Toward the National Research Platform

Award Abstract # 1826967

CC* NPEO: Toward the National Research Platform

NSF Org:
Office of Advanced Cyberinfrastructure (OAC)
Awardee: UNIVERSITY OF CALIFORNIA, SAN DIEGO
Initial Amendment Date:September 12, 2018
Latest Amendment Date:May 7, 2021
Award Number:1826967
Award Instrument:Standard Grant
Program Manager:Kevin Thompson
kthompso@nsf.gov  (703)292-4220
OAC  Office of Advanced Cyberinfrastructure (OAC)
CSE  Direct For Computer & Info Scie & Enginr
Start Date:October 1, 2018
End Date:September 30, 2022 (Estimated)
Total Intended Award Amount:$2,500,000.00
Total Awarded Amount to Date:$2,532,000.00
Funds Obligated to Date: FY 2018 = $2,500,000.00
FY 2019 = $16,000.00
FY 2021 = $16,000.00
History of Investigator:
  • Larry  Smarr (Principal Investigator)
     lsmarr@ucsd.edu  
  • Philip  Papadopoulos (Co-Principal Investigator)
  • Frank  Wuerthwein (Co-Principal Investigator)
  • Tajana  Rosing (Co-Principal Investigator)
  • Ilkay  Altintas (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):Campus Cyberinfrastructure
Primary Program Source: 040100 NSF RESEARCH & RELATED ACTIVIT
040100 NSF RESEARCH & RELATED ACTIVIT
040100 NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9251
Program Element Code(s): 8080
Award Agency Code:4900
Fund Agency Code:4900
CFDA Number(s):47.070

ABSTRACT

Academic researchers need a simple data sharing architecture with end-to-end 10-to-100Gbps performance to enable virtual co-location of large amounts of data with computing. End-to-end is a difficult problem to solve in general because the networks between ends (campuses, data repositories, etc.) typically traverse multiple network management domains: campus, regional, and national. No one organization owns the responsibility for providing scientists with high-bandwidth disk-to-disk performance. Toward the National Research Platform (TNRP), addresses issues critical to scaling end-to-end data sharing. TNRP will instrument a large federation of heterogeneous “national-regional-state” networks (NRSNs) to greatly improve end-to-end network performance across the nation.

The goal of improving end-to-end network performance across the nation requires active participation of these distributed intermediate-level entities to reach out to their campuses. They are trusted conveners of their member institutions, contributing effectively to the “people networking” that is as necessary to the development of a full National Research Platform as is the stability, deployment, and performance of technology. TNRP’s collaborating NRSNs structure leads to engagement of a large set of science applications, identified by the participating NRSNs and the Open Science Grid.

TNRP is highly instrumented to directly measure performance. Visualizations of disk-to-disk performance with passive and active network monitoring show intra- and inter-NSRN end-to-end performance. Internet2, critical for interconnecting regional networks, will provide an instrumented dedicated virtual network instance for the interconnection of TNRP’s NRSNs. Cybersecurity is a continuing concern; evaluations of advanced containerized orchestration, hardware crypto engines, and novel IPv6 strategies are part of the TNRP plan.

This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.

 PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

  • Zhu, Shilin and Xu, Zexiang and Jensen, Henrik Wann and Su, Hao and Ramamoorthi, Ravi “Deep Kernel Density Estimation for Photon Mapping” Computer Graphics Forum , v.39 , 2020
  • Li, J. “Multi-task Batch Reinforcement Learning with Metric Learning” ArXivorg , 2020

  • Ho, C. H. “Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object Recognition” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2020 

  • Ho, C. H. “Contrastive Learning with Adversarial Examples” ArXivorg , 2020 

  • Wu, T. Y. “Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier” European Conference on Computer Vision , 2020 

  • Xu, Y. “Explainable Object-induced Action Decision for Autonomous Vehicles” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2020 

  • Hansen, N. “Self-Supervised Policy Adaptation during Deployment” ArXivorg , 2020 

  • Zhang, Q. “Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency” ArXivorg , 2020 

  • Hansen, N. and “Generalization in Reinforcement Learning by Soft Data Augmentation” ArXivorg , 2020 

  • Tang, H. “Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks” ArXivorg , 2020 

  • Morgado, P. “Learning Representations from Audio-Visual Spatial Alignment” ArXivorg , 2020 

  • Zhou, M. “Self-supervised Regularization for Text Classification” Transactions on Association of Computational Linguistics (TACL) , 2021 

  • 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 

  • Guo, Y. “Spottune: transfer learning through adaptive fine-tuning” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 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 

  • 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 

  • 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

  • Gupta, Saransh and Imani, Mohsen and Rosing, Tajana “Exploring Processing In-Memory for Different Technologies” ACM Great Lakes Symposium on VLSI , 2019 

  • Altintas I., Marcus K. “Workflow-Driven Distributed Machine Learning in CHASE-CI: A Cognitive Hardware and Software Ecosystem Community Infrastructure” 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

  • Das, Srinjoy and Politis, Dimitris N. “Nonparametric Estimation of the Conditional Distribution at Regression Boundary Points” The American Statistician , 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 

  • 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 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 Huang, Chenyu and Kong, Deqian and Rosing, Tajana “Hierarchical Hyperdimensional Computing for Energy Efficient Classification” IEEE/ACM Design Automation Conference , 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 

  • 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 

  • 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 

  • Nakandala, Supun and Zhang, Yuhao and Kumar, Arun “Cerebro: Efficient and Reproducible Model Selection on Deep Learning Systems” ACM SIGMOD Workshop on Data Management for End-to-End Machine Learning (DEEM) , 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 

  • 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 

  • Peroni, Daniel and Imani, Mohsen and Rosing, Tajana “ALook: adaptive lookup for GPGPU acceleration” IEEE Asia and South Pacific Design Automation Conference , 2019 

  • Imani M., Saransh G. “FloatPIM: in-memory acceleration of deep neural network training with high precision” IEEE International Symposium on Computer Architecture (ISCA) , 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 

  • 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 

  • 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 

  • 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

  • Imani M., Samragh M. “RAPIDNN: In-Memory Deep Neural Network Acceleration Framework” ArXiv.org , 2018

  • Kim, Yeseong and Imani, Mohsen and Rosing, Tajana Simunic “Image Recognition Accelerator Design Using In-Memory Processing” IEEE Micro , v.39 , 2019

  • Varma, Girish and Subramanian, Anbumani and Namboodiri, Anoop and Chandraker, Manmohan and Jawahar, C.V. “IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments” IEEE Winter Conference on Applications of Computer Vision (WACV) , 2019 

  • Stets, Jonathan and Li, Zhengqin and Frisvad, Jeppe Revall and Chandraker, Manmohan “Single-Shot Analysis of Refractive Shape Using Convolutional Neural Networks” IEEE Winter Conference on Applications of Computer Vision (WACV) , 2019 

  • 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 

  • Li, Zhengqin and Xu, Zexiang and Ramamoorthi, Ravi and Sunkavalli, Kalyan and Chandraker, Manmohan “Learning to reconstruct shape and spatially-varying reflectance from a single image” ACM Transactions on Graphics , v.37 , 2019 

  • 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, 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 

  • Zhang, M. “Server-Aided 3D DICOM Viewer for Mobile Platforms” Electronic imaging , v.2021 , 2021

  • Feng, Qiaojun and Atanasov, Nikolay “Fully Convolutional Geometric Features for Category-level Object Alignment” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020 

  • Shan, Mo and Feng, Qiaojun and Atanasov, Nikolay “OrcVIO: Object residual constrained Visual-Inertial Odometry” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020 

  • Alipour, Kamran and Ray, Arijit and Lin, Xiao and Schulze, Jurgen P. and Yao, Yi and Burachas, Giedrius T. “The Impact of Explanations on AI Competency Prediction in VQA” 2020 IEEE International Conference on Humanized Computing and Communication with Artificial Intelligence (HCCAI) , 2020 

  • Sfiligoi, Igor and Schultz, David and Riedel, Benedikt and Wuerthwein, Frank and Barnet, Steve and Brik, Vladimir “Demonstrating a Pre-Exascale, Cost-Effective Multi-Cloud Environment for Scientific Computing: Producing a fp32 ExaFLOP hour worth of IceCube simulation data in a single workday” PEARC ’20: Practice and Experience in Advanced Research Computing , 2020 

  • Sfiligoi, Igor “Demonstrating 100 Gbps in and out of the public Clouds” Practice and Experience in Advanced Research Computing (PEARC20) , 2020 

  • Sfiligoi, Igor and McDonald, Daniel and Knight, Rob “Porting and optimizing UniFrac for GPUs: Reducing microbiome analysis runtimes by orders of magnitude” Practice and Experience in Advanced Research Computing (PEARC20) , 2020 

  • 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 

  • Wang, Tianyu and Dhiman, Vikas and Atanasov, Nikolay “Learning Navigation Costs from Demonstration in Partially Observable Environments” 2020 IEEE International Conference on Robotics and Automation (ICRA) , 2020

  • Li, Z. “Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2020 

  • Luebeck, J. “AmpliconReconstructor: Integrated analysis of NGS and optical mapping resolves the complex structures of focal amplifications in cancer” bioRxiv , 2020 

  • Wang, T. “Learning Navigation Costs from Demonstrations with Semantic Observations, Learning for Dynamics and Control” Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR , v.120 , 2020 

  • He, X. “Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans” medrxiv , 2020 

  • He, X. “PathVQA: 30000+ Questions for Medical Visual Question Answering.” ArXivorg , 2020

  • Alipour, K. “A Study on Multimodal and Interactive Explanations for Visual Question Answering” ArXivorg , 2020

  • Haberl, M.G. “CDeep3M-Preview: Online segmentation using the deep neural network model zoo” bioRxiv , 2020

  • Yang, R. “Multi-Task Reinforcement Learning with Soft Modularization” ArXivorg , 2020

  • Yang, W. “On the Generation of Medical Dialogues for COVID-19” ArXivorg , 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

  • Jia, Z. and “Information-Theoretic Local Minima Characterization and Regularization” Proceedings of the 37th International Conference on Machine Learning , v.119 , 2020 

  • 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 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

  • 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 

  • Gupta, Saransh and Morris, Justin and Imani, Mohsen and Ramkumar, Ranganathan and Yu, Jeffrey and Tiwari, Aniket and Aksanli, Baris and Rosing, Tajana Šimunić “THRIFTY: training with hyperdimensional computing across flash hierarchy” 2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD) , 2020
  • Jau, You-Yi and Zhu, Rui and Su, Hao and Chandraker, Manmohan “Deep Keypoint-Based Camera Pose Estimation with Geometric Constraints” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020 

  • Bang, S. “Explaining Black-box Models Using A Deep Variational Information Bottleneck Approach” ArXivorg , 2020

  • Zeng, G. “MedDialog: Large-scale Medical Dialogue Dataset” Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , 2020 

  • Xie, P. “Skillearn: Machine Learning Inspired by Humans’ Learning Skills” ArXivorg , 2020

  • Song, C. “Generalized Zero-shot ICD Coding” ArXivorg , 2020 

  • Du, X. “Learning by Passing Tests, with Application to Neural Architecture Search” ArXivorg , 2020

  • 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 

  • 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 

  • Kim, Yeseong and Imani, Mohsen and Rosing, Tajana S. “Efficient human activity recognition using hyperdimensional computing” IEEE Conference on Internet of Things (Hil-IoT) , 2018 

  • Ostertag, Michael H. and Al-Doweesh, Sarah and Rosing, Tajana “Efficient Training on Edge Devices Using Online Quantization” Design, Automation and Test in Europe Conference (DATE) , 2020
  • Chen, Rui and Han, Songfang and Xu, Jing and su, hao “Visibility-Aware Point-Based Multi-View Stereo Network” IEEE Transactions on Pattern Analysis and Machine Intelligence , 2020
  • Hosseini, R. and “. Learning by Self-Explanation, with Application to Neural Architecture Search” ArXivorg , 2020 

  • Alipour, K. “A study on multimodal and interactive explanations for visual question answering” ArXivorg , 2020 

  • Guo, Y. “Adafilter: Adaptive filter fine-tuning for deep transfer learning.” Proceedings of the AAAI Conference on Artificial Intelligence , v.34 , 2020 

  • Guo, Y. “A broader study of cross-domain few-shot learning” European Conference on Computer Vision , 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 

  • Kusupati, U. “Normal Assisted Stereo Depth Estimation”, Computer Vision and Pattern Recognition” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2020

  • Mu, T. “Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals” ArXivorg , 2020

  • Liu, M. “Meshing point clouds with predicted intrinsic-extrinsic ratio guidance” European Conference on Computer Vision , 2020 

  • Liang, Zhijin and Zhang, Junkang and An, Cheolhong “Foveal Avascular Zone Segmentation of Octa Images Using Deep Learning Approach with Unsupervised Vessel Segmentation” ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2021
  • Strawson, James and Cao, Pengcheng and Bewley, Thomas and Kuester, Falko “Rotor Orientation Optimization for Direct 6 Degree of Freedom Control of Multirotors” 2021 IEEE Aerospace Conference (50100) , 2021 

  • Gupta, Saransh and Imani, Mohsen and Zhao, Hengyu and Wu, Fan and Zhao, Jishen and Rosing, Tajana Šimunić “Implementing binary neural networks in memory with approximate accumulation” Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design , 2020

  • 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 

  • Xie, F. “Deep Imitation Learning for Bimanual Robotic Manipulation” ArXivorg , 2020 

  • 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

  • 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 

  • 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 

  • Sfiligoi, I. “, 2020. Running a Pre-Exascale, Geographically Distributed, Multi-Cloud Scientific Simulation.” Proceedings of ISC High Performance 2020 , 2020

  • 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 

  • 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 

  • 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 

  • 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 

  • 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
  • Imani, Mohsen and Yin, Xunzhao and Messerly, John and Gupta, Saransh and Niemier, Michael and Hu, Xiaobo Sharon and Rosing, Tajana “SearcHD: A Memory-Centric Hyperdimensional Computing with Stochastic Training” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 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 

  • Imani, Mohsen and Bosch, Samuel and Datta, Sohum and Ramakrishna, Sharadhi and Salamat, Sahand and Rabaey, Jan M. and Rosing, Tajana “QuantHD: A Quantization Framework for Hyperdimensional Computing” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2019 

  • Vikram, Sharad and Collier-Oxandale, Ashley and Ostertag, Michael H. and Menarini, Massimiliano and Chermak, Camron and Dasgupta, Sanjoy and Rosing, Tajana and Hannigan, Michael and Griswold, William G. “Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring” Atmospheric Measurement Techniques , v.12 , 2019 

  • Khaleghi, B. “Prive-HD: Privacy-Preserved Hyperdimensional Computing” Design Automation Conference 2020 , 2020 

  • Peroni, Daniel and Imani, Mohsen and Nejatollahi, Hamid and Dutt, Nikil and Rosing, Tajana “Data Reuse for Accelerated Approximate Warps” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2020 

  • 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 

  • 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 

  • Nejatollahi, H. “CryptoPIM: In-memory Acceleration for Lattice-based Cryptographic Hardware” 2020 International Association for Cryptologic Research Conference (Crypto 2020) , v.276 , 2020

  • Wang, Yiqian and Zhang, Junkang and Cavichini, Melina and Bartsch, Dirk-Uwe G. and Freeman, William R. and Nguyen, Truong Q. and An, Cheolhong “Robust Content-Adaptive Global Registration for Multimodal Retinal Images Using Weakly Supervised Deep-Learning Framework” IEEE Transactions on Image Processing , v.30 , 2021
  • Greenwood-Hickman, Mikael Anne and Nakandala, Supun and Jankowska, Marta M. and Rosenberg, Dori and Tuz-Zahra, Fatima and Bellettiere, John and Carlson, Jordan and Hibbing, Paul R. and Zou, Jingjing and LaCroix, Andrea Z. and Kumar, Arun and Natarajan, Lo “The CNN Hip Accelerometer Posture (CHAP) Method for Classifying Sitting Patterns from Hip Accelerometers: A Validation Study” Medicine & Science in Sports & Exercise , v.Publish , 2021 

  • Jiang, Y. “DEPP: Deep Learning Enables Extending Species Trees using Single Genes” bioRxiv , 2021

  • Kumar, A. “65. Cerebro: A Layered Data Platform for Scalable Deep Learning” 11th Annual Conference on Innovative Data Systems Research (CIDR ‘21) , 2021

  • Sheth, P. “Learning by Teaching, with Application to Neural Architecture Search” ArXivorg , 2021

  • Al-Battal, A.F. “A CNN Segmentation Based Approach To Object Detection And Tracking” ArXivorg , 2021

  • Nakandala, Supun and Nagrecha, Kabir and Kumar, Arun and Papakonstantinou, Yannis “Incremental and Approximate Computations for Accelerating Deep CNN Inference” ACM Transactions on Database Systems , v.45 , 2020 

  • Wang, X. and Wittich, C. E. and Hutchinson, T. C. and Bock, Yehuda and Goldberg, Dara and Lo, Eric and Kuester, F. “Methodology and Validation of UAV-Based Video Analysis Approach for Tracking Earthquake-Induced Building Displacements” Journal of Computing in Civil Engineering , v.34 , 2020 

  • Nakandala, Supun and Kumar, Arun and Papakonstantinou, Yannis “Query Optimization for Faster Deep CNN Explanations” ACM SIGMOD Record , v.49 , 2020 

  • Nakandala, Supun and Zhang, Yuhao and Kumar, Arun “Cerebro: a data system for optimized deep learning model selection” Proceedings of the VLDB Endowment , v.13 , 2020

  • Sang, Shen and Chandraker, Manmohan “Single-Shot Neural Relighting and SVBRDF Estimation” European Conference on Computer Vision , 2020 

  • Nakandala, Supun and Kumar, Arun “Vista: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale” Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data , 2020 

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