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Follow @eems_mit8.10.2023
Peter Li receives the EECS MathWorks Fellowship
7.24.2023
Fisher and Nellie’s paper on “Tailor Swiftiles: Accelerating Sparse Tensor Algebra by Overbooking Buffer Occupancy” has been accepted for presentation at MICRO 2023
Nellie’s paper on “HighLight: Efficient and Flexible DNN Acceleration with Hierarchical Structured Sparsity” has been accepted for presentation at MICRO 2023
6.6.2023
CSAIL Podcast: The Importance of Energy Efficiency in AI with Vivienne Sze
3.9.2023
Tanner’s paper on “RAELLA: Reforming the Arithmetic for Efficient, Low-Resolution, and Low-Loss Analog PIM: No Retraining Required!” has been accepted for presentation at ISCA 2023
3.1.2023
Michael and Nellie’s paper on “LoopTree: Enabling Exploration of Fused-layer Dataflow Accelerators” has been accepted for presentation at ISPASS 2023
1.13.2023
MIT News: Computers that power self-driving cars could be a huge driver of global carbon emissions
1.7.2023
Hsin-Yu’s paper on “Individualized Tracking of Neurocognitive-State-Dependent Eye-Movement Features Using Mobile Devices” has been accepted for publication in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)
10.4.2022
Nellie receives the MICRO 2022 Distinguished Artifact Award for her open-source code for “Sparseloop: An Analytical Approach to Sparse Tensor Accelerator Modeling”
9.24.2022
Soumya’s paper on “Data Centers on Wheels: Emissions from Computing Onboard Autonomous Vehicles” has been accepted for publication in IEEE Micro’s Special Issue on Environmentally Sustainable Computing
9.22.2022
Tanner Andrulis is named to the Siebel Scholars class of 2023
7.19.2022
Nellie’s paper on “Sparseloop: An Analytical Approach to Sparse Tensor Accelerator Modeling” has been accepted for presentation at MICRO 2022
1.31.2022
Soumya’s paper on “Uncertainty from Motion for DNN Monocular Depth Estimation” has been accepted for presentation at ICRA 2022
Peter’s paper on “Memory-Efficient Gaussian Fitting for Depth Images in Real Time” has been accepted for presentation at ICRA 2022
1.4.2022
Soumya Sudhakar receives the 2021-22 Accenture Fellowship
8.16.2021
Hsin-Yu and Gladynel’s paper on “App-based saccade latency and directional error determination across the adult age spectrum” has been accepted for publication in IEEE Transactions on Biomedical Engineering (TBME)
6.30.2021
Keshav and Peter’s paper on “Efficient Computation of Map-scale Continuous Mutual Information on Chip in Real Time” has been accepted for presentation at IROS 2021
4.28.2021
MIT News: Q&A: Vivienne Sze on crossing the hardware-software divide for efficient artificial intelligence
3.1.2021
Francis, Nellie and Matt’s paper on “Architecture-Level Energy Estimation for Heterogeneous Computing Systems” has been accepted for presentation at ISPASS 2021
Nellie’s paper on “Sparseloop: An Analytical, Energy-Focused Design Space Exploration Methodology for Sparse Tensor Accelerators” has been accepted for presentation at ISPASS 2021
2.28.2021
Tien-Ju and Yi-Lun’s paper on “NetAdaptV2: Efficient neural architecture search with fast super-network training and architecture optimization” has been accepted for presentation at CVPR 2021
1.27.2021
Soumya Sudhakar receives Best Presentation Award at the 2021 Microsystems Annual Research Conference (MARC) for her work on “Balancing Actuation Energy and Computing Energy in Motion Planning”
9.22.2020
Featured ACM Member: Vivienne Sze
9.1.2020
New article on “How to Evaluate Deep Neural Network Processors: TOPS/W (Alone) Considered Harmful” in SSCS Magazine
8.7.2020
MIT News: Shrinking deep learning’s carbon footprint
7.24.2020
MIT News: The tenured engineers of 2020
6.25.2020
Our book on “Efficient Processing for Deep Neural Networks” is published
6.5.2020
Theia receives the first place 2020 David Adler Memorial Thesis Award for her MEng thesis entitled “A Continuous Approach to Information-Theoretic Exploration with Range Sensors”
6.2.2020
New website MIT LEAN (Low-Energy Autonomy and Navigation) for work on enabling efficient computing for low-energy robotics
5.29.2020
Video and slides from our tutorial on using Timeloop/Accelergy for rapid evaluation of DNN accelerators are now available online
5.20.2020
Peter receives First Place, Graduate winner at the ACM Student Research Competition Grand Finals for his work on “A Mutual Information Accelerator for Autonomous Robot Exploration”
4.17.2020
Our forthcoming book on “Efficient Processing for Deep Neural Networks” is now available for pre-order
4.16.2020
Peter receives the NSERC Postgraduate Scholarship – Doctoral (PGS D)
2.16.2020
Excerpt of from our forthcoming book “Efficient Processing for Deep Neural Networks” discussing advanced technologies now available
2.13.2020
Nellie’s paper on “An Architecture-Level Energy and Area Estimator for Processing-In-Memory Accelerator Designs” has been accepted for presentation at ISPASS 2020
1.30.2020
Soumya receives Best Presentation Award in the Control Theory and Algorithms Session at the LIDS Student Conference 2020
1.23.2020
Video and slides of our talk on “Efficient Computing for Deep Learning, Robotics, and AI” for the MIT Deep Learning Seminar Series are now available online
1.21.2020
Theia’s paper on “An Efficient and Continuous Approach to Information-Theoretic Exploration” has been accepted for presentation at ICRA 2020
Soumya’s paper on “Balancing Actuation and Computing Energy in Motion Planning” has been accepted for presentation at ICRA 2020
1.14.2020
Vivienne Sze receives the inaugural ACM-W Rising Star Award
12.9.2019
Video and slides for our NeurIPS tutorial on “Efficient Processing of Deep Neural Networks: from Algorithms to Hardware Architectures” are now available online
10.24.2019
We will be giving a tutorial on “Efficient Processing of Deep Neural Network: from Algorithms to Hardware Architectures” at NeurIPS 2019 on December 9, 2019
10.16.2019
Peter receives the Gold medal in the ACM Student Research Competition (SRC) at MICRO-52 for his work on “A Mutual Information Accelerator for Autonomous Robot Exploration”
10.1.2019
We will be giving a tutorial on “How to Understand and Evaluate Deep Learning Processors” at ISSCC 2020 on February 16, 2020
9.19.2019
Code released for NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications
9.18.2019
Tien-Ju’s paper on “Design Considerations for Efficient Deep Neural Networks on Processing-in-Memory Accelerators” has been accepted for presentation at IEDM 2019
9.7.2019
Our talk on “Domain Specific Architectures for AI and Robotics: Opportunities and Challenges” at the SIGARCH Visioning Workshop: Agile and Open Hardware for Next Generation Computing (ISCA 2019) is now available online
8.28.2019
We will be giving a tutorial on “Efficient Image Processing with Deep Neural Networks” at the IEEE International Conference on Image Processing (ICIP) in Taipei, Taiwan on September 22, 2019
8.27.2019
We will be giving a tutorial on “Timeloop and Accelergy: Tools for Evaluating Deep Neural Network Accelerator Designs” at MICRO-52 on October 12, 2019
8.14.2019
Nellie’s paper on “Accelergy: An Architecture-Level Energy Estimation Methodology for Accelerator Designs” has been accepted for presentation at ICCAD 2019
7.19.2019
TEDxMIT talk on Energy-Efficient AI now available online
7.11.2019
Slides and Videos from ICML2019 and CVPR2019 Workshops now available on talks/tutorial page
6.26.2019
Yu-Hsin Chen receives the 2019 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, which recognizes excellent thesis research by doctoral candidates in the field of computer architecture, for contributions to efficient and flexible dataflows and architectures for deep learning acceleration.
6.12.2019
Our paper “Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones” receives the Best Student Paper Award at the IEEE Symposium on VLSI Circuits (VLSI-Circuits)
5.15.2019
We will be giving a tutorial on Hardware Architectures for Deep Neural Networks at ISCA 2019
5.8.2019
New paper on “FSMI: Fast computation of Shannon Mutual Information for information-theoretic mapping” available on arXiv
5.1.2019
MIT Technology Review: This chip was demoed at Jeff Bezos’s secretive tech conference. It could be key to the future of AI.
4.30.2019
James and Alan’s paper on “Low Power Adaptive Time-Of-Flight Imaging For Multiple Rigid Objects” has been accepted for presentation at ICIP 2019
Peter and Zhengdong’s paper on “High-throughput Computation of Shannon Mutual Information on Chip” has been accepted for presentation at RSS 2019
4.21.2019
Yu-Hsin and Tien-Ju’s paper on “Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices” has been accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS)
4.19.2019
Hsin-Yu and Gladynel’s paper on “Measuring Saccade Latency Using Smartphone Cameras” has been accepted for publication in IEEE Journal of Biomedical and Health Informatics (JBHI)
4.18.2019
Vivienne Sze wins Edgerton Faculty Award
4.16.2019
Our talk on “Efficient Computing for Autonomous Navigation of Miniaturized Robots” at the MARS Conference 2019 is now available online.
4.12.2019
Slides from talk on “Efficient Computing for AI and Robotics” now available online
4.1.2019
An article by Prof. Sze in the ECE Source about “Computing Hardware: A Look at the Future”
3.26.2019
James’s paper on “Low Power Depth Estimation of Rigid Objects for Time-of-Flight Imaging” has been accepted for publication in IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
3.12.2019
Our talk on “Energy-Efficient AI” at the MIT College of Computing celebration is now available online
3.6.2019
Code released for FastDepth: Fast Monocular Depth Estimation on Embedded Systems
1.29.2019
Diana, Fangchang and Tien-Ju’s paper on “FastDepth: Fast Monocular Depth Estimation on Embedded Systems” has been accepted for presentation at ICRA 2019
Zhengdong and Trevor’s paper on “FSMI: Fast computation of Shannon Mutual Information for information-theoretic mapping” has been accepted for presentation at ICRA 2019
12.1.2018
Amr and Zhengdong’s paper on “Navion: A 2mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones” has been accepted for publication in the Journal of Solid-State Circuits (JSSC)
11.6.2018
Yu-Hsin Chen receives the 2018 Jin-Au Kong Doctoral Thesis Prize for outstanding doctoral thesis in Electrical Engineering at MIT
10.9.2018
New paper on “Low Power Depth Estimation of Rigid Objects for Time-of-Flight Imaging” available on arXiv
9.25.2018
New paper on “Navion: A 2mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones” available on arXiv
9.19.2018
Prof. Sze will be teaching a half day course on “Foundations of Deep Learning: An Introduction” in Hong Kong Oct 10 via MIT Professional Education
9.13.2018
Video of our talk on Navion at Hot Chips is now available online
8.20.2018
Our Navion chip is presented at HotChips 30
7.24.2018
Prof. Sze receives the 2018 Qualcomm Faculty Award
7.3.2018
Tien-Ju’s paper on “NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications” has been accepted for presentation at ECCV2018
6.25.2018
Prof. Sze gives a keynote at the 2018 Picture Coding Symposium on “Energy-Efficient Processing at the Edge: From Compressing to Understanding Pixels”
6.20.2018
MIT News: Chip upgrade helps miniature drones navigate
5.18.2018
Diana Wofk receives the 2017-2018 SuperUROP Award
5.10.2018
Mehul’s paper on “A Fully-Integrated Energy-Efficient H.265/HEVC Decoder With eDRAM for Wearable Devices” has been accepted for publication in JSSC
5.4.2018
Hsin-Yu and Gladynel’s paper on “Enabling Saccade Latency Measurements With Consumer-Grade Cameras” has been accepted for presentation at ICIP 2018
James’s paper on “Depth Estimation Of Non-Rigid Objects For Time-Of-Flight Imaging” has been accepted for presentation at ICIP 2018
4.30.2018
Video of keynote on “Energy-Efficient Edge Computing for AI-driven Applications” at 2018 UIUC CSL Student Conference now available online
4.7.2018
New paper on “NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications” available on arXiv
4.6.2018
Gladynel and Hsin-Yu’s paper on “Determination of saccade latency distributions using video recordings from consumer-grade devices” has been accepted for presentation at EMBC 2018
3.31.2018
Prof. Sze’s two-day summer short course on “Designing Efficient Deep Learning Systems” via MIT Professional Education is now open for registration
3.21.2018
Amr and Zhengdong’s paper on “Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones” has been accepted for presentation at VLSI 2018
3.9.2018
Prof. Sze receives the Facebook Hardware & Software Research Award
3.3.2018
Our paper “Hardware for Machine Learning: Challenges and Opportunities” receives the Best Invited Paper Award at the IEEE Custom Integrated Circuits Conference (CICC)
2.22.2018
Prof. Sze will be giving a tutorial at IEEE ISCAS 2018 with Prof. Boris Murmann and Prof. Naveen Verma on “Introduction to Machine Learning and Inference for Circuit and System Designers”
2.4.2018
Prof. Sze will be giving a talk about “Understanding the Limitations of Existing Energy-Efficient Design Approaches for Deep Neural Networks” at SysML 2018
1.30.2018
Hsin-Yu and Gladynel receive the best pitch and best poster awards, respectively, at MARC 2018
1.22.2018
Prof. Sze will be giving a talk about “Efficient Edge Solutions for Deep Learning Applications” at the ISSCC 2018 Short Course on Hardware Approaches to Machine Learning and Inference
12.3.2017
Prof. Sze is co-organizing a workshop on Circuits for Social Good at ISSCC 2018
12.1.2017
MIT News: Building the hardware for the next generation of artificial intelligence
11.22.2017
Our paper on “Efficient Processing of Deep Neural Networks: A Tutorial and Survey” is featured on the cover of the December issue of Proceedings of the IEEE
11.7.2017
Code released for FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos
11.1.2017
Gladynel Saavedra is named to the Siebel Scholars class of 2018
10.25.2017
Prof. Sze was part of the Joint Collaborative Team on Video Coding that received an Emmy for the HEVC standard
9.18.2017
Prof. Sze will be teaching a short course on “Designing Efficient Deep Learning Systems” via MIT Professional Education
8.22.2017
Prof. Sze will give a webinar about “Efficient Processing for Deep Learning” hosted by Embedded Vision Alliance
7.18.2017
MIT News: Bringing neural networks to cellphones
7.12.2017
MIT News: Miniaturizing the brain of a drone
6.25.2017
Slides from ISCA Tutorial on Hardware Architectures for DNNs now available online
5.9.2017
Zhengdong’s paper on “FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos” has been accepted for presentation at the 2017 CVPR Workshop on New Trends in Image Restoration and Enhancement
5.8.2017
James’s paper on “Low Power Depth Estimation for Time-of-Flight Imaging” has been accepted for presentation at ICIP 2017
5.1.2017
Prof. Sze will be teaching a new class on “6.S082/6.888 Hardware Architecture for Deep Learning” in Fall 2017 with Prof. Joel Emer
4.28.2017
Amr and Zhengdong’s paper on “Visual-Inertial Odometry on Chip: An Algorithm-and-Hardware Co-design Approach” has been accepted for presentation at RSS 2017
4.27.2017
Prof. Sze receives the 2017 Qualcomm Faculty Award
3.28.2017
New paper “Efficient Processing of Deep Neural Networks: A Tutorial and Survey” now available on arxiv
3.27.2017
DNN Energy Estimation Website available online
3.26.2017
Mehul’s paper on “A Fully-Integrated Energy-Efficient H.265/HEVC Decoder with eDRAM for Wearable Devices” has been accepted for presentation at IEEE VLSI 2017
3.17.2017
Our paper on “Towards Closing the Energy Gap Between HOG and CNN Features for Embedded Vision” has been accepted for presentation at IEEE ISCAS 2017
3.3.2017
Tien-Ju and Yu-Hsin’s paper “Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning” has been accepted for presentation at IEEE CVPR 2017
2.13.2017
Prof. Sze receives the Google Faculty Research Award
2.7.2017
Prof. Sze promoted to the rank of Associate Professor without Tenure
1.22.2017
We will be giving a tutorial on Hardware Architectures for Deep Neural Networks at ISCA 2017
1.17.2017
Our paper “Hardware for Machine Learning: Challenges and Opportunities” has been accepted for presentation at IEEE CICC 2017
1.3.2017
Amr and Zhengdong’s paper on “A 58.6mW 30fps Real-Time Programmable Multi-Object Detection Accelerator with Deformable Parts Models on Full HD 1920×1080 Videos” has been accepted for publication in the Journal of Solid-State Circuits (JSSC)
12.30.2016
Our paper “Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks” has been selected for IEEE Micro “Top Picks in Computer Architecture” for 2016
12.23.2016
New paper on “Hardware for Machine Learning: Challenges and Opportunities” available on arXiv
12.22.2016
Slides from NIPS 2016 Workshop on EMDNN available online
12.2.2016
Yu-Hsin Chen receives the IEEE Solid-State Circuits Society Predoctoral Achievement Award for 2016-2017
11.16.2016
New paper on “Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning” available on arXiv
11.12.2016
Slides for MICRO Tutorial on Hardware Architectures for DNNs now available online
11.7.2016
Prof. Sze’s talk on “Energy-Efficient Hardware for Embedded Vision and Deep Convolutional Neural Networks” now available on YouTube
9.28.2016
Yu-Hsin’s paper on “Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks” has been accepted for publication in the Journal of Solid-State Circuits (JSSC) Special Issue on the 2016 International Solid State Circuits Conference (ISSCC)
9.20.2016
Prof. Sze to give a keynote at the NIPS 2016 Workshop on Efficient Methods for Deep Neural Networks (EMDNN)
8.25.2016
Prof. Sze to give an invited talk at the ICCAD 2016 Workshop on Hardware and Algorithms for Learning On-a-chip (HALO)
7.10.2016
We will be giving a tutorial on Hardware Architectures for Deep Neural Networks at MICRO-49
6.9.2016
Eyeriss featured in Microprocessor Report
5.9.2016
Prof. Sze to give a keynote at the CVPR 2016 Embedded Vision Workshop
4.20.2016
Prof. Sze to give an invited talk at the ICML 2016 Workshop on On-Device Intelligence
4.15.2016
Yu-Hsin to give a talk on Eyeriss at Deep Learning Summit 2016 in Boston
4.4.2016
Yu-Hsin to present a poster on Eyeriss at GTC 2016
4.1.2016
Amr and Zhengdong’s paper accepted to IEEE VLSI 2016
3.23.2016
Prof. Sze receives the Young Investigator Research Program (YIP) award from the Air Force Office of Scientific Research (AFOSR)
3.8.2016
Yu-Hsin Chen to present a paper at IEEE ISCA 2016
3.3.2016
Prof. Sze receives a 2016 3M Non-Tenured Faculty Award
2.12.2016
Eyeriss Project Page Online
2.3.2016
MIT News: Energy-friendly chip can perform powerful artificial-intelligence tasks
11.16.2015
Our deep learning chip (Eyeriss) is highlighted in an EETimes article about ISSCC 2016
11.5.2015
Amr Suleiman selected to present his work on low power object detection at the ISSCC 2016 Student Research Preview
10.14.2015
Amr’s paper on “An Energy-efficient Hardware Implementation of HOG-based Object Detection at 1080HD 60 fps with Multi-scale Support” has been accepted for publication in the Journal of Signal Processing Systems
10.12.2015
Yu-Hsin Chen to present a paper at IEEE ISSCC 2016
6.5.2015
Amr Suleiman awarded third place in the 2015 Broadcom Foundation University Research Competition
4.29.2015
Zhengdong Zhang to present a paper at IEEE ICIP 2015
4.21.2015
Amr Suleiman selected as a finalist in the 2015 Broadcom Foundation University Research Competition
4.16.2015
Yu-Hsin Chen receives the 2015 NVIDIA Graduate Fellowship
1.18.2015
Yu-Hsin Chen receives the 2015 Analog Devices Outstanding Student Designer Award
12.18.2014
Prof. Sze receives the 2014 DARPA Young Faculty Award (YFA)
10.6.2014
Yu-Hsin’s paper on “A Deeply Pipelined CABAC Decoder for HEVC Supporting Level 6.2 High-tier Applications” has been accepted for publication in IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
9.22.2014
Mehul’s paper on “Energy and Area-Efficient Hardware Implementation of HEVC Inverse Transform and Dequantization” recognized as one of the “Top 10%” papers at IEEE ICIP 2014
9.1.2014
Prof. Sze’s co-edited book “High Efficiency Video Coding (HEVC) – Algorithms and Architectures” is published by Springer
8.1.2014
Prof. Sze will serve as a guest editor for the “Special Section on Efficient HEVC Implementations” in IEEE Transactions on Circuits and Systems for Video Technology
7.30.2014
Amr Suleiman to present a paper at IEEE SiPS 2014
5.21.2014
Yu-Hsin Chen and Mehul Tikekar to present papers at IEEE ICIP 2014
1.21.2014
Prof. Sze will chair a special session on “Efficient Design of HEVC Video-Codec Implementations” at IEEE ICIP 2014
12.19.2013
Prof. Sze will be giving a tutorial at IEEE ISCAS 2014 with Dr. Madhukar Budagavi on “Design and Implementation of Next Generation Video Coding Systems”
12.16.2013
Prof. Sze recipient of the 2013 Jonathan Allen Junior Faculty Award
10.18.2013
Sze, Vaikuntanathan named for career development professorships
9.23.2013
Heldt, Sze and Vaikuntananthan join EECS Faculty
