Our paper titled "Fusion-3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering" won the best paper award at the 57th IEEE/ACM International Symposium on Microarchitecture (MICRO 2024)! Congratulations to Sixu Li, Yang Zhao, Chaojian Li, Bowei Guo, Jingqun Zhang, Wenbo Zhu, Zhifan Ye, and Cheng Wan!

Congratulations to Choajian Li and Sixu Li for their paper titled "A Unified Accelerator for Real-Time Rendering Across Diverse Neural Renderers" being accepted to HPCA 2025!

Congratulations to Zhifan Ye, Yonggan Fu, Sixu Li, Cheng Wan, and Chaojian Li for their paper titled "Gaussian Blending Unit: An Edge GPU Plug-in for Real-Time Gaussian-Based Rendering in AR/VR" being accepted to HPCA 2025!

Congratulations to Zhifan Ye, Chaojian Li, Jihoon Hong, Sixu Li, and Luke Zhang for their paper titled "3D Gaussian Can Be Sparser Than You Thought: Efficient Rendering via Learned Fragment Pruning" being accepted to NeurIPS 2024!

Congratulations to Haoran You and Yipin Guo for their paper titled "ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization" being accepted to NeurIPS 2024!

Congratulations to Yonggan Fu for his paper titled "AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment", and his collaborative paper titled "Rad-NeRF: Ray-decoupled Training of Neural Radiance Field" being accepted to NeurIPS 2024!

We are proud to celebrate our postdoc alumni Jyotikrishna Dass starting his new role as a Tenure-Track Assistant Professor in University of Arizona, Department of Electrical and Computer Engineering!

We warmly welcome our new Ph.D. colleagues: ChengJhih Shi, Dachuan Shi, Hyewon Suh, Jihoon Hong, Lex Whalen, Xiangchi Yuan, and Zhenyang Chen! We wish you all the best as you embark on this exciting journey!

Congratulations to Sixu Li for his paper titled "Fusion3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering" being accepted by MICRO 2024!

Congratulations to Yonggan Fu, Zhifan Ye, and Chaojian Li for their paper titled "Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications" being accepted as an oral paper at ECCV 2024!

Our paper titled “MG-Verilog: A Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation” won the best paper award in the First IEEE International Workshop on LLM-Aided Design (LAD 2024). Congratulations to Yongan Zhang, Zhongzhi Yu, Yonggan Fu, and Cheng Wan!

Congratulations to Chaojian for winning first places in the DAC PhD Forum of 2024!

Congratulations to Chaojian Li for being selected as one of the Machine Learning (ML) and Systems Rising Stars of 2024! He will attend the in-person ML and Systems Rising Stars workshop at Nvidia on July 15-16.

Congratulations to all our Ph.D. colleagues who have accepted their internship offers for Summer 2024!

Sixu, Zhongzhi, and Yonggan: NVIDIA; Luke: Meta; Cheng: ByteDance; Haoran: Adobe; Chaojian and Zhifan: Oak Ridge National Lab (ORNL).

Congratulations to Chaojian and Sixu for their paper titled "Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction" being selected for presentation at SRC TECHCON 2024.

Congratulations to Luke, Yonggan, and Zhongzhi for their paper titled "Data4AIGChip: An Automated Data Generation and Validation Flow for LLM-assisted Hardware Design" being selected for presentation at SRC TECHCON 2024.

Congratulations to Zhongzhi Yu and Yonggan Fu for their paper titled "Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration" being accepted by ICML 2024.

Congratulations to Haoran You for his paper titled "When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models" being accepted by ICML 2024.

Congratulations to Luke Zhang for his paper titled "AutoAI2C: An Automated Hardware Generator for DNN Acceleration on both FPGA and ASIC" being accepted by the TCAD journal.

Congratulations to Chaojian Li for being awarded 1st place at the 2024 College of Computing (CoC) Graduate Poster Symposium at GT!

Congratulations to Zhongzhi Yu for his paper titled "EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning & Voting" being accepted by DAC 2024.

Congratulations to Yujie Zhao and Yang Zhao for their paper titled "3D-Carbon: An Analytical Carbon Modeling Tool for 3D and 2.5D Integrated Circuits" being accepted by DAC 2024.

Congratulations to Luke Zhang for his paper titled "Data4AIGChip: An Automated Data Generation and Validation Flow for LLM-assisted Hardware Design" being accepted by DAC 2024.

Congratulation to Zhifan for his poster submission titled 'MarryRecon: Marry Radiance Fields and Meshes Towards Efficient 3D Reconstruction and Rendering' being accepted to NVIDIA GTC 2024!

Congratulation to Chaojian and Yonggan for their talk titled 'Dive Deep into Real-Time Neural Rendering on NVIDIA GPUs' being accepted to NVIDIA GTC 2024!

We had the honor of hosting Georgia Tech's President Angel Cabrera in our lab!

Congratulations to Haoran and Chaojian for winning first and third places in SRC@ICCAD 2023!

Congratulation to Chaojian Li for his paper titled "MixRT: Mixed Neural Representations For Real-Time NeRF Rendering" being accepted by 3DV 2024.

Congratulation to Haoran You, Huihong Shi, and Yipin Guo for their paper titled "ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer" being accepted by NeurIPS 2023.

Congratulation to Shunyao Zhang and Yonggan Fu for their paper titled "NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation" being accepted by IEEE Micro.

Congratulations to Yonggan Fu for being selected to receive the competitive IBM PhD Fellowship Award! Citing from the IBM award program: This award is highly competitive and recognizes the quality of this student's research at your institution.

Congratulations to Haoran You, Yonggan Fu, and Yang (Katie) Zhao for being selected as Machine Learning (ML) and Systems Rising Stars of 2023! They will attend the in-person ML and Systems Rising Stars workshop at Google on August 17-18.

Congratulation to Yonggan Fu*, Yongan Zhang*, and Zhongzhi Yu* for their paper titled "GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models" being accepted by ICCAD 2023.

Our demonstration titled "Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design" won second place in University Demo Best Demonstration at DAC 2023.

Congratulation to Chaojian Li for his paper titled "An Investigation on Hardware-Aware Vision Transformer Scaling" being accepted by ACM TECS Journal.

Congratulations to Yang (Katie) Zhao on joining the Department of Electrical and Computer Engineering at the University of Minnesota as a tenure-track assistant professor, starting in Spring 2024!

Congratulations to our intern Ye Yuan for being admitted to the MS program at CMU!

This is the third time that our interns have joined the MS program at CMU after Zhihan Lu / Zhanyi Sun!

Congratulations to Yang for her paper titled "i-FlatCam: A 253 FPS, 91.49 μJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR" being selected for presentation at SRC TECHCON 2023.

Congratulations to Haoran for his paper titled "ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design" being selected for presentation at SRC TECHCON 2023.

Congratulation to Yonggan Fu and Ye Yuan for their paper titled "NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations" being accepted.

Congratulation to Zhongzhi Yu and Cheng Wan for their paper titled "Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modularized Learning" being accepted.

Congratulations to Yang (Katie) Zhao for receiving the prestigious PhD thesis award called the Ralph Budd Award for Research in Engineering at Rice University!

Congratulations to Haoran You for being awarded the 1st place poster competition winner by the School of Computer Science at GT!

Congratulations to our MS student colleague @Shang Wu for being admitted to the CS PhD program at Northwestern University!

This is the fourth exciting outcome for our undergraduate/MS interns in the past one year: 1) Maki Yu was admitted to the ECE Program at Princeton and 2) Zhihan Lu / Zhanyi Sun was admitted to the CS at CMU.

Congratulation to Haoran You for being selected by the College of Computing Awards Committee to receive the Outstanding Graduate Research Assistant Award.

Congratulation to Sixu Li, Chaojian Li, and Wenbo Zhu for their paper titled "Instant-3D: Instant Neural Radiance Fields Training Towards Real-Time AR/VR 3D Reconstruction" being accepted.

Congratulation to Yonggan Fu, Zhifan Ye, and Jiayi Yuan for their paper titled "Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design" being accepted.

Congratulation to Yonggan Fu for his paper titled "Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence" being accepted.

Congratulation to Haoran You for his paper titled "Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference" being accepted.

Congratulation to Zhongzhi Yu, Shang Wu, Shunyao Zhang, and Yonggan Fu for their paper titled "Hint-Aug: Drawing Hints from Vision Foundation Models towards Boosted Few-shot Parameter-Efficient ViT Tuning" being accepted.

Congratulation to Chaojian Li, Wenwan Chen, and Jiayi Yuan for their paper titled "ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement" being accepted.

Congratulation to Yang (Katie) Zhao, Shang Wu, and Jingqun Zhang for their paper titled "Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing" being accepted.

Congratulation to Yonggan Fu and Ye Yuan for their paper titled "Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning" being accepted.

Congratulation to Zhongzhi Yu, Yonggan Fu, and Jiayi Yuan for their paper titled "NetBooster: Empowering Tiny Deep Learning By Standing on the Shoulders of Deep Giants" being accepted.

Congratulation to Zhongzhi Yu, Yonggan Fu, and Chaojian Li for their paper titled "AugViT: Improving Vision Transformer Training by Marrying Attention and Data Augmentation" being accepted.

Our EyeCoD paper, published in ISCA 2022, was selected for IEEE Micro Top Picks of 2023, which is a recognition of "the most significant research papers in computer architecture based on novelty and potential for long-term impact, published in the top computer architecture conferences of 2022"!

Congratulation to Haoran You, Cheng Wan, Yang (Katie) Zhao, Zhongzhi and more colleagues!

Congratulation to Chaojian Li, Shang Wu, Junchi Teng, and Sixu Li!

Congratulations to Haoran You, Zhanyi Sun, and Huihong Shi for their paper titled "ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design" being accepted.

Congratulations to Jyotikrishna Dass*, Shang Wu*, and Huihong Shi* for their paper titled "ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with Linear Taylor Attention" being accepted.

Congratulations to Yonggan Fu, Zhifan Ye, and Zhongzhi Yu for their paper titled "Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing" being accepted.

Congratulations to Prof. Lin for receiving two Meta Faculty Research Awards: Hardware/Software Codesign and Network for AI

Congratulations to Chaojian Li, Yang (Katie) Zhao, and Sixu Li for their paper titled "RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering" being accepted.

Congratulations to Huihong Shi and Haoran You for their paper titled "NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks" being accepted.

Our demonstration titled “i-FlatCam: A 253 FPS, 91.49 μJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR,” won first place in University Demonstration at DAC 2022.

Congratulations to Haoran You, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, and Shang Wu for their paper titled "Max-Affine Spline Insights Into Deep Network Pruning" being accepted.

Congratulations to Haoran You, Zhanyi Sun, and Xu Ouyang for their paper titled "SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning" being accepted.

Two papers are accepted to the Thirty-ninth International Conference on Machine Learning (ICML 2022).

Congratulations to Yonggan Fu, Jiayi Yuan, and Cheng Wan for their paper “DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks” being accepted.

Congratulations to Haoran You and Yonggan Fu, for their paper “ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks” being accepted.

Two papers are accepted to 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI 2022).

Congratulations to Yang (Katie) Zhao, Yonggan Fu, Luke Zhang, Chaojian Li, Cheng Wan, Haoran You, Shang Wu, and Ouyang Xu for their paper “i-FlatCam: A 253 FPS, 91.49 uJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR” being accepted.

Congratulations to Yang (Katie) Zhao, Luke Zhang, Yonggan Fu, Ouyang Xu, Cheng Wan, and Shang Wu, for their paper “e-G2C: A 0.14-to-8.31 uJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion” being accepted.

Prof. Yingyan Lin received the 2021 ACM SIGDA Outstanding Young Faculty Award.

“This award is to recognize Yingyan Lin's outstanding potential as an educator and researcher in the field of electronic design automation (EDA).”

Many thanks to EIC Lab's students and collaborators for their contributions to this recognition.

Our paper titled "EyeCoD: Eye Tracking System Acceleration via FlatCam-Based Algorithm and Accelerator Co-Design" has been accepted to ISCA 2022 with an acceptance rate of 16.7%.

Congratulations to Haoran You, Yang (Katie) Zhao, Zhongzhi Yu, Cheng Wan, Yonggan Fu, Chaojian Li, Shunyao Zhang, Yongan Zhang, Shang Wu, and Jiayi Yuan.

Our paper titled "Contrastive Quant: Quantization Makes Stronger Contrastive Learning," has been accepted to DAC 2022 with an acceptance rate of 23%.

Congratulations to Yonggan Fu, Maki Yu, and Ouyang Xu.

Our paper titled "LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference," has been accepted to the tinyML Research Symposium 2022 for a long oral presentation.

Their review score ranks 2nd among all tinyML submissions this year! Congratulations to Zhongzhi Yu and Yonggan Fu.

Congratulations to all our senior PhD colleagues who have accepted their internship offers for Summer 2022.

Yang (Katie) Zhao: NVIDIA's ASIC & VLSI Research Group led by Dr. Brucek Khailany; Chaojian Li and Haoran You: Facebook's mobile vision team; Yonggan Fu and Luke Zhang: Facebook's codec avatar team; Zhongzhi Yu: MIT-IBM Watson AI Lab; Cheng Wan: AWS's distributed large-scale training system team

Our paper titled "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling Sampling", has been accepted to MLSys 2022.

Congratulations to Cheng Wan for his paper titled "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication" being accepted.

Congratulations to Yonggan Fu, Shunyao Zhang, and Shang Wu for their paper titled "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?" being accepted.

Congratulations to Haoran You and Yonggan Fu for their paper titled "Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Ticket". being accepted

Congratulations to Zhongzhi Yu, Sicheng Li, Yonggan Fu, Mengquan Li and Chaojian Li for their paper titled "MIA-Former: Efficient and Robust Vision Transformers via Multi-grained Input-Adaptation" being accepted.

Congratulations to Haoran You and Yongan Zhang for their paper titled "GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design" being accepted by HPCA 2022.

Prof. Yingyan Lin received the 2021 IBM Faculty Award, to support her research on HW/NN co-design and co-optimization to enable energy-efficient on-device machine learning.

Congratulations to Yonggan Fu and Yue Wang for their their paper titled “SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam” being accepted by ICCV 2021.

Two papers are accepted to the 54th IEEE/ACM International Symposium on Microarchitecture (MICRO 2021) with an acceptance rate of 21%.

Congratulations to Yonggan Fu and Yang (Katie) Zhao for their paper titled "2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency" being accepted.

Congratulations to Yongan Zhang and Haoran You for their paper titled "I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization" being accepted.

Two papers are accepted to 2021 International Conference On Computer Aided Design (ICCAD 2021) with an acceptance rate of 23.5%.

Congratulations to Yongan Zhang and Haoran You for their paper titled "G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency" being accepted.

Congratulations to Mengquan Li and Zhongzhi Yu for their paper titled "O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed" being accepted.

Prof. Yingyan Lin received a Facebook Research Award, to support her research on HW/NN co-design and co-optimization to enable energy-efficient on-device machine learning.

Prof. Lin gave an invited talk at Efficient Deep Learning for Computer Vision CVPR Workshop 2021.

Congratulations to Luke Zhang and Yonggan Fu for their paper titled "RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms" being accepted.

Two papers are accepted to the Thirty-eighth International Conference on Machine Learning (ICML 2021).

Congratulations to Yonggan Fu and Luke Zhang for their paper titled "Auto-NBA: Efficient and Effective Search Over The Joint Space of Networks, Bitwidths, and Accelerators" being accepted.

Congratulations to Yonggan Fu and our undergraduate intern Maki (Qixuan) Yu for their paper titled "Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference" being accepted.

Prof. Lin gave an invited talk at Hewlett-Packard.

Yonggan Fu and Chaojian Li: Facebook AI research

Haoran You: Baidu AI research

Yongan Zhang: The high-performance-computing (HPC) group of the Pacific Northwest National Laboratory (PNNL)

Prof. Lin gave an invited talk at Rutgers University.

Prof. Lin gave an invited talk at Northeastern University.

Two of our papers have been accepted to The 58th Design Automation Conference (DAC 2021).

Congratulations to Yonggan Fu, Zhongzhi Yu, and Yongan Zhang for their paper titled “InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks" being accepted.

Congratulations to Yonggan Fu, Yongan Zhang, and Chaojian Li for their paper titled “A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning" being accepted.

Prof. Yingyan Lin won a National Science Foundation (NSF) CAREER Award, the NSF's most prestigious award in support of early-career faculty

Prof. Lin gave an invited talk at Google Research.

Two papers are accepted to The 9th International Conference on Learning Representations (ICLR 2021), both as a spotlight paper.

Congratulations to Yonggan Fu and our undergraduate intern Han Guo for their paper titled "CPT: Efficient Deep Neural Network Training via Cyclic Precision" being accepted.

Congratulations to Chaojian Li and Zhongzhi Yu for their paper titled "HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark" being accepted.

All three EIC Lab Ph.D. students, Haoran You, Yonggan Fu, and Chaojian Li, who joined in Fall 2019 with a BS degree, now have their first author ICLR spotlight papers! Congratulations.

Prof. Yingyan Lin was invited to serve as an ASAP 2021 Program Co-chair.

Prof. Yingyan Lin was invited to serve as an MLSys 2021 Technical Program Committee member.

Yang (Katie) Zhao received the 2020 Cadence Women in Technology Scholarship. Congratulations to Yang (Katie) for her impressive academic achievements and drive to shape the future of technology.

Prof. Yingyan Lin received the Career Champion Certificate from the Center for Career Development at Rice University for her efforts in advancing the mission of educating, connecting, and empowering Owls to find and make their place in the world.

Two papers are accepted to The Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020).

Congratulations to Yonggan Fu, Haoran You, Yang (Katie) Zhao, Yue Wang, and Chaojian Li for their paper titled "FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training" being accepted.

Congratulations to Haoran You, Yongan Zhang, and Chaojian Li for their paper titled "ShiftAddNet: A Hardware-Inspired Deep Network" being accepted.

Our NSF sponsored 3DML project is in the Rice News.

Congratulations to Chaojian Li and Haoran You for their Paper titled "Learning to Adapt: Towards Resource-Efficient On-Device Adaptation Beyond Gradient Descent" being accepted by ECCV 2020.

Congratulations to Yonggan Fu for his paper titled "Auto-GAN-Distiller: Searching to Compress Generative Adversarial Networks" being accepted by ICML 2020.

Congratulations to Haoran You, Yonggan Fu, and Chaojian Li.

Prof. Yingyan Lin was invited to serve as a NeurIPS 2020 Technical Program Committee member.

Prof. Yingyan Lin successfully organized the Joint Workshop on Efficient Deep Learning in Computer Vision, in conjunction with CVPR 2020.

Prof. Yingyan Lin successfully organized the UG2+ Prize Challenge Workshops, in conjunction with CVPR 2020.

Our lab's graduate students enrolled in Fall 2019 passed their Ph.D. qualifying exams with high scores.

Congratulations to Chaojian Li, Yonggan Fu, Haoran You, Luke Zhang, Anton Banta, and Yue Wang.

Prof. Yingyan Lin was invited to serve as a ICCAD 2020 Technical Program Committee member.

Congratulations to Yang (Katie) Zhao for her paper titled "Practical Deep Neural Network Attacks through Memory Trojaning" being accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Congratulations to Sicong Liu for her paper titled "AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles" being accepted by IEEE Transactions on Mobile Computing.

Our TIMELY and SmartExchange works are in the Rice News and ScienceDaily.

Prof. Yingyan Lin was invited to serve as a SECON 2020 Technical Program Committee member.

Our Early Bird work is in the Rice News and ScienceDaily.

Two papers are accepted to The 2020 IEEE/ACM International Symposium on Computer Architecture (ISCA 2020).

Congratulations to Yang (Katie) Zhao, Yue Wang, Chaojian Li and Haoran You for their paper titled “SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation“ being accepted.

Congratulations to Weitao Li, Pengfei Xu and Yang (Katie) Zhao for their paper titled “TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators towards Local and in Time Domain“ being accepted.

Congratulations to Yang (Katie) Zhao, Chaojian Li, Yue Wang, Pengfei Xu, and Yongan Zhang for their paper titled “DNN-CHIP PREDICTOR: a Multi-grained Graph-based Performance Simulator for DNN Accelerators” being accepted by ICASSP 2020.

Congratulations to Hongjie Wang (2019 summer intern at EIC lab), Yang (Katie) Zhao (equal 1st author), Chaojian Li, and Yue Wang for their paper titled “A New MRAM-Based Process In-Memory Accelerator for Efficient Neural NetworkTraining with Floating Point Precision” being accepted by IEEE International Symposium on Circuits & Systems

Prof. Lin co-chaired the “On-Device Intelligence” Workshop at the Third Conference on Machine Learning and Systems (MLSys 2020).

Congratulations to Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, and Yue Wang for their EB-Train Work being accepted by ICLR 2020 as a spotlight paper (~3%).

Prof. Yingyan Lin was invited to serve as a DAC 2020 Technical Program Committee member, in track of DES4-II. AI/ML System Design.

Congratulations to Yue and Pengfei for their paper titled “Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference” being accepted by the IEEE Journal of Selected Topics in Signal Processing.

Congratulations to Yue and Pengfei! Special thanks to Yonggan, Chaojian, and Haoran for their help in carefully proofreading the paper.

Prof. Lin co-lead the Breakout Session on “Computing Architecture for Edge Computing (CAEC)” with Dr. Yiran Chen at NSF CSR/NeTS 2019 Joint PI Meeting.

Prof. Lin gave an invited talk at ICCAD 2019.

Congratulations to Yue, Pengfei and Yang for their paper titled “E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving” being accepted by NeurIPS 2019.

Prof. Lin presented at the DARPA/NSF Real Time Machine Learning (RTML) Kickoff Meeting at the Defense Advanced Research Projects Agency (DARPA) Headquarters in Arlington, VA, to strategize on the project’s three-year arc.

EIC Lab received NIH funding to develop intelligent, personalized pacemakers: "NIH R01: Leadless Wirelessly Powered Pacemaker for Multi Chamber Pacing

Congratulations to Jianghao Shen, Yue Wang, Yonggan Fu, and Pengfei Xu for their fractional skipping work being accepted by AAAI 2020.

Congratulations to Pengfei Xu, Yang (Katie) Zhao, Luke Zhang, and Yue Wang for their AutoDNNchip work being accepted by FPGA 2020.

EIC Lab received NSF funding to develop real-time machine learning systems: "RTML Large: Harmonizing Predictive Algorithms and Mixed Signal Circuits

Prof. Lin was invited to serve on the MobiCom 2020 program committee.

EIC Lab received NSF funding to develop intelligent Internet-of-Things: “Enabling Ubiquitous Intelligent Internet-of-Eyes via a Holistic Platform, Algorithm, and Hardware Co-design”.

Prof. Yingyan Lin co-organized ODML-CDNNR workshop at ICML 2019, for which top IT companies either submitted papers or gave an invited talk, was well-received.

Yang (Katie) passed her Ph.D qualifying exam with an “A+” grade! She is one of the only two who got “A+” in the Department this year.

Congratulations to Yang (Katie).

EIC Lab received a grant from the Office of Naval Research (ONR) to develop on-chip Lensless Imager.

Thanks to the Office of Naval Research.

Four students with strong profiles accepted our PhD offers.

Welcome Chaojian, Luke, Yonggan, and Haoran.

All our current group members submitted their first first-author papers to a top-tier conference.

Congratulations to Yue, Yang, Pengfei, and Weitao.

Prof. Yingyan Lin chaired the Sessions of “Deep Learning Systems II” and “Neural Systems, Machine Learning, and Applications II” at ISCAS 2019.

Congratulations to Yang, Pengfei and Yue for their paper “Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) via Deep K-Means” being accepted by ISCAS 2019.

Dr. Lin gave invited talks at IBM China, Tsinghua, Peking, and Fudan Universities.

Prof. Lin was invited to chair the section of “High-Performance Deep Learning Accelerators on FPGAs” at ICCAD 2018.

Dr. Lin will serve on IEEE Signal Processing Society DISPS Technical Committee from Jan. 1 2019 to Dec. 31 2021

Prof. Lin was invited to serve on the GLSVLSI 2019 program committee.

Congratulations to Yue and Yang for their paper titled “EnergyNet: Energy-Efficient Dynamic Inference” being accepted by NIPS 2018 CDNNRIA Workshop.

Prof. Lin gave an invited talk at the University of Houston. Thank you Dr. Zhu Han for the invitation.

Our ASTRO project is in the news.

Our pacemaker project has been officially funded (Award # 1838873). We will develop machine learning systems for the next-generation cardiac sensing and pacing technology! [News]

Thanks to the National Science Foundation.

Prof. Lin gave an invited talk at the University of Notre Dame.

Our first NSF awarded project “NeTS: Large: Collaborative Research: DoJo: A Platform for High-Resolution Data-Driven Mobile Sensing via Networked Drones” kicked off. (Award # 1801865)

Thanks to the National Science Foundation.

Weitao and Yang (Katie) joined the EIC Lab. Welcome.

EIC Lab's proposal on efficient and intelligent distributed pacemakers recommended to be funded.

Thanks to the National Science Foundation.

Pengfei joined the EIC lab. Welcome.

Congratulations to Junru and Yue for their paper titled “Deep k-Means: Re-Training and Parameter Sharing with Hard Cluster Assignments for Compressing Deep Convolutions” being accepted by ICML 2018.

Congratulations to EIC Lab for the paper titled “ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes” being accepted by DroNet 2018.

Congratulations to Sicong for her paper titled “AdaDeep: On-Demand Deep Model Compression for Mobile Devices” being accepted by MobiSys 2018.

Congratulations to EIC Lab for the paper titled “Energy-efficient CNNs via Statistical Error Compensated Near Threshold Computing” being accepted by ISCAS 2018.

The first paper at Rice!

Yue joined the EIC lab. Welcome.