenyin Fu; Shengbao Zheng; Brian Coutinho; Saeed Rashidi; Changhai Man; Tushar Krishna (CoRR, 2023)

Hardware-Software Co-Design for Real-Time Latency-Accuracy Navigation in Tiny Machine Learning Applications. - Payman Behnam; Jianming Tong; Alind Khare; Yangyu Chen; Yue Pan; Pranav Gadikar; Abhimanyu Bambhaniya; Tushar Krishna; Alexey Tumanov (IEEE Micro, 2023)

TNT: A Modular Approach to Traversing Physically Heterogeneous NOCs at Bare-wire Latency. - Gokul Subramanian Ravi; Tushar Krishna; Mikko H. Lipasti (ACM Trans. Archit. Code Optim., 2023)

Introduction to the Special Issue on Next-Generation On-Chip and Off-Chip Communication Architectures for Edge, Cloud and HPC. - John Kim 001; Tushar Krishna (ACM J. Emerg. Technol. Comput. Syst., 2023)

STIFT: A Spatio-Temporal Integrated Folding Tree for Efficient Reductions in Flexible DNN Accelerators. - Francisco Muñoz-Martínez; José L. Abellán; Manuel E. Acacio; Tushar Krishna (ACM J. Emerg. Technol. Comput. Syst., 2023)

On Continuing DNN Accelerator Architecture Scaling Using Tightly Coupled Compute-on-Memory 3-D ICs. - Gauthaman Murali; Aditya Iyer 001; Lingjun Zhu; Jianming Tong; Francisco Muñoz-Martínez; Srivatsa Rangachar Srinivasa; Tanay Karnik; Tushar Krishna; Sung Kyu Lim (IEEE Trans. Very Large Scale Integr. Syst., 2023)

SPOCK: Reverse Packet Traversal for Deadlock Recovery. - Zeyu Chen; Ankur Bindal; Vaidehi Garg; Tushar Krishna (IEEE Des. Test, 2023)

Special Session: Neuro-Symbolic Architecture Meets Large Language Models: A Memory-Centric Perspective. - Mohamed Ibrahim 002; Zishen Wan; Haitong Li; Priyadarshini Panda; Tushar Krishna; Pentti Kanerva; Yiran Chen 001; Arijit Raychowdhury (CODES+ISSS, 2024)

Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference. - Akshat Ramachandran; Zishen Wan; Geonhwa Jeong; John Gustafson; Tushar Krishna (DAC, 2024)

H3DFact: Heterogeneous 3D Integrated CIM for Factorization with Holographic Perceptual Representations. - Zishen Wan; Che-Kai Liu; Mohamed Ibrahim 002; Hanchen Yang; Samuel Spetalnick; Tushar Krishna; Arijit Raychowdhury (DATE, 2024)

CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-training Quantization of ViTs. - Akshat Ramachandran; Souvik Kundu 002; Tushar Krishna (ECCV (67), 2024)

GEAR: An Efficient Error Reduction Framework for KV Cache Compression in LLM Inference. - Hao Kang; Qingru Zhang; Souvik Kundu 009; Geonhwa Jeong; Zaoxing Liu; Tushar Krishna; Tuo Zhao (ENLSP, 2024)

Towards a Standardized Representation for Deep Learning Collective Algorithms. - Jinsun Yoo; William Won; Meghan Cowan; Nan Jiang; Benjamin Klenk; Srinivas Sridharan 002; Tushar Krishna (HOTI, 2024)

Thinking and Moving: An Efficient Computing Approach for Integrated Task and Motion Planning in Cooperative Embodied AI Systems. - Zishen Wan; Yuhang Du; Mohamed Ibrahim 002; Yang (Katie) Zhao; Tushar Krishna; Arijit Raychowdhury (ICCAD, 2024)

Understanding Performance Implications of LLM Inference on CPUs. - Seonjin Na; Geonhwa Jeong; Byung Hoon Ahn; Jeffrey Young 001; Tushar Krishna; Hyesoon Kim (IISWC, 2024)

FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching. - Jianming Tong; Anirudh Itagi; Prasanth Chatarasi; Tushar Krishna (ISCA, 2024)

Leveraging Memory Expansion to Accelerate Large-Scale DL Training. - Divya Kiran Kadiyala; Saeed Rashidi; Taekyung Heo; Abhimanyu Bambhaniya; Tushar Krishna; Alexandros Daglis (ISPASS, 2024)

Towards Cognitive AI Systems: Workload and Characterization of Neuro-Symbolic AI. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Ritik Raj; Chaojian Li; Haoran You; Yonggan Fu; Cheng Wan 005; Ananda Samajdar; Yingyan Celine Lin; Tushar Krishna; Arijit Raychowdhury (ISPASS, 2024)

LIBRA: Enabling Workload-Aware Multi-Dimensional Network Topology Optimization for Distributed Training of Large AI Models. - William Won; Saeed Rashidi; Sudarshan Srinivasan; Tushar Krishna (ISPASS, 2024)

TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Machine Learning. - William Won; Midhilesh Elavazhagan; Sudarshan Srinivasan; Swati Gupta 001; Tushar Krishna (MICRO, 2024)

Accurate Low-Degree Polynomial Approximation of Non-Polynomial Operators for Fast Private Inference in Homomorphic Encryption. - Jingtian Dang; Jianming Tong; Anupam Golder; Cong Hao; Arijit Raychowdhury; Tushar Krishna (MLSys, 2024)

Enhancing Scalability and Performance in Influence Maximization with Optimized Parallel Processing. - Hanjiang Wu; Huan Xu; Joongun Park; Jesmin Jahan Tithi; Fabio Checconi; Jordi Wolfson-Pou; Fabrizio Petrini; Tushar Krishna (SC Workshops, 2024)

Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Chaojian Li; Haoran You; Yonggan Fu; Cheng Wan 005; Tushar Krishna; Yingyan Lin; Arijit Raychowdhury (CoRR, 2024)

Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers. - Abhimanyu Rajeshkumar Bambhaniya; Amir Yazdanbakhsh; Suvinay Subramanian; Sheng-Chun Kao; Shivani Agrawal; Utku Evci; Tushar Krishna (CoRR, 2024)

GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. - Hao Kang; Qingru Zhang; Souvik Kundu 009; Geonhwa Jeong; Zaoxing Liu; Tushar Krishna; Tuo Zhao (CoRR, 2024)

Abstracting Sparse DNN Acceleration via Structured Sparse Tensor Decomposition. - Geonhwa Jeong; Po-An Tsai; Abhimanyu Rajeshkumar Bambhaniya; Stephen W. Keckler; Tushar Krishna (CoRR, 2024)

Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption. - Jianming Tong; Jingtian Dang; Anupam Golder; Callie Hao; Arijit Raychowdhury; Tushar Krishna (CoRR, 2024)

PipeOrgan: Efficient Inter-operation Pipelining with Flexible Spatial Organization and Interconnects. - Raveesh Garg; Hyoukjun Kwon; Eric Qin 001; Yu-Hsin Chen; Tushar Krishna; Liangzhen Lai (CoRR, 2024)

Demystifying Platform Requirements for Diverse LLM Inference Use Cases. - Abhimanyu Bambhaniya; Ritik Raj; Geonhwa Jeong; Souvik Kundu 009; Sudarshan Srinivasan; Midhilesh Elavazhagan; Madhu Kumar; Tushar Krishna (CoRR, 2024)

SDQ: Sparse Decomposed Quantization for LLM Inference. - Geonhwa Jeong; Po-An Tsai; Stephen W. Keckler; Tushar Krishna (CoRR, 2024)

FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Models. - Saeed Rashidi; William Won; Sudarshan Srinivasan; Puneet Gupta 001; Tushar Krishna (CoRR, 2024)

CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs. - Akshat Ramachandran; Souvik Kundu 009; Tushar Krishna (CoRR, 2024)

Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Ritik Raj; Chaojian Li; Haoran You; Yonggan Fu; Cheng Wan 005; Sixu Li; Youbin Kim; Ananda Samajdar; Yingyan Celine Lin; et al. (CoRR, 2024)

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. - Mufei Li; Viraj Shitole; Eli Chien; Changhai Man; Zhaodong Wang; Srinivas Sridharan 002; Ying Zhang; Tushar Krishna; Pan Li 005 (CoRR, 2024)

AI Metropolis: Scaling Large Language Model-based Multi-Agent Simulation with Out-of-order Execution. - Zhiqiang Xie; Hao Kang; Ying Sheng 007; Tushar Krishna; Kayvon Fatahalian; Christos Kozyrakis (CoRR, 2024)

TurboAttention: Efficient Attention Approximation For High Throughputs LLMs. - Hao Kang; Srikant Bharadwaj; James Hensman; Tushar Krishna; Victor Rühle; Saravan Rajmohan (CoRR, 2024)

Remembering Arvind. - Tushar Krishna (IEEE Des. Test, 2024)

ReCA: Integrated Acceleration for Real-Time and Efficient Cooperative Embodied Autonomous Agents. - Zishen Wan; Yuhang Du; Mohamed Ibrahim 002; Jiayi Qian; Jason Jabbour; Yang (Katie) Zhao; Tushar Krishna; Arijit Raychowdhury; Vijay Janapa Reddi (ASPLOS (2), 2025)

Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers. - Abhimanyu Rajeshkumar Bambhaniya; Amir Yazdanbakhsh; Suvinay Subramanian; Sheng-Chun Kao; Shivani Agrawal; Utku Evci; Tushar Krishna (CPAL, 2025)

Axon: A Novel Systolic Array Architecture for Improved Run Time and Energy Efficient GeMM and Conv Operation with On-Chip im2col. - Md Mizanur Rahaman Nayan; Ritik Raj; Shaik Gouse Basha; Tushar Krishna; Azad J. Naeemi (DATE, 2025)

AIRCHITECT v2: Learning the Hardware Accelerator Design Space Through Unified Representations. - Jamin Seo; Akshat Ramachandran; Yu-Chuan Chuang; Anirudh Itagi; Tushar Krishna (DATE, 2025)

CogSys: Efficient and Scalable Neurosymbolic Cognition System via Algorithm-Hardware Co-Design. - Zishen Wan; Hanchen Yang; Ritik Raj; Che-Kai Liu; Ananda Samajdar; Arijit Raychowdhury; Tushar Krishna (HPCA, 2025)

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. - Mufei Li; Viraj Shitole; Eli Chien; Changhai Man; Zhaodong Wang; Srinivas; Ying Zhang; Tushar Krishna; Pan Li 005 (ICLR, 2025)

Cello: Co-Designing Schedule and Hybrid Implicit/Explicit Buffer for Complex Tensor Reuse. - Raveesh Garg; Michael Pellauer; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2025)

MicroScopiQ: Accelerating Foundational Models through Outlier-Aware Microscaling Quantization. - Akshat Ramachandran; Souvik Kundu 009; Tushar Krishna (ISCA, 2025)

FRED: A Wafer-scale Fabric for 3D Parallel DNN Training. - Saeed Rashidi; William Won; Sudarshan Srinivasan; Puneet Gupta 001; Tushar Krishna (ISCA, 2025)

Optimizing Sparse/Dense VEGETA Accelerator Performance with Microscaling Quantization. - Kazi Barria Nine; Connor Talley; Ajay Sharma Mandadi; Tushar Krishna; Arijit Raychowdhury (ISCAS, 2025)

SCALE-Sim V3: a Modular Cycle-Accurate Systolic Accelerator Simulator for End-To-End System Analysis. - Ritik Raj; Sarbartha Banerjee; Nikhil Chandra; Zishen Wan; Jianming Tong; Ananda Samajdhar; Tushar Krishna (ISPASS, 2025)

Exploring Constrained Dataflow Accelerators for Real-Time Multi-Task Multi-Model Ml Workloads. - Jamin Seo; Jianming Tong; Tushar Krishna; Hyoukjun Kwon (ISPASS, 2025)

Generative AI in Embodied Systems: System-Level Analysis of Performance, Efficiency and Scalability. - Zishen Wan; Jiayi Qian; Yuhang Du; Jason Jabbour; Yilun Du; Yang Zhao 013; Arijit Raychowdhury; Tushar Krishna; Vijay Janapa Reddi (ISPASS, 2025)

Efficient Processing of Neuro-Symbolic AI: A Tutorial and Cross-Layer Co-Design Case Study. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Ritik Raj; Arijit Raychowdhury; Tushar Krishna (NeuS, 2025)

Toward a Standardized Representation for Deep Learning Collective Algorithms. - Jinsun Yoo; William Won; Meghan Cowan; Nan Jiang; Benjamin Klenk; Srinivas Sridharan 002; Tushar Krishna (IEEE Micro, 2025)

Leveraging ASIC AI Chips for Homomorphic Encryption. - Jianming Tong; Tianhao Huang; Leo de Castro; Anirudh Itagi; Jingtian Dang; Anupam Golder; Asra Ali; Jevin Jiang; Arvind 001; G. Edward Suh; Tushar Krishna (CoRR, 2025)

HARP: A Taxonomy for Heterogeneous and Hierarchical Processors for Mixed-reuse Workloads. - Raveesh Garg; Michael Pellauer; Tushar Krishna (CoRR, 2025)

OuroMamba: A Data-Free Quantization Framework for Vision Mamba Models. - Akshat Ramachandran; Mingyu Lee; Huan Xu; Souvik Kundu 009; Tushar Krishna (CoRR, 2025)

Understanding and Optimizing Multi-Stage AI Inference Pipelines. - Abhimanyu Rajeshkumar Bambhaniya; Hanjiang Wu; Suvinay Subramanian; Sudarshan Srinivasan; Souvik Kundu 009; Amir Yazdanbakhsh; Midhilesh Elavazhagan; Madhu Kumar; Tushar Krishna (CoRR, 2025)

Accelerating LLM Inference with Flexible N:M Sparsity via A Fully Digital Compute-in-Memory Accelerator. - Akshat Ramachandran; Souvik Kundu 009; Arnab Raha; Shamik Kundu; Deepak A. Mathaikutty; Tushar Krishna (CoRR, 2025)

NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI. - Hanchen Yang; Zishen Wan; Ritik Raj; Joongun Park; Ziwei Li; Ananda Samajdar; Arijit Raychowdhury; Tushar Krishna (CoRR, 2025)

Towards Easy and Realistic Network Infrastructure Testing for Large-scale Machine Learning. - Jinsun Yoo; ChonLam Lao; Lianjie Cao; Bob Lantz; Minlan Yu; Tushar Krishna; Puneet Sharma (CoRR, 2025)

MCMComm: Hardware-Software Co-Optimization for End-to-End Communication in Multi-Chip-Modules. - Ritik Raj; Shengjie Lin; William Won; Tushar Krishna (CoRR, 2025)

OneDSE: A Unified Microprocessor Metric Prediction and Design Space Exploration Framework. - Ritik Raj; Akshat Ramachandran; Jeff Nye; Shashank Nemawarkar; Tushar Krishna (CoRR, 2025)

COSMIC: Enabling Full-Stack Co-Design and Optimization of Distributed Machine Learning Systems. - Aditi Raju; Jared Ni; William Won; Changhai Man; Srivatsan Krishnan; Srinivas Sridharan 002; Amir Yazdanbakhsh; Tushar Krishna; Vijay Janapa Reddi (CoRR, 2025)

Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs. - Hao Kang; Qingru Zhang; Han Cai; Weiyuan Xu; Tushar Krishna; Yilun Du; Tsachy Weissman (CoRR, 2025)

Cross-Layer Design of Vector-Symbolic Computing: Bridging Cognition and Brain-Inspired Hardware Acceleration. - Shuting Du; Mohamed Ibrahim 002; Zishen Wan; Luqi Zheng; Boheng Zhao; Zhenkun Fan; Che-Kai Liu; Tushar Krishna; Arijit Raychowdhury; Haitong Li (CoRR, 2025)