Award Abstract # 1730158

CI-New: Cognitive Hardware and Software Ecosystem Community Infrastructure (CHASE-CI)

NSF Org:CNS
Division Of Computer and Network Systems
Awardee: UNIVERSITY OF CALIFORNIA, SAN DIEGO
Initial Amendment Date:June 8, 2017
Latest Amendment Date:November 4, 2020
Award Number:1730158
Award Instrument:Standard Grant
Program Manager:Marilyn McClure
mmcclure@nsf.gov
 (703)292-5197
CNS
 Division Of Computer and Network Systems
CSE
 Direct For Computer & Info Scie & Enginr
Start Date:October 1, 2017
End Date:September 30, 2021 (Estimated)
Total Intended Award Amount:$1,000,000.00
Total Awarded Amount to Date:$1,231,998.00
Funds Obligated to Date: FY 2017 = $1,000,000.00
FY 2018 = $199,998.00

FY 2020 = $16,000.00

FY 2021 = $16,000.00
History of Investigator:
  • Larry  Smarr (Principal Investigator)
    lsmarr@ucsd.edu
  • Kenneth  Kreutz-Delgado (Co-Principal Investigator)
  • Tajana  Rosing (Co-Principal Investigator)
  • Ilkay  Altintas (Co-Principal Investigator)
  • Thomas  DeFanti (Co-Principal Investigator)
Awardee Sponsored Research Office: University of California-San Diego
Office of Contract & Grant Admin
La Jolla
CA  US  92093-0934
(858)534-4896
Sponsor Congressional District: 49
Primary Place of Performance: University of California-San Diego
9500 Gilman Drive
La Jolla
CA  US  92093-0934
Primary Place of Performance
Congressional District:
49
DUNS ID: 804355790
Parent DUNS ID: 071549000
NSF Program(s):Special Projects – CNS,
CSR-Computer Systems Research,
CCRI-CISE Cmnty Rsrch Infrstrc
Primary Program Source: 040100 NSF RESEARCH & RELATED ACTIVIT
040100 NSF RESEARCH & RELATED ACTIVIT

040100 NSF RESEARCH & RELATED ACTIVIT

040100 NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7354, 7359, 9178, 9251
Program Element Code(s): 1714, 7354, 7359
Award Agency Code:4900
Fund Agency Code:4900
CFDA Number(s):47.070

ABSTRACT

This project, called the Cognitive Hardware And Software Ecosystem Community Infrastructure (CHASE-CI), will build a cloud of hundreds of affordable Graphics Processing Units (GPUs), networked together with a variety of neural network machines to facilitate development of next generation cognitive computing. This cloud will be accessible by 30 researchers assembled from 10 universities via the NSF-funded Pacific Research Platform. These researchers will investigate a range of problems from image and video recognition, computer vision, contextual robotics to cognitive neurosciences using the cloud to be purpose-built in this project.

Training of neural network with large data-sets is best performed on GPUs. Lack of availability of affordable GPUs and lack of easy access to the new generation of Non-von Neumann (NvN) machines with embedded neural networks impede research in cognitive computing. The purpose-built cloud will be available over the network to address this bottleneck. PIs will study various Deep Neural Network, Recurrent Neural Network, and Reinforcement Learning Algorithms on this platform.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

  • Ordookhanians, Allen and Li, Xin and Nakandala, Supun and Kumar, Arun “Demonstration of Krypton: optimized CNN inference for occlusion-based deep CNN explanations” Proceedings of the VLDB Endowment , v.12 , 2019

  • Guo, Yunhui and Li, Yandong and Wang, Liqiang and Rosing, Tajana “Depthwise Convolution Is All You Need for Learning Multiple Visual Domains” Proceedings of the AAAI Conference on Artificial Intelligence , v.33 , 2019

  • Liu, Xiao and Zhou, Mingxuan and Rosing, Tajana S. and Zhao, Jishen “HR 3 AM: A Heat Resilient Design for RRAM-based Neuromorphic Computing” IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED) , 2019
  • Morris, Justin and Imani, Mohsen and Bosch, Samuel and Thomas, Anthony and Shu, Helen and Rosing, Tajana “CompHD: Efficient Hyperdimensional Computing Using Model Compression” IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED) , 2019
  • Yhdego, Haben and Li, Jiang and Morrison, Steven and Audette, Michel and Paolini, Christopher and Sarkar, Mahasweta and Okhravi, Hamid “Towards Musculoskeletal Simulation-Aware Fall Injury Mitigation: Transfer Learning with Deep CNN for Fall Detection” 2019 Spring Simulation Conference (SpringSim) , 2019
  • M. Imani, S. Gupta “FloatPIM: In-Memory Acceleration of Deep Neural Network Training with High Precision” 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA) , 2019
  • Nakandala, S. “Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations” Proceedings of the 2019 International Conference on Management of Data , 2019
  • Yunhui Guo, Honghui Shi “SpotTune: Transfer Learning through Adaptive Fine-tuning” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2019
  • Das, Srinjoy and Politis, Dimitris N. “Predictive Inference for Locally Stationary Time Series With an Application to Climate Data” Journal of the American Statistical Association , 2020
  • Fang, Zhou and Hong, Dezhi and Gupta, Rajesh K. “Serving deep neural networks at the cloud edge for vision applications on mobile platforms” ACM Multimedia Systems Conference (MMSys) 2019 , 2019
  • Paolini, Christopher and Adigal, Hrishikesh and Sarkar, Mahasweta “Upper Bound on LoRa Smart Metering Uplink Rate” IEEE Consumer Communications and Networking Conference (CCNC 2020) , 2020
  • 133. He, X. “PathVQA: 30000+ Questions for Medical Visual Question Answering” ArXivorg , v.2003.10 , 2020
  • 132. He, X. “Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans” IEEE transactions on medical imaging , 2020
  • H. Nejatollahi, S. Gupta “CryptoPIM: In-Memory Acceleration for RLWE Lattice-based Cryptography” Design Automation Conference (DAC), 2020. , 2020
  • Rajkumar, Utkrisht and Turner, Kristen and Luebeck, Jens and Deshpande, Viraj and Chandraker, Manmohan and Mischel, Paul and Bafna, Vineet “EcSeg: Semantic Segmentation of Metaphase Images Containing Extrachromosomal DNA” iScience , v.21 , 2019
  • Ostertag, Michael and Atanasov, Nikolay and Rosing, Tajana “Robust Velocity Control for Minimum Steady State Uncertainty in Persistent Monitoring Applications” 2019 Annual American Controls Conferene (ACC) , 2019
  • Gupta, Saransh and Imani, Mohsen and Khaleghi, Behnam and Kumar, Venkatesh and Rosing, Tajana “RAPID: A ReRAM Processing in-Memory Architecture for DNA Sequence Alignment” International Symposium on Low Power Electronics and Design (ISLPED) 2019 , 2019
  • Imani, Mohsen and Gupta, Saransh and Kim, Yeseong and Zhou, Minxuan and Rosing, Tajana “DigitalPIM: Digital-based Processing In-Memory for Big Data Acceleration” ACM Great Lakes Symposium on VLSI (GLSVLSI) 2019 , 2019
  • Imani, Mohsen and Messerly, John and Wu, Fan and Pi, Wang and Rosing, Tajana “A Binary Learning Framework for Hyperdimensional Computing” IEEE/ACM Design Automation and Test in Europe Conference (DATE) , 2019
  • Khaleghi, Behnam and Rosing, Tajana Simunic “Thermal-Aware Design and Flow for FPGA Performance Improvement” IEEE/ACM Design Automation and Test in Europe (DATE) Conference 2019 , 2019
  • Sim, Joonseop and Kim, Minsu and Kim, Yeseong and Gupta, Saransh and Khaleghi, Behnam and Rosing, Tajana “MAPIM: Mat Parallelism for High Performance Processing in Non-volatile Memory Architecture” IEEE International Symposium on Quality Electronic Design (ISQED) 2019 , 2019
  • Kim, Yeseong and More, Ankit and Shriver, Emily and Rosing, Tajana “Application Performance Prediction and Optimization Under Cache Allocation Technology” IEEE/ACM Design Automation and Test in Europe (DATE) Conference 2019 , 2019
  • Gupta, Saransh and Imani, Mohsen and Sim, Joonseop and Huang, Andrew and Wu, Fan and Najafi, M. Hassan and Rosing, Tajana “SCRIMP: A General Stochastic Computing Architecture using ReRAM in-Memory Processing” Design Automation Conference 2020 , 2020
  • Kim, Yeseong and Imani, Mohsen and Moshiri, Niema and Rosing, Tajana “GenieHD: Efficient DNA Pattern Matching Accelerator Using Hyperdimensional Computing” 2020 Design, Automation, and Test in Europe Conference (DATE 2020) , 2020
  • Imani, Mohsen and Samragh Razlighi, Mohammad and Kim, Yeseong and Gupta, Saransh and Koushanfar, Farinaz and Rosing, Tajana “Deep Learning Acceleration with Neuron-to-Memory Transformation” 26th IEEE International Symposium on High-Performance Computer Architecture , 2020
  • Imani, Mohsen and Morris, Justin and Bosch, Samuel and Shu, Helen and Micheli, Giovanni De and Rosing, Tajana “AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing” 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS) , 2019
  • Imani, Mohsen and Gupta, Saransh and Rosing, Tajana “Digital-based processing in-memory: a highly-parallel accelerator for data intensive applications” ACM International Symposium on Memory Systems (MEMSYS) 2019 , 2019
  • Imani, Mohsen and Kim, Yeseong and Riazi, Sadegh and Messerly, John and Liu, Patric and Koushanfar, Farinaz and Rosing, Tajana “A Framework for Collaborative Learning in Secure High-Dimensional Space” IEEE Cloud Computing (CLOUD) 2019 , 2019
  • Chandrasekaran, Rishikanth and Guo, Yunhui and Thomas, Anthony and Menarini, Massimiliano and Ostertag, Michael H. and Kim, Yeseong and Rosing, Tajana “Efficient Sparse Processing in Smart Home Applications” 18th ACM Conference on Embedded Networked Sensor Systems , 2019
  • Imani, Mohsen and Morris, Justin and Messerly, John and Shu, Helen and Deng, Yaobang and Rosing, Tajana “BRIC: Locality-based Encoding for Energy-Efficient Brain-Inspired Hyperdimensional Computing” IEEE/ACM Design Automation Conference (DAC) , 2019
  • Imani, Mohsen and Gupta, Saransh and Rosing, Tajana “GenPIM: Generalized processing in-memory to accelerate data intensive applications” IEEE/ACM Design Automation and Test in Europe Conference (DATE) 2018 , 2018
  • Kahng, Andrew B. and Mallappa, Uday and Saul, Lawrence and Tong, Shangyuan “”Unobserved Corner” Prediction: Reducing Timing Analysis Effort for Faster Design Convergence in Advanced-Node Design” Proceedings of Design, Automation and Test in Europe (DATE) Conference , 2019
  • Kahng, Andrew B. and Kang, Seokhyeong and Kim, Seungwon and Samadi, Kambiz and Xu, Bangqi “Power Delivery Pathfinding for Emerging Die-to-Wafer Integration Technology” Proceedings of Design, Automation and Test in Europe (DATE) Conference , 2019
  • Heo, Sun ik and Kahng, Andrew B. and Kim, Minsoo and Wang, Lutong “Diffusion break-aware leakage power optimization and detailed placement in sub-10nm VLSI” Proceedings of the Asia and South Pacific Design Automation Conference , 2019
  • Fogaça, Mateus and Kahng, Andrew B. and Reis, Ricardo and Wang, Lutong “Finding placement-relevant clusters with fast modularity-based clustering” Proceedings of the Asia and South Pacific Design Automation Conference , 2019
  • Fatemi, Hamed and Kahng, Andrew B. and Lee, Hyein and de Gyvez, Jose Pineda “Heuristic Methods for Fine-Grain Exploitation of FDSOI” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2019
  • 169. Y. Cao, J. Li “Learning-Based Prediction of Package Power Delivery Network Quality” Proceedings of the Asia and South Pacific Design Automation Conference , 2019
  • 175. T. Ajayi, D. Blaauw “OpenROAD: Toward a Self-Driving, Open-Source Digital Layout Implementation Tool Chain” Proceedings of Government Microcircuit Applications and Critical Technology Conference , 2019
  • Alexandari, A. “Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat atLabel Shift Adaptation” ArXivorg , v.1901.06 , 2019
  • Nguyen, Mai H. and Block, Jessica and Crawl, Daniel and Siu, Vincent and Bhatnagar, Akshit and Rodriguez, Federico and Kwan, Alison and Baru, Namrita and Altintas, Ilkay “Land Cover Classification at the Wildland Urban Interface using High-Resolution Satellite Imagery and Deep Learning” IEEE International Conference on Big Data (Big Data) , 2018
  • Nguyen, Mai H. and Altintas, Ilkay and Muse, Evan D. and Quer, Giorgio and Steinhubl, Steven and Abdelmaguid, Ehab and Huang, Jolene and Kenchareddy, Sanjay and Singla, Disha and Wilke, Laura and Bobar, Marcus and Carruth, Eric D. and Uys, Dylan “Analytics pipeline for left ventricle segmentation and volume estimation on cardiac MRI using deep learning” IEEE 14th International Conference on e-Science (e-Science) , 2018
  • Kahng, Andrew B. “Machine Learning Applications in Physical Design: Recent Results and Directions” Proceedings of ACM/IEEE International Symposium on Physical Design , 2018
  • Avsec, Ž. “Kipoi: accelerating the community exchange and reuse of predictive models for genomics” ICML Workshop for Computational Biology , 2018
  • Han, Kwangsoo and Kahng, Andrew B. and Li, Jiajia “Optimal Generalized H-Tree Topology and Buffering for High-Performance and Low-Power Clock Distribution” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , v.39 , 2020
  • Coskun, Ayse and Eris, Furkan and Joshi, Ajay and Kahng, Andrew B. and Ma, Yenai and Narayan, Aditya and Srinivas, Vaishnav “Cross-Layer Co-Optimization of Network Design and Chiplet Placement in 2.5D Systems” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2020
  • Kahng, Andrew B. and Wang, Lutong and Xu, Bangqi “TritonRoute: The Open Source Detailed Router” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2020
  • Chhabria, Vidya A. and Kahng, Andrew B. and Kim, Minsoo and Mallappa, Uday and Sapatnekar, Sachin S. and Xu, Bangqi “Template-based PDN Synthesis in Floorplan and Placement Using Classifier and CNN Techniques” Proceedings of Asia and South Pacific Design Automation Conference , 2020
  • Cheng, S. “Deep stereo using adaptive thin volume representation with uncertainty awareness” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2020
  • Alipour, K. “A Study on Multimodal and Interactive Explanations for Visual Question Answering” ArXivorg , v.2003.00 , 2020
  • 189. Jia, Zhiwei “Information-Theoretic Local Minima Characterization and Regularization” International Conference on Machine Learning , 2020
  • 190. Ruihan Yang, Huazhe Xu “Multi-Task Reinforcement Learning with Soft Modularization” ArXivorg , v.2003.13 , 2020
  • Ros-Giralt, Jordi and Bohara, Atul and Yellamraju, Sruthi and Langston, M. Harper and Lethin, Richard and Jiang, Yuang and Tassiulas, Leandros and Li, Josie and Tan, Yuanlong and Veeraraghavan, Malathi “On the Bottleneck Structure of Congestion-Controlled Networks” Proceedings of the ACM on Measurement and Analysis of Computing Systems , v.3 , 2019
  • Potapov, Alexander and Colbert, Ian and Kreutz-Delgado, Ken and Cloninger, Alexander and Das, Srinjoy “PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems” 2019 53rd Asilomar Conference on Signals, Systems, and Computers , 2019
  • Han, Changho and Kahng, Andrew B. and Wang, Lutong and Xu, Bangqi “Enhanced Optimal Multi-Row Detailed Placement for Neighbor Diffusion Effect Mitigation in Sub-10 nm VLSI” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , v.38 , 2019
  • Ajayi, Tutu and Chhabria, Vidya A. and Fogaça, Mateus and Hashemi, Soheil and Hosny, Abdelrahman and Kahng, Andrew B. and Kim, Minsoo and Lee, Jeongsup and Mallappa, Uday and Neseem, Marina and Pradipta, Geraldo and Reda, Sherief and Saligane, Mehdi and S “Toward an Open-Source Digital Flow: First Learnings from the OpenROAD Project” Proceedings of ACM/IEEE Design Automation Conference , 2019
  • Avsec, Žiga and Kreuzhuber, Roman and Israeli, Johnny and Xu, Nancy and Cheng, Jun and Shrikumar, Avanti and Banerjee, Abhimanyu and Kim, Daniel S. and Beier, Thorsten and Urban, Lara and Kundaje, Anshul and Stegle, Oliver and Gagneur, Julien “The Kipoi repository accelerates community exchange and reuse of predictive models for genomics” Nature Biotechnology , v.37 , 2019
  • Heo, Sun ik and Kahng, Andrew B. and Kim, Minsoo and Wang, Lutong and Yang, Chutong “Detailed Placement for IR Drop Mitigation by Power Staple Insertion in Sub-10nm VLSI” Proceedings of Design, Automation and Test in Europe (DATE) Conference , 2019
  • Hariri, Ali and Alipour, Kamran and Mantri, Yash and Schulze, Jurgen P. and Jokerst, Jesse V. “Deep learning improves contrast in low-fluence photoacoustic imaging” Biomedical Optics Express , v.11 , 2020
  • Imani, Mohsen and Kim, Yeseong and Worley, Thomas and Gupta, Saransh and Rosing, Tajana “HDCluster: An Accurate Clustering Using Brain-Inspired High-Dimensional Computing” IEEE/ACM Design Automation and Test in Europe Conference , 2019
  • Imani M., Samragh M. “RAPIDNN: In-memory deep neural network acceleration framwork.” ArXiv.org , 2019
  • Gupta, Saransh and Imani, Mohsen and Kaur, Harveen and Rosing, Tajana Simunic “NNPIM: A Processing In-Memory Architecture for Neural Network Acceleration” IEEE Transactions on Computers , 2019
  • Imani, Mohsen and Morris, Justin and Shu, Helen and Li, Shou and Rosing, Tajana “Efficient Associative Search in Brain-Inspired Hyperdimensional Computing” IEEE Design & Test , 2019
  • Imani, Mohsen and Salamat, Sahand and Khaleghi, Behnam and Samragh, Mohammad and Koushanfar, Farinaz and Rosing, Tajana “SparseHD: Algorithm-Hardware Co-optimization for Efficient High-Dimensional Computing” IEEE International Symposium on Field-Programmable Cusstom Computing Machines (FCCM) , 2019
  • Wang, Weijia and Lin, Bill “Trained Biased Number Representation for ReRAM-Based Neural Network Accelerators” ACM Journal on Emerging Technologies in Computing Systems , v.15 , 2019
  • Imani, Mohsen and Garcia, Ricardo and Gupta, Saransh and Rosing, Tajana “Hardware-Software Co-design to Accelerate Neural Network Applications” ACM Journal on Emerging Technologies in Computing Systems , v.15 , 2019
  • Thomas, Anthony and Guo, Yunhui and Kim, Yeseong and Aksanli, Baris and Kumar, Arun and Rosing, Tajana S. “Hierarchical and Distributed Machine Learning Inference Beyond the Edge” 16th Annual IEEE Conference on Networking, Sensing, and Control , 2019
  • Das, Srinjoy and Politis, Dimitris N. “Nonparametric Estimation of the Conditional Distribution at Regression Boundary Points” The American Statistician , 2019
  • Kim, Yeseong and Imani, Mohsen and Rosing, Tajana “ORCHARD: Visual object recognition accelerator based on approximate in-memory processing” International Conference on Computer-Aided Design (ICCAD) 2017 , 2017
  • Imani, Mohsen and Huang, Chenyu and Kong, Deqian and Rosing, Tajana “Hierarchical hyperdimensional computing for energy efficient classification” Proceedings of the 55th Annual Design Automation Conference 2018 , 2018
  • Imani, Mohsen and Masich, Max and Peroni, Daniel and Wang, Pushen and Rosing, Tajana “CANNA: Neural network acceleration using configurable approximation on GPGPU” IEEE Asia and South Pacific Design Automation Conference 2018 , 2018 
  • Sim, Joonseop and Imani, Mohsen and Choi, Woojin and Kim, Yeseong and Rosing, Tajana “LUPIS: Latch-up based ultra efficient processing in-memory system” IEEE International Symposium on Quality Electronic Design 2018 , 2018
  • Zhou, Minxuan and Imani, Mohsen and Gupta, Saransh and Rosing, Tajana “Thermal-Aware Design and Management for Search-based In-Memory Acceleration” IEEE/ACM Design Automation Conference , 2019
  • Colbert I., Kreutz-Delgado K. “AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks” ArXiv.org , 2019
  • Imani, Mohsen and Wang, Pushen and Rosing, Tajana “Deep neural network acceleration framework under hardware uncertainty” IEEE International Symposium on Quality Electronic Design 2018 , 2018
  • Imani, Mohsen and Peroni, Daniel and Rosing, Tajana “Program acceleration using nearest distance associative search” IEEE International Symposium on Quality Electronic Design 2018 , 2018
  • Imani, Mohsen and Gupta, Saransh and Sharma, Sahil and Rosing, Tajana “NVQuery: Efficient Query Processing in Non-Volatile Memory” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2018
  • Imani, Mohsen and Nassar, Tarek and Rahimi, Abbas and Rosing, Tajana “HDNA: Energy-efficient DNA sequencing using hyperdimensional computing” IEEE International Conference on Biomedical and Health Informatics 2018 , 2018
  • Gupta, Saransh and Imani, Mohsen and Rosing, Tajana “FELIX: fast and energy-efficient logic in memory” IEEE/ACM International Conference on Computer Aided Design , 2018
  • Salamat, Sahand and Imani, Mohsen and Gupta, Sarangh and Rosing, Tajana “RNSnet: In-Memory Neural Network Acceleration Using Residue Number System” IEEE International Conference on Rebooting Computing , 2018
  • Peroni, Daniel and Imani, Mohsen and Nejatollahi, Hamid and Dutt, Nikil and Rosing, Tajana “ARGA: Approximate Reuse for GPGPU Acceleration” IEEE/ACM Design Automation Conference (DAC) , 2019
  • Imani, Mohsen and Salamat, Sahand and Gupta, Saransh and Huang, Jiani and Rosing, Tajana “FACH: FPGA-based acceleration of hyperdimensional computing by reducing computational complexity” IEEE Asia and South Pacific Design Automation Conference , 2019
  • Zhou, Minxuan and Imani, Mohsen and Gupta, Saransh and Kim, Yeseong and Rosing, Tajana “GRAM: graph processing in a ReRAM-based computational memory” IEEE Asia and South Pacific Design Automation Conference , 2019
  • Sim, Joonseop and Gupta, Saransh and Imani, Mohsen and Kim, Yeseong and Rosing, Tajana “UPIM: Unipolar Switching Logic for High Density Processing-in-Memory Applications” ACM Great Lakes Symposium on VLSI , 2019 10
  • Imani, Mohsen and Garcia, Ricardo and Gupta, Saransh and Rosing, Tajana “RMAC: Runtime Configurable Floating Point Multiplier for Approximate Computing” ACM International Symposium on Low Power Electronics and Design , 2018
  • Salamat, Sahand and Imani, Mohsen and Khaleghi, Behnam and Rosing, Tajana “F5-HD: Fast Flexible FPGA-based Framework for Refreshing Hyperdimensional Computing” ACM/SIGDA International Symposium on Field-Programmable Gate Arrays , 2019
  • Kim, Yeseong and Imani, Mohsen and Rosing, Tajana Simunic “Image Recognition Accelerator Design Using In-Memory Processing” IEEE Micro , v.39 , 2019
  • Peroni, Daniel and Imani, Mohsen and Rosing, Tajana “Runtime Efficiency-Accuracy Trade-off Using Configurable Floating Point Multiplier” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2018
  • Shin, D. “Multi-layer Depth and Epipolar Feature Transformers for 3D Scene Reconstruction.” ArXiv.org , 2019
  • Peroni, Daniel and Imani, Mohsen and Rosing, Tajana “ALook: adaptive lookup for GPGPU acceleration” IEEE Asia and South Pacific Design Automation Conference , 2019
  • Imani, Mohsen and Garcia, Ricardo and Huang, Andrew and Rosing, Tajana “CADE: Configurable Approximate Divider for Energy Efficiency” IEEE/ACM Design Automation and Test in Europe Conference (DATE) , 2019
  • Imani, Mohsen and Sokolova, Alice and Garcia, Ricardo and Huang, Andrew and Wu, Fan and Aksanli, Baris and Rosing, Tajana “ApproxLP: Approximate Multiplication with Linearization and Iterative Error Control” IEEE/ACM Design Automation Conference , 2019
  • Gupta, Saransh and Imani, Mohsen and Rosing, Tajana “Exploring Processing In-Memory for Different Technologies” ACM Great Lakes Symposium on VLSI , 2019
  • Benz, Susanne and Park, Hogeun and Li, Jiaxin and Crawl, Daniel and Block, Jessica and Nguyen, Mai and Altintas, Ilkay “Understanding a Rapidly Expanding Refugee Camp Using Convolutional Neural Networks and Satellite Imagery” 15th International Conference on eScience (eScience) , 2019 
  • Paolini, Christopher and Soselia, Davit and Baweja, Harsimran and Sarkar, Mahasweta “Optimal Location for Fall Detection Edge Inferencing” IEEE GLOBECOM 2019 , 2019
  • Fatemi, Hamed and Kahng, Andrew B. and Lee, Hyein and Li, Jiajia and Pineda de Gyvez, Jose “Enhancing sensitivity-based power reduction for an industry IC design context” Integration , v.66 , 2019
  • Nair, Surag and Kim, Daniel S and Perricone, Jacob and Kundaje, Anshul “Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts” Bioinformatics , v.35 , 2019