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Books and Theses
- 2020
[b3]Tushar Krishna, Hyoukjun Kwon
, Angshuman Parashar, Michael Pellauer, Ananda Samajdar:
Data Orchestration in Deep Learning Accelerators. Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2020, ISBN 978-3-031-00639-5- 2017
- [b2]Natalie D. Enright Jerger, Tushar Krishna, Li-Shiuan Peh:
On-Chip Networks, Second Edition. Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2017, ISBN 978-3-031-00627-2 - 2014
- [b1]Tushar Krishna:
Enabling dedicated single-cycle connections over a shared network-on-chip. Massachusetts Institute of Technology, Cambridge, MA, USA, 2014
Journal Articles
- 2024
- [j28]Tushar Krishna:
Remembering Arvind. IEEE Des. Test 41(6): 101-102 (2024) - 2023
- [j27]Anurag Kar, Xueyang Liu, Yonghae Kim, Gururaj Saileshwar, Hyesoon Kim, Tushar Krishna:
Mitigating Timing-Based NoC Side-Channel Attacks With LLC Remapping. IEEE Comput. Archit. Lett. 22(1): 53-56 (2023) - [j26]Zeyu Chen, Ankur Bindal, Vaidehi Garg, Tushar Krishna:
SPOCK: Reverse Packet Traversal for Deadlock Recovery. IEEE Des. Test 40(6): 86-99 (2023) - [j25]John Kim, Tushar Krishna:
Introduction to the Special Issue on Next-Generation On-Chip and Off-Chip Communication Architectures for Edge, Cloud and HPC. ACM J. Emerg. Technol. Comput. Syst. 19(4): 31:1 (2023) - [j24]Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio, Tushar Krishna:
STIFT: A Spatio-Temporal Integrated Folding Tree for Efficient Reductions in Flexible DNN Accelerators. ACM J. Emerg. Technol. Comput. Syst. 19(4): 32:1-32:20 (2023) - [j23]Payman Behnam, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Bambhaniya, Tushar Krishna, Alexey Tumanov:
Hardware-Software Co-Design for Real-Time Latency-Accuracy Navigation in Tiny Machine Learning Applications. IEEE Micro 43(6): 93-101 (2023) - [j22]Gokul Subramanian Ravi, Tushar Krishna, Mikko H. Lipasti:
TNT: A Modular Approach to Traversing Physically Heterogeneous NOCs at Bare-wire Latency. ACM Trans. Archit. Code Optim. 20(3): 35:1-35:25 (2023) - [j21]Gauthaman Murali, Aditya Iyer, Lingjun Zhu, Jianming Tong, Francisco Muñoz-Martínez, Srivatsa Rangachar Srinivasa, Tanay Karnik, Tushar Krishna, Sung Kyu Lim:
On Continuing DNN Accelerator Architecture Scaling Using Tightly Coupled Compute-on-Memory 3-D ICs. IEEE Trans. Very Large Scale Integr. Syst. 31(10): 1603-1613 (2023) - 2022
- [j20]Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna:
A Formalism of DNN Accelerator Flexibility. Proc. ACM Meas. Anal. Comput. Syst. 6(2): 41:1-41:23 (2022) - [j19]Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar:
Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators. ACM Trans. Archit. Code Optim. 19(1): 6:1-6:26 (2022) - [j18]Michael Ferdman, Jorge Albericio, Tushar Krishna, Peter A. Milder:
Guest Editorial: IEEE TC Special Issue: Hardware Acceleration of Machine Learning. IEEE Trans. Computers 71(12): 3072-3073 (2022) - [j17]Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna:
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. IEEE Trans. Parallel Distributed Syst. 33(4): 1002-1014 (2022) - 2021
- [j16]Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna:
Flexion: A Quantitative Metric for Flexibility in DNN Accelerators. IEEE Comput. Archit. Lett. 20(1): 1-4 (2021) - [j15]Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio, Tushar Krishna:
STONNE: Enabling Cycle-Level Microarchitectural Simulation for DNN Inference Accelerators. IEEE Comput. Archit. Lett. 20(2): 122-125 (2021) - [j14]Bahar Asgari, Ramyad Hadidi, Tushar Krishna, Hyesoon Kim, Sudhakar Yalamanchili:
Efficiently Solving Partial Differential Equations in a Partially Reconfigurable Specialized Hardware. IEEE Trans. Computers 70(4): 524-538 (2021) - [j13]Gauthaman Murali, Heechun Park, Eric Qin, Hakki Mert Torun, Majid Ahadi Dolatsara, Madhavan Swaminathan, Tushar Krishna, Sung Kyu Lim:
Clock Delivery Network Design and Analysis for Interposer-Based 2.5-D Heterogeneous Systems. IEEE Trans. Very Large Scale Integr. Syst. 29(4): 605-616 (2021) - 2020
- [j12]Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar:
MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings. IEEE Micro 40(3): 20-29 (2020) - [j11]Steffen Maass, Mohan Kumar Kumar, Taesoo Kim, Tushar Krishna, Abhishek Bhattacharjee:
ECOTLB: Eventually Consistent TLBs. ACM Trans. Archit. Code Optim. 17(4): 27:1-27:24 (2020) - [j10]Jinwoo Kim, Gauthaman Murali, Heechun Park, Eric Qin, Hyoukjun Kwon, Venkata Chaitanya Krishna Chekuri, Nael Mizanur Rahman, Nihar Dasari, Arvind Singh, Minah Lee, Hakki Mert Torun, Kallol Roy, Madhavan Swaminathan, Saibal Mukhopadhyay, Tushar Krishna, Sung Kyu Lim:
Architecture, Chip, and Package Codesign Flow for Interposer-Based 2.5-D Chiplet Integration Enabling Heterogeneous IP Reuse. IEEE Trans. Very Large Scale Integr. Syst. 28(11): 2424-2437 (2020) - 2019
- [j9]Aniruddh Ramrakhyani, Paul V. Gratz, Tushar Krishna:
Synchronized Progress in Interconnection Networks (SPIN): A New Theory for Deadlock Freedom. IEEE Micro 39(3): 110-117 (2019) - 2018
- [j8]Hyoukjun Kwon, Ananda Samajdar, Tushar Krishna:
A Communication-Centric Approach for Designing Flexible DNN Accelerators. IEEE Micro 38(6): 25-35 (2018) - 2017
- [j7]Yu-Hsin Chen, Tushar Krishna, Joel S. Emer, Vivienne Sze:
Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks. IEEE J. Solid State Circuits 52(1): 127-138 (2017) - 2015
- [j6]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, Vladimir Pavlov, Rachid Rayess, Antonia Zhai, Joel S. Emer:
Efficient Control and Communication Paradigms for Coarse-Grained Spatial Architectures. ACM Trans. Comput. Syst. 33(3): 10:1-10:32 (2015) - 2014
- [j5]Tushar Krishna, Chia-Hsin Owen Chen, Woo-Cheol Kwon, Li-Shiuan Peh:
Smart: Single-Cycle Multihop Traversals over a Shared Network on Chip. IEEE Micro 34(3): 43-56 (2014) - 2013
- [j4]Tushar Krishna, Chia-Hsin Owen Chen, Sunghyun Park, Woo-Cheol Kwon, Suvinay Subramanian, Anantha P. Chandrakasan, Li-Shiuan Peh:
Single-Cycle Multihop Asynchronous Repeated Traversal: A SMART Future for Reconfigurable On-Chip Networks. Computer 46(10): 48-55 (2013) - [j3]Jacob Postman, Tushar Krishna, Christopher Edmonds, Li-Shiuan Peh, Patrick Chiang:
SWIFT: A Low-Power Network-On-Chip Implementing the Token Flow Control Router Architecture With Swing-Reduced Interconnects. IEEE Trans. Very Large Scale Integr. Syst. 21(8): 1432-1446 (2013) - 2011
- [j2]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, Muhammad Shoaib Bin Altaf, Nilay Vaish, Mark D. Hill, David A. Wood:
The gem5 simulator. SIGARCH Comput. Archit. News 39(2): 1-7 (2011) - 2009
- [j1]Tushar Krishna, Amit Kumar, Li-Shiuan Peh, Jacob Postman, Patrick Chiang, Mattan Erez:
Express Virtual Channels with Capacitively Driven Global Links. IEEE Micro 29(4): 48-61 (2009)
Conference and Workshop Papers
- 2024
- [c104]Akshat Ramachandran, Zishen Wan, Geonhwa Jeong, John Gustafson, Tushar Krishna:
Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference. DAC 2024: 326:1-326:6 - [c103]Zishen Wan, Che-Kai Liu, Mohamed Ibrahim, Hanchen Yang, Samuel Spetalnick, Tushar Krishna, Arijit Raychowdhury:
H3DFact: Heterogeneous 3D Integrated CIM for Factorization with Holographic Perceptual Representations. DATE 2024: 1-6 - [c102]Jinsun Yoo, William Won, Meghan Cowan, Nan Jiang, Benjamin Klenk, Srinivas Sridharan, Tushar Krishna:
Towards a Standardized Representation for Deep Learning Collective Algorithms. HOTI 2024: 33-36 - [c101]Jianming Tong, Anirudh Itagi, Prasanth Chatarasi, Tushar Krishna:
FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching. ISCA 2024: 198-214 - [c100]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: 205-216 - [c99]Zishen Wan, Che-Kai Liu, Hanchen Yang, Ritik Raj, Chaojian Li, Haoran You, Yonggan Fu, Cheng Wan, Ananda Samajdar, Yingyan Celine Lin, Tushar Krishna, Arijit Raychowdhury:
Towards Cognitive AI Systems: Workload and Characterization of Neuro-Symbolic AI. ISPASS 2024: 268-279 - [c98]Divya Kiran Kadiyala, Saeed Rashidi, Taekyung Heo, Abhimanyu Bambhaniya, Tushar Krishna, Alexandros Daglis:
Leveraging Memory Expansion to Accelerate Large-Scale DL Training. ISPASS 2024: 292-294 - [c97]Jingtian Dang, Jianming Tong, Anupam Golder, Cong Hao, Arijit Raychowdhury, Tushar Krishna:
Accurate Low-Degree Polynomial Approximation of Non-Polynomial Operators for Fast Private Inference in Homomorphic Encryption. MLSys 2024 - 2023
- [c96]Afshin Abdi, Saeed Rashidi, Faramarz Fekri, Tushar Krishna:
Efficient Distributed Inference of Deep Neural Networks via Restructuring and Pruning. AAAI 2023: 6640-6648 - [c95]Francisco Muñoz-Martínez, Raveesh Garg, Michael Pellauer, José L. Abellán, Manuel E. Acacio, Tushar Krishna:
Flexagon: A Multi-dataflow Sparse-Sparse Matrix Multiplication Accelerator for Efficient DNN Processing. ASPLOS (3) 2023: 252-265 - [c94]Sheng-Chun Kao, Suvinay Subramanian, Gaurav Agrawal, Amir Yazdanbakhsh, Tushar Krishna:
FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks. ASPLOS (2) 2023: 295-310 - [c93]Abhimanyu Rajeshkumar Bambhaniya, Yangyu Chen, Anshuman, Rohan Banerjee, Tushar Krishna:
Proteus : HLS-based NoC Generator and Simulator. DATE 2023: 1-6 - [c92]Ananda Samajdar, Jan Moritz Joseph, Tushar Krishna:
AIrchitect: Automating Hardware Architecture and Mapping Optimization. DATE 2023: 1-6 - [c91]Geonhwa Jeong, Sana Damani, Abhimanyu Rajeshkumar Bambhaniya, Eric Qin, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna:
VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs. HPCA 2023: 259-272 - [c90]Sudarshan Sharma, Uday Kamal, Jianming Tong, Tushar Krishna, Saibal Mukhopadhyay:
SNATCH: Stealing Neural Network Architecture from ML Accelerator in Intelligent Sensors. SENSORS 2023: 1-4 - [c89]Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna:
Characterization of Data Compression in Datacenters. ISPASS 2023: 1-12 - [c88]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: 283-294 - [c87]Payman Behnam, Alexey Tumanov, Tushar Krishna, Pranav Gadikar, Yangyu Chen, Jianming Tong, Yue Pan, Abhimanyu Rajeshkumar Bambhaniya, Alind Khare:
Subgraph Stationary Hardware-Software Inference Co-Design. MLSys 2023 - [c86]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, Liangzhen Lai, Ashish Sirasao, Tushar Krishna, Harshit Khaitan, Vikas Chandra, Vijay Janapa Reddi:
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. MLSys 2023 - 2022
- [c85]Ananda Samajdar, Eric Qin, Michael Pellauer, Tushar Krishna:
Self adaptive reconfigurable arrays (SARA): learning flexible GEMM accelerator configuration and mapping-space using ML. DAC 2022: 583-588 - [c84]Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna:
DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. DATE 2022: 232-237 - [c83]Tarannum Khan, Saeed Rashidi, Srinivas Sridharan, Pallavi Shurpali, Aditya Akella, Tushar Krishna:
Impact of RoCE Congestion Control Policies on Distributed Training of DNNs. HOTI 2022: 39-48 - [c82]Sheng-Chun Kao, Tushar Krishna:
MAGMA: An Optimization Framework for Mapping Multiple DNNs on Multiple Accelerator Cores. HPCA 2022: 814-830 - [c81]Hossein Farrokhbakht, Paul V. Gratz, Tushar Krishna, Joshua San Miguel, Natalie D. Enright Jerger:
Stay in your Lane: A NoC with Low-overhead Multi-packet Bypassing. HPCA 2022: 957-970 - [c80]Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna:
Demystifying Map Space Exploration for NPUs. IISWC 2022: 269-281 - [c79]Raveesh Garg, Eric Qin, Francisco Muñoz-Martínez, Robert Guirado, Akshay Jain, Sergi Abadal, José L. Abellán, Manuel E. Acacio, Eduard Alarcón, Sivasankaran Rajamanickam, Tushar Krishna:
Understanding the Design-Space of Sparse/Dense Multiphase GNN dataflows on Spatial Accelerators. IPDPS 2022: 571-582 - [c78]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: 581-596 - [c77]Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna:
Understanding Data Compression in Warehouse-Scale Datacenter Services. ISPASS 2022: 221-223 - [c76]Difei Cao, Jinsun Yoo, Zhuangdi Xu, Enrique Saurez, Harshit Gupta, Tushar Krishna, Umakishore Ramachandran:
MicroEdge: a multi-tenant edge cluster system architecture for scalable camera processing. Middleware 2022: 322-334 - [c75]Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna:
A Formalism of DNN Accelerator Flexibility. SIGMETRICS (Abstracts) 2022: 53-54 - 2021
- [c74]Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna:
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. PACT 2021: 30-44 - [c73]Jan Moritz Joseph, Lennart Bamberg, Geonhwa Jeong, Ruei-Ting Chien, Rainer Leupers, Alberto García-Ortiz, Tushar Krishna, Thilo Pionteck:
Bridging the Frequency Gap in Heterogeneous 3D SoCs through Technology-Specific NoC Router Architectures. ASP-DAC 2021: 197-203 - [c72]Robert Guirado, Hyoukjun Kwon, Sergi Abadal, Eduard Alarcón, Tushar Krishna:
Dataflow-Architecture Co-Design for 2.5D DNN Accelerators using Wireless Network-on-Package. ASP-DAC 2021: 806-812 - [c71]Geonhwa Jeong, Eric Qin, Ananda Samajdar, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna:
RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU. DAC 2021: 253-258 - [c70]Hyoukjun Kwon, Liangzhen Lai, Michael Pellauer, Tushar Krishna, Yu-Hsin Chen, Vikas Chandra:
Heterogeneous Dataflow Accelerators for Multi-DNN Workloads. HPCA 2021: 71-83 - [c69]Hossein Farrokhbakht, Henry Kao, Kamran Hasan, Paul V. Gratz, Tushar Krishna, Joshua San Miguel, Natalie D. Enright Jerger:
Pitstop: Enabling a Virtual Network Free Network-on-Chip. HPCA 2021: 682-695 - [c68]Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio, Tushar Krishna:
STONNE: Enabling Cycle-Level Microarchitectural Simulation for DNN Inference Accelerators. IISWC 2021: 201-213 - [c67]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: 1014-1024 - [c66]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: 540-553 - [c65]Sheng-Chun Kao, Tushar Krishna:
E3: A HW/SW Co-design Neuroevolution Platform for Autonomous Learning in Edge Device. ISPASS 2021: 288-298 - [c64]Jan Moritz Joseph, Ananda Samajdar, Lingjun Zhu, Rainer Leupers, Sung Kyu Lim, Thilo Pionteck, Tushar Krishna:
Architecture, Dataflow and Physical Design Implications of 3D-ICs for DNN-Accelerators. ISQED 2021: 60-66 - [c63]Lennart Bamberg, Tushar Krishna, Jan Moritz Joseph:
Technology-aware Router Architectures for On-Chip-Networks in Heterogeneous Technologies. NANOCOM 2021: 17:1-17:7 - [c62]Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio, Tushar Krishna:
A novel network fabric for efficient spatio-temporal reduction in flexible DNN accelerators. NOCS 2021: 1-8 - [c61]Srikant Bharadwaj, Shomit Das, Yasuko Eckert, Mark Oskin, Tushar Krishna:
DUB: dynamic underclocking and bypassing in nocs for heterogeneous GPU workloads. NOCS 2021: 49-54 - [c60]Mayank Parasar, Natalie D. Enright Jerger, Paul V. Gratz, Joshua San Miguel, Tushar Krishna:
SEEC: stochastic escape express channel. SC 2021: 34 - 2020
- [c59]Srikant Bharadwaj, Jieming Yin, Bradford M. Beckmann, Tushar Krishna:
Kite: A Family of Heterogeneous Interposer Topologies Enabled via Accurate Interconnect Modeling. DAC 2020: 1-6 - [c58]Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi:
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. DAC 2020: 1-6 - [c57]Saeed Rashidi, Pallavi Shurpali, Srinivas Sridharan, Naader Hassani, Dheevatsa Mudigere, Krishnakumar Nair, Misha Smelyanski, Tushar Krishna:
Scalable Distributed Training of Recommendation Models: An ASTRA-SIM + NS3 case-study with TCP/IP transport. Hot Interconnects 2020: 33-42 - [c56]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: 58-70 - [c55]Bahar Asgari, Ramyad Hadidi, Tushar Krishna, Hyesoon Kim, Sudhakar Yalamanchili:
ALRESCHA: A Lightweight Reconfigurable Sparse-Computation Accelerator. HPCA 2020: 249-260 - [c54]Mayank Parasar, Hossein Farrokhbakht, Natalie D. Enright Jerger, Paul V. Gratz, Tushar Krishna, Joshua San Miguel:
DRAIN: Deadlock Removal for Arbitrary Irregular Networks. HPCA 2020: 447-460 - [c53]Sheng-Chun Kao, Tushar Krishna:
GAMMA: Automating the HW Mapping of DNN Models on Accelerators via Genetic Algorithm. ICCAD 2020: 44:1-44:9 - [c52]Ananda Samajdar, Jan Moritz Joseph, Yuhao Zhu, Paul N. Whatmough, Matthew Mattina, Tushar Krishna:
A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim. ISPASS 2020: 58-68 - [c51]Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna:
ASTRA-SIM: Enabling SW/HW Co-Design Exploration for Distributed DL Training Platforms. ISPASS 2020: 81-92 - [c50]Parth Mannan, Ananda Samajdar, Tushar Krishna:
CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices. ISPASS 2020: 93-103 - [c49]Sheng-Chun Kao, Geonhwa Jeong, Tushar Krishna:
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning. MICRO 2020: 622-636 - [c48]Brian Crafton, Samuel Spetalnick, Gauthaman Murali, Tushar Krishna, Sung Kyu Lim, Arijit Raychowdhury:
Breaking Barriers: Maximizing Array Utilization for Compute in-Memory Fabrics. VLSI-SOC 2020: 123-128 - [c47]Brian Crafton, Samuel Spetalnick, Gauthaman Murali, Tushar Krishna, Sung Kyu Lim, Arijit Raychowdhury:
Statistical Array Allocation and Partitioning for Compute In-Memory Fabrics. VLSI-SoC (Selected Papers) 2020: 323-341 - 2019
- [c46]Jinwoo Kim, Gauthaman Murali, Heechun Park, Eric Qin, Hyoukjun Kwon, Venkata Chaitanya Krishna Chekuri, Nihar Dasari, Arvind Singh, Minah Lee, Hakki Mert Torun, Kallol Roy, Madhavan Swaminathan, Saibal Mukhopadhyay, Tushar Krishna, Sung Kyu Lim:
Architecture, Chip, and Package Co-design Flow for 2.5D IC Design Enabling Heterogeneous IP Reuse. DAC 2019: 178 - [c45]Ananda Samajdar, Tushar Garg, Tushar Krishna, Nachiket Kapre:
Scaling the Cascades: Interconnect-Aware FPGA Implementation of Machine Learning Problems. FPL 2019: 342-349 - [c44]Robert Guirado, Hyoukjun Kwon, Eduard Alarcón, Sergi Abadal, Tushar Krishna:
Understanding the Impact of On-chip Communication on DNN Accelerator Performance. ICECS 2019: 85-88 - [c43]Ramyad Hadidi, Jiashen Cao, Yilun Xie, Bahar Asgari, Tushar Krishna, Hyesoon Kim:
Characterizing the Deployment of Deep Neural Networks on Commercial Edge Devices. IISWC 2019: 35-48 - [c42]Zhongyuan Zhao, Hyoukjun Kwon, Sachit Kuhar, Weiguang Sheng, Zhigang Mao, Tushar Krishna:
mRNA: Enabling Efficient Mapping Space Exploration for a Reconfiguration Neural Accelerator. ISPASS 2019: 282-292 - [c41]Tushar Krishna:
A communication-centric approach for designing flexible DNN accelerators. NoCArc@MICRO 2019: 6:1 - [c40]Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer, Angshuman Parashar, Vivek Sarkar, Tushar Krishna:
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach. MICRO 2019: 754-768 - [c39]Mayank Parasar, Natalie D. Enright Jerger, Paul V. Gratz, Joshua San Miguel, Tushar Krishna:
SWAP: Synchronized Weaving of Adjacent Packets for Network Deadlock Resolution. MICRO 2019: 873-885 - [c38]Mayank Parasar, Tushar Krishna:
BINDU: deadlock-freedom with one bubble in the network. NOCS 2019: 3:1-3:8 - [c37]Sheng-Chun Kao, Chao-Han Huck Yang, Pin-Yu Chen, Xiaoli Ma, Tushar Krishna:
Reinforcement learning based interconnection routing for adaptive traffic optimization. NOCS 2019: 17:1-17:2 - 2018
- [c36]Hyoukjun Kwon, Ananda Samajdar, Tushar Krishna:
MAERI: Enabling Flexible Dataflow Mapping over DNN Accelerators via Reconfigurable Interconnects. ASPLOS 2018: 461-475 - [c35]Mohan Kumar, Steffen Maass, Sanidhya Kashyap, Ján Veselý, Zi Yan, Taesoo Kim, Abhishek Bhattacharjee, Tushar Krishna:
LATR: Lazy Translation Coherence. ASPLOS 2018: 651-664 - [c34]Zhongyuan Zhao, Yantao Liu, Weiguang Sheng, Tushar Krishna, Qin Wang, Zhigang Mao:
Optimizing the data placement and transformation for multi-bank CGRA computing system. DATE 2018: 1087-1092 - [c33]Nachiket Kapre, Tushar Krishna:
FastTrack: Exploiting Fast FPGA Wiring for Implementing NoC Shortcuts (Abstract Only). FPGA 2018: 286 - [c32]Brian Lebiednik, Sergi Abadal, Hyoukjun Kwon, Tushar Krishna:
Spoofing Prevention via RF Power Profiling in Wireless Network-on-Chip. AISTECS@HiPEAC 2018: 2:1-2:4 - [c31]Anirudh Jain, Sriseshan Srikanth, Erik P. DeBenedictis, Tushar Krishna:
Merge Network for a Non-Von Neumann Accumulate Accelerator in a 3D Chip. ICRC 2018: 1-11 - [c30]Mayank Parasar, Abhishek Bhattacharjee, Tushar Krishna:
SEESAW: Using Superpages to Improve VIPT Caches. ISCA 2018: 193-206 - [c29]Aniruddh Ramrakhyani, Paul V. Gratz, Tushar Krishna:
Synchronized Progress in Interconnection Networks (SPIN): A New Theory for Deadlock Freedom. ISCA 2018: 699-711 - [c28]Nachiket Kapre, Tushar Krishna:
FastTrack: Leveraging Heterogeneous FPGA Wires to Design Low-Cost High-Performance Soft NoCs. ISCA 2018: 739-751 - [c27]Ramyad Hadidi, Bahar Asgari, Jeffrey S. Young, Burhan Ahmad Mudassar, Kartikay Garg, Tushar Krishna, Hyesoon Kim:
Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube. ISPASS 2018: 99-108 - [c26]Srikant Bharadwaj, Guilherme Cox, Tushar Krishna, Abhishek Bhattacharjee:
Scalable Distributed Last-Level TLBs Using Low-Latency Interconnects. MICRO 2018: 271-284 - [c25]Ananda Samajdar, Parth Mannan, Kartikay Garg, Tushar Krishna:
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware. MICRO 2018: 855-866 - [c24]Mayank Parasar, Ankit Sinha, Tushar Krishna:
Brownian Bubble Router: Enabling Deadlock Freedom via Guaranteed Forward Progress. NOCS 2018: 9:1-9:8 - [c23]Brian Lebiednik, Sergi Abadal, Hyoukjun Kwon, Tushar Krishna:
Architecting a Secure Wireless Network-on-Chip. NOCS 2018: 16:1-16:8 - 2017
- [c22]Tushar Krishna, Arya Balachandran, Siau Ben Chiah, Li Zhang, Bing Wang, Cong Wang, Kenneth Eng-Kian Lee, Jürgen Michel, Li-Shiuan Peh:
Automatic place-and-route of emerging LED-driven wires within a monolithically-integrated CMOS-III-V process. DATE 2017: 344-349 - [c21]Aniruddh Ramrakhyani, Tushar Krishna:
Static Bubble: A Framework for Deadlock-Free Irregular On-chip Topologies. HPCA 2017: 253-264 - [c20]Monodeep Kar, Tushar Krishna:
A case for low frequency single cycle multi hop NoCs for energy efficiency and high performance. ICCAD 2017: 743-750 - [c19]Hyoukjun Kwon, Tushar Krishna:
OpenSMART: Single-cycle multi-hop NoC generator in BSV and Chisel. ISPASS 2017: 195-204 - [c18]Mayank Parasar, Tushar Krishna:
Lightweight Emulation of Virtual Channels using Swaps. NoCArc@MICRO 2017: 1:1-1:6 - [c17]Hyoukjun Kwon, Ananda Samajdar, Tushar Krishna:
Rethinking NoCs for Spatial Neural Network Accelerators. NOCS 2017: 19:1-19:8 - [c16]Janardhan Rao Doppa, Ryan Gary Kim, Mihailo Isakov, Michel A. Kinsy, Hyoukjun Kwon, Tushar Krishna:
Adaptive Manycore Architectures for Big Data Computing. NOCS 2017: 20:1-20:8 - 2016
- [c15]Yu-Hsin Chen, Tushar Krishna, Joel S. Emer, Vivienne Sze:
14.5 Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks. ISSCC 2016: 262-263 - 2014
- [c14]Woo-Cheol Kwon, Tushar Krishna, Li-Shiuan Peh:
Locality-oblivious cache organization leveraging single-cycle multi-hop NoCs. ASPLOS 2014: 715-728 - [c13]Chia-Hsin Owen Chen, Sunghyun Park, Suvinay Subramanian, Tushar Krishna, Bhavya K. Daya, Woo-Cheol Kwon, Brett Wilkerson, John Arends, Anantha P. Chandrakasan, Li-Shiuan Peh:
SCORPIO: 36-core shared memory processor demonstrating snoopy coherence on a mesh interconnect. Hot Chips Symposium 2014: 1-20 - [c12]Bhavya K. Daya, Chia-Hsin Owen Chen, Suvinay Subramanian, Woo-Cheol Kwon, Sunghyun Park, Tushar Krishna, Jim Holt, Anantha P. Chandrakasan, Li-Shiuan Peh:
SCORPIO: A 36-core research chip demonstrating snoopy coherence on a scalable mesh NoC with in-network ordering. ISCA 2014: 25-36 - [c11]Tushar Krishna, Li-Shiuan Peh:
Single-cycle collective communication over a shared network fabric. NOCS 2014: 1-8 - 2013
- [c10]Chia-Hsin Owen Chen, Sunghyun Park, Tushar Krishna, Suvinay Subramanian, Anantha P. Chandrakasan, Li-Shiuan Peh:
SMART: a single-cycle reconfigurable NoC for SoC applications. DATE 2013: 338-343 - [c9]Tushar Krishna, Chia-Hsin Owen Chen, Woo-Cheol Kwon, Li-Shiuan Peh:
Breaking the on-chip latency barrier using SMART. HPCA 2013: 378-389 - 2012
- [c8]Sunghyun Park, Tushar Krishna, Chia-Hsin Owen Chen, Bhavya K. Daya, Anantha P. Chandrakasan, Li-Shiuan Peh:
Approaching the theoretical limits of a mesh NoC with a 16-node chip prototype in 45nm SOI. DAC 2012: 398-405 - 2011
- [c7]Chia-Hsin Owen Chen, Sunghyun Park, Tushar Krishna, Li-Shiuan Peh:
A low-swing crossbar and link generator for low-power networks-on-chip. ICCAD 2011: 779-786 - [c6]Tushar Krishna, Li-Shiuan Peh, Bradford M. Beckmann, Steven K. Reinhardt:
Towards the ideal on-chip fabric for 1-to-many and many-to-1 communication. MICRO 2011: 71-82 - 2010
- [c5]Tushar Krishna, Jacob Postman, Christopher Edmonds, Li-Shiuan Peh, Patrick Chiang:
SWIFT: A SWing-reduced interconnect for a Token-based Network-on-Chip in 90nm CMOS. ICCD 2010: 439-446 - [c4]Chia-Hsin Owen Chen, Niket Agarwal, Tushar Krishna, Kyung-Hoae Koo, Li-Shiuan Peh, Krishna Saraswat:
Physical vs. Virtual Express Topologies with Low-Swing Links for Future Many-Core NoCs. NOCS 2010: 173-180 - 2009
- [c3]Niket Agarwal, Tushar Krishna, Li-Shiuan Peh, Niraj K. Jha:
GARNET: A detailed on-chip network model inside a full-system simulator. ISPASS 2009: 33-42 - 2008
- [c2]Tushar Krishna, Amit Kumar, Patrick Chiang, Mattan Erez, Li-Shiuan Peh:
NoC with Near-Ideal Express Virtual Channels Using Global-Line Communication. Hot Interconnects 2008: 11-20 - [c1]B. V. N. Silpa, Anjul Patney, Tushar Krishna, Preeti Ranjan Panda, G. S. Visweswaran:
Texture filter memory: a power-efficient and scalable texture memory architecture for mobile graphics processors. ICCAD 2008: 559-564
Editorship
- 2021
- [e1]Tushar Krishna, John Kim, Sergi Abadal, Joshua San Miguel:
NOCS '21: International Symposium on Networks-on-Chip, Virtual Event, October 14-15, 2021. ACM 2021, ISBN 978-1-4503-9083-5 [contents]
Informal and Other Publications
- 2024
- [i65]Zishen Wan, Che-Kai Liu, Hanchen Yang, Chaojian Li, Haoran You, Yonggan Fu, Cheng Wan, Tushar Krishna, Yingyan Lin, Arijit Raychowdhury:
Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI. CoRR abs/2401.01040 (2024) - [i64]Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna:
Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers. CoRR abs/2402.04744 (2024) - [i63]Akshat Ramachandran, Zishen Wan, Geonhwa Jeong, John Gustafson, Tushar Krishna:
Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference. CoRR abs/2403.05465 (2024) - [i62]Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao:
GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. CoRR abs/2403.05527 (2024) - [i61]Geonhwa Jeong, Po-An Tsai, Abhimanyu Rajeshkumar Bambhaniya, Stephen W. Keckler, Tushar Krishna:
Abstracting Sparse DNN Acceleration via Structured Sparse Tensor Decomposition. CoRR abs/2403.07953 (2024) - [i60]Jianming Tong, Jingtian Dang, Anupam Golder, Callie Hao, Arijit Raychowdhury, Tushar Krishna:
Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption. CoRR abs/2404.03216 (2024) - [i59]Zishen Wan, Che-Kai Liu, Mohamed Ibrahim, Hanchen Yang, Samuel Spetalnick, Tushar Krishna, Arijit Raychowdhury:
H3DFact: Heterogeneous 3D Integrated CIM for Factorization with Holographic Perceptual Representations. CoRR abs/2404.04173 (2024) - [i58]Raveesh Garg, Hyoukjun Kwon, Eric Qin, Yu-Hsin Chen, Tushar Krishna, Liangzhen Lai:
PipeOrgan: Efficient Inter-operation Pipelining with Flexible Spatial Organization and Interconnects. CoRR abs/2405.01736 (2024) - [i57]Jianming Tong, Anirudh Itagi, Prasanth Chatarasi, Tushar Krishna:
FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching. CoRR abs/2405.13170 (2024) - [i56]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 abs/2406.01698 (2024) - [i55]Geonhwa Jeong, Po-An Tsai, Stephen W. Keckler, Tushar Krishna:
SDQ: Sparse Decomposed Quantization for LLM Inference. CoRR abs/2406.13868 (2024) - [i54]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 abs/2406.19580 (2024) - [i53]Akshat Ramachandran, Souvik Kundu, Tushar Krishna:
CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs. CoRR abs/2407.05266 (2024) - [i52]Jinsun Yoo, William Won, Meghan Cowan, Nan Jiang, Benjamin Klenk, Srinivas Sridharan, Tushar Krishna:
Towards a Standardized Representation for Deep Learning Collective Algorithms. CoRR abs/2408.11008 (2024) - [i51]Zishen Wan, Che-Kai Liu, Hanchen Yang, Ritik Raj, Chaojian Li, Haoran You, Yonggan Fu, Cheng Wan, Sixu Li, Youbin Kim, Ananda Samajdar, Yingyan Celine Lin, Mohamed Ibrahim, Jan M. Rabaey, Tushar Krishna, Arijit Raychowdhury:
Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture. CoRR abs/2409.13153 (2024) - 2023
- [i50]Francisco Muñoz-Martínez, Raveesh Garg, José L. Abellán, Michael Pellauer, Manuel E. Acacio, Tushar Krishna:
Flexagon: A Multi-Dataflow Sparse-Sparse Matrix Multiplication Accelerator for Efficient DNN Processing. CoRR abs/2301.10852 (2023) - [i49]Geonhwa Jeong, Sana Damani, Abhimanyu Rajeshkumar Bambhaniya, Eric Qin, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna:
VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs. CoRR abs/2302.08687 (2023) - [i48]Raveesh Garg, Michael Pellauer, Sivasankaran Rajamanickam, Tushar Krishna:
Exploiting Inter-Operation Data Reuse in Scientific Applications using GOGETA. CoRR abs/2303.11499 (2023) - [i47]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 abs/2303.14006 (2023) - [i46]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:
Perspectives on AI Architectures and Co-design for Earth System Predictability. CoRR abs/2304.03748 (2023) - [i45]William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Ajaya Durg, Swati Gupta, Tushar Krishna:
TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training. CoRR abs/2304.05301 (2023) - [i44]Srinivas Sridharan, Taekyung Heo, Louis Feng, Zhaodong Wang, Matt Bergeron, Wenyin Fu, Shengbao Zheng, Brian Coutinho, Saeed Rashidi, Changhai Man, Tushar Krishna:
Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces. CoRR abs/2305.14516 (2023) - [i43]Payman Behnam, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Rajeshkumar Bambhaniya, Tushar Krishna, Alexey Tumanov:
Subgraph Stationary Hardware-Software Inference Co-Design. CoRR abs/2306.17266 (2023) - 2022
- [i42]Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya, Michael Pellauer, Angshuman Parashar, Sivasankaran Rajamanickam, Cong Hao, Tushar Krishna:
Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity. CoRR abs/2201.08916 (2022) - [i41]Sheng-Chun Kao, Xiaoyu Huang, Tushar Krishna:
DNNFuser: Generative Pre-Trained Transformer as a Generalized Mapper for Layer Fusion in DNN Accelerators. CoRR abs/2201.11218 (2022) - [i40]Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna:
DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. CoRR abs/2201.11220 (2022) - [i39]Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna:
A Formalism of DNN Accelerator Flexibility. CoRR abs/2206.02987 (2022) - [i38]Tarannum Khan, Saeed Rashidi, Srinivas Sridharan, Pallavi Shurpali, Aditya Akella, Tushar Krishna:
Impact of RoCE Congestion Control Policies on Distributed Training of DNNs. CoRR abs/2207.10898 (2022) - [i37]Sheng-Chun Kao, Amir Yazdanbakhsh, Suvinay Subramanian, Shivani Agrawal, Utku Evci, Tushar Krishna:
Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask. CoRR abs/2209.07617 (2022) - [i36]Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna:
Demystifying Map Space Exploration for NPUs. CoRR abs/2210.03731 (2022) - [i35]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, Liangzhen Lai, Ashish Sirasao, Tushar Krishna, Harshit Khaitan, Vikas Chandra, Vijay Janapa Reddi:
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. CoRR abs/2211.08675 (2022) - [i34]Divya Kiran Kadiyala, Saeed Rashidi, Taekyung Heo, Abhimanyu Rajeshkumar Bambhaniya, Tushar Krishna, Alexandros Daglis:
COMET: A Comprehensive Cluster Design Methodology for Distributed Deep Learning Training. CoRR abs/2211.16648 (2022) - 2021
- [i33]Ananda Samajdar, Michael Pellauer, Tushar Krishna:
Self-Adaptive Reconfigurable Arrays (SARA): Using ML to Assist Scaling GEMM Acceleration. CoRR abs/2101.04799 (2021) - [i32]Raveesh Garg, Eric Qin, Francisco Muñoz-Martínez, Robert Guirado, Akshay Jain, Sergi Abadal, José L. Abellán, Manuel E. Acacio, Eduard Alarcón, Sivasankaran Rajamanickam, Tushar Krishna:
A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators. CoRR abs/2103.07977 (2021) - [i31]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 abs/2103.10452 (2021) - [i30]Sheng-Chun Kao, Tushar Krishna:
Domain-specific Genetic Algorithm for Multi-tenant DNNAccelerator Scheduling. CoRR abs/2104.13997 (2021) - [i29]Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna:
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. CoRR abs/2106.10499 (2021) - [i28]Sheng-Chun Kao, Suvinay Subramanian, Gaurav Agrawal, Tushar Krishna:
ATTACC the Quadratic Bottleneck of Attention Layers. CoRR abs/2107.06419 (2021) - [i27]Ananda Samajdar, Jan Moritz Joseph, Matthew Denton, Tushar Krishna:
AIRCHITECT: Learning Custom Architecture Design and Mapping Space. CoRR abs/2108.08295 (2021) - [i26]Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna:
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. CoRR abs/2109.07419 (2021) - [i25]William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna:
Exploring Multi-dimensional Hierarchical Network Topologies for Efficient Distributed Training of Trillion Parameter DL Models. CoRR abs/2109.11762 (2021) - [i24]Geonhwa Jeong, Eric Qin, Ananda Samajdar, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna:
RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU. CoRR abs/2110.01752 (2021) - [i23]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 abs/2110.04478 (2021) - 2020
- [i22]Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi:
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. CoRR abs/2002.04116 (2020) - [i21]Prasanth Chatarasi, Hyoukjun Kwon, Natesh Raina, Saurabh Malik, Vaisakh Haridas, Tushar Krishna, Vivek Sarkar:
MARVEL: A Decoupled Model-driven Approach for Efficiently Mapping Convolutions on Spatial DNN Accelerators. CoRR abs/2002.07752 (2020) - [i20]Sheng-Chun Kao, Arun Ramamurthy, Tushar Krishna:
Generative Design of Hardware-aware DNNs. CoRR abs/2006.03968 (2020) - [i19]Sheng-Chun Kao, Arun Ramamurthy, Reed Williams, Tushar Krishna:
Conditional Neural Architecture Search. CoRR abs/2006.03969 (2020) - [i18]Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio, Tushar Krishna:
STONNE: A Detailed Architectural Simulator for Flexible Neural Network Accelerators. CoRR abs/2006.07137 (2020) - [i17]Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Matthew Denton, Tushar Krishna:
Efficient Communication Acceleration for Next-Gen Scale-up Deep Learning Training Platforms. CoRR abs/2007.00156 (2020) - [i16]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, Daniel Rodrigues Carvalho, Jerónimo Castrillón, Lizhong Chen, Nicolas Derumigny, Stephan Diestelhorst, Wendy Elsasser, Marjan Fariborz, Amin Farmahini Farahani, Pouya Fotouhi, Ryan Gambord, Jayneel Gandhi, Dibakar Gope, Thomas Grass, Bagus Hanindhito, Andreas Hansson, Swapnil Haria, Austin Harris, Timothy Hayes, Adrian Herrera, Matthew Horsnell, Syed Ali Raza Jafri, Radhika Jagtap, Hanhwi Jang, Reiley Jeyapaul, Timothy M. Jones, Matthias Jung, Subash Kannoth, Hamidreza Khaleghzadeh, Yuetsu Kodama, Tushar Krishna, Tommaso Marinelli, Christian Menard, Andrea Mondelli, Tiago Mück, Omar Naji, Krishnendra Nathella, Hoa Nguyen, Nikos Nikoleris, Lena E. Olson, Marc S. Orr, Binh Pham, Pablo Prieto, Trivikram Reddy, Alec Roelke, Mahyar Samani, Andreas Sandberg, Javier Setoain, Boris Shingarov, Matthew D. Sinclair, Tuan Ta, Rahul Thakur, Giacomo Travaglini, Michael Upton, Nilay Vaish, Ilias Vougioukas, Zhengrong Wang, Norbert Wehn, Christian Weis, David A. Wood, Hongil Yoon, Éder F. Zulian:
The gem5 Simulator: Version 20.0+. CoRR abs/2007.03152 (2020) - [i15]Brian Crafton, Samuel Spetalnick, Gauthaman Murali, Tushar Krishna, Sung Kyu Lim, Arijit Raychowdhury:
Breaking Barriers: Maximizing Array Utilization for Compute In-Memory Fabrics. CoRR abs/2008.06741 (2020) - [i14]Afshin Abdi, Saeed Rashidi, Faramarz Fekri, Tushar Krishna:
Restructuring, Pruning, and Adjustment of Deep Models for Parallel Distributed Inference. CoRR abs/2008.08289 (2020) - [i13]Parth Mannan, Ananda Samajdar, Tushar Krishna:
CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices. CoRR abs/2008.11881 (2020) - [i12]Sheng-Chun Kao, Geonhwa Jeong, Tushar Krishna:
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning. CoRR abs/2009.02010 (2020) - [i11]Robert Guirado, Hyoukjun Kwon, Sergi Abadal, Eduard Alarcón, Tushar Krishna:
Dataflow-Architecture Co-Design for 2.5D DNN Accelerators using Wireless Network-on-Package. CoRR abs/2011.14755 (2020) - [i10]Jan Moritz Joseph, Ananda Samajdar, Lingjun Zhu, Rainer Leupers, Sung Kyu Lim, Thilo Pionteck, Tushar Krishna:
Architecture, Dataflow and Physical Design Implications of 3D-ICs for DNN-Accelerators. CoRR abs/2012.12563 (2020) - 2019
- [i9]Sheng-Chun Kao, Chao-Han Huck Yang, Pin-Yu Chen, Xiaoli Ma, Tushar Krishna:
Reinforcement Learning based Interconnection Routing for Adaptive Traffic Optimization. CoRR abs/1908.04484 (2019) - [i8]Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra:
HERALD: Optimizing Heterogeneous DNN Accelerators for Edge Devices. CoRR abs/1909.07437 (2019) - [i7]Robert Guirado, Hyoukjun Kwon, Eduard Alarcón, Sergi Abadal, Tushar Krishna:
Understanding the Impact of On-chip Communication on DNN Accelerator Performance. CoRR abs/1912.01664 (2019) - 2018
- [i6]Hyoukjun Kwon, Michael Pellauer, Tushar Krishna:
MAESTRO: An Open-source Infrastructure for Modeling Dataflows within Deep Learning Accelerators. CoRR abs/1805.02566 (2018) - [i5]Ananda Samajdar, Parth Mannan, Kartikay Garg, Tushar Krishna:
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware. CoRR abs/1808.01363 (2018) - [i4]Ananda Samajdar, Yuhao Zhu, Paul N. Whatmough, Matthew Mattina, Tushar Krishna:
SCALE-Sim: Systolic CNN Accelerator. CoRR abs/1811.02883 (2018) - 2017
- [i3]Mayank Parasar, Abhishek Bhattacharjee, Tushar Krishna:
VESPA: VIPT Enhancements for Superpage Accesses. CoRR abs/1701.03499 (2017) - [i2]Pengju Ren, Michel A. Kinsy, Mengjiao Zhu, Shreeya Khadka, Mihailo Isakov, Aniruddh Ramrakhyani, Tushar Krishna, Nanning Zheng:
FASHION: Fault-Aware Self-Healing Intelligent On-chip Network. CoRR abs/1702.02313 (2017) - [i1]Ramyad Hadidi, Bahar Asgari, Jeffrey S. Young, Burhan Ahmad Mudassar, Kartikay Garg, Tushar Krishna, Hyesoon Kim:
Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube. CoRR abs/1707.05399 (2017)
Coauthor Index
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