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Showing results 1 to 8 of 8

Conference
Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge
  • Ni, Yang ; 
  • Kim, Yeseong ; 
  • Rosing, Tajana ; 
  • Imani, Mohsen
  • 2022-03-17
  • Ni, Yang. (2022-03-17). Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge. Design Automation and Test in Europe Conference, 292–297. doi: 10.23919/DATE54114.2022.9774524
  • IEEE Council on Electronic Design Automation
  • View : 119
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Conference
Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge (Extended Abstract)
  • Ni, Yang ; 
  • Kim, Yeseong ; 
  • Rosing, Tajana ; 
  • Imani, Mohsen
  • 2023-08-24
  • Ni, Yang. (2023-08-24). Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge (Extended Abstract). International Joint Conference on Artificial Intelligence, 6474–6479. doi: 10.24963/ijcai.2023/723
  • International Joint Conferences on Artifical Intelligence (IJCAI)
  • View : 127
  • Download : 0

HyperRec: Efficient Recommender Systems with Hyperdimensional Computing

Conference
HyperRec: Efficient Recommender Systems with Hyperdimensional Computing
  • Guo, Yunhui ; 
  • Imani, Mohsen ; 
  • Kang, Jaeyoung ; 
  • Salamat, Sahand ; 
  • Morris, Justin ; 
  • Aksanli, Baris ; 
  • Kim, Yeseong ; 
  • Rosing, Tajana
  • 2021-01-18
  • Guo, Yunhui. (2021-01-18). HyperRec: Efficient Recommender Systems with Hyperdimensional Computing. 26th Asia and South Pacific Design Automation Conference, ASP-DAC 2021, 384–389. doi: 10.1145/3394885.3431553
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 152
  • Download : 29
Conference
Late Breaking Results: Hyperdimensional Regression with Fine-Grained and Scalable Confidence-Based Learning
  • Kim, Jiseung ; 
  • Lee, Hyunsei ; 
  • Rosing, Tajana ; 
  • Imani, Mohsen ; 
  • Kim, Yeseong
  • 2025-04-02
  • Kim, Jiseung. (2025-04-02). Late Breaking Results: Hyperdimensional Regression with Fine-Grained and Scalable Confidence-Based Learning. Design Automation and Test in Europe Conference, 1–2. doi: 10.23919/DATE64628.2025.10993077
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 210
  • Download : 0
Conference
Online Performance and Power Prediction for Edge TPU via Comprehensive Characterization
  • Ni, Yang ; 
  • Kim, Yeseong ; 
  • Rosing, Tajana ; 
  • Imani, Mohsen
  • 2022-03-22
  • Ni, Yang. (2022-03-22). Online Performance and Power Prediction for Edge TPU via Comprehensive Characterization. Design Automation and Test in Europe Conference, 612–615. doi: 10.23919/DATE54114.2022.9774764
  • IEEE Council on Electronic Design Automation
  • View : 139
  • Download : 0
Article
OpenHD: A GPU-Powered Framework for Hyperdimensional Computing
  • Kang, Jaeyoung ; 
  • Khaleghi, Behnam ; 
  • Rosing, Tajana ; 
  • Kim, Yeseong
  • 2022-11
  • Kang, Jaeyoung. (2022-11). OpenHD: A GPU-Powered Framework for Hyperdimensional Computing. IEEE Transactions on Computers, 71(11), 2753–2765. doi: 10.1109/TC.2022.3179226
  • Institute of Electrical and Electronics Engineers
  • View : 241
  • Download : 0
Conference
Revisiting HyperDimensional Learning for FPGA and Low-Power Architectures
  • Imani, Mohsen ; 
  • Zou, Zhuowen ; 
  • Bosch, Samuel ; 
  • Rao, Sanjay Anantha ; 
  • Salamat, Sahand ; 
  • Kumar, Venkatesh ; 
  • Kim, Yeseong ; 
  • Rosing, Tajana
  • 2021-03-01
  • Imani, Mohsen. (2021-03-01). Revisiting HyperDimensional Learning for FPGA and Low-Power Architectures. International Symposium on High-Performance Computer Architecture, 221–234. doi: 10.1109/HPCA51647.2021.00028
  • IEEE Computer Society
  • View : 147
  • Download : 0
Conference
XCelHD: An Efficient GPU-Powered Hyperdimensional Computing with Parallelized Training
  • Kang, Jaeyoung ; 
  • Khaleghi, Behnam ; 
  • Kim, Yeseong ; 
  • Rosing, Tajana
  • 2022-01-18
  • Kang, Jaeyoung. (2022-01-18). XCelHD: An Efficient GPU-Powered Hyperdimensional Computing with Parallelized Training. 27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022, 220–225. doi: 10.1109/ASP-DAC52403.2022.9712549
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 85
  • Download : 0
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