Publications

Publications

Google Scholar   dblp

Journals

  1. Jaeha Kung, Duckhwan Kim, and Saibal Mukhopadhyay, “Adaptive precision cellular neural network,” submitted to ACM Journal on Emerging Technologies in Computing (JETC), 2016 (under revision)
  2. Duckhwan Kim, Jaeha Kung, and Saibal Mukhopadhyay, “A power-aware digital multilayer perceptron accelerator with on-chip training based on approximate computing,” submitted to IEEE Transactions on Emerging Topics in Computing (TETC), 2016 (under revision).
  3. Duckhwan Kim and Saibal Mukhopadhyay, “Partitioning Methods for Interface Circuit of Heterogeneous 3-D-ICs Under Process Variation,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems (TVLSI), vol. 24, no. 5, pp. 1626-1635, May 2016. [paper]
  4. Jaeha Kung, Duckhwan Kim, and Saibal Mukhopadhyay, “On the impact of energy-accuracy tradeo in a digital cellular neural network for image processing,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 34, no. 7, pp. 1070-1081, February 2015. (Ranked 2 in most downloaded articles for IEEE TCAD in July 2015) [paper]
  5. Youngsoo Shin, Insup Shin, Donkyu Baek, Duckhwan Kim, Seungwhun Paik, “HAPL: Heterogeneous Array of Programmable Logic Using Selective Mask Patterning.” IEEE Transaction on Circuits and Systems I (TCAS-I), vol. 61, no. 1, pp. 146-159, January 2014. [paper]

Conferences

  1. Duckhwan Kim, Jaeha Kung, Sek Chai, Sudhakar Yalamanchili, and Saibal Mukhopadhyay, “An Optimized, Programmable In-Memory Accelerator for Deep Learning,” submitted to ACM/IEEE International Symposium on Computer Architecture (ISCA), 2017.
  2. Jaeha Kung, Yun Long, Duckhwan Kim, and Saibal Mukhopadhyay, “A Programmable Hard-ware Accelerator for Simulating Dynamical Systems,” submitted to ACM/IEEE International Symposium on Computer Architecture (ISCA), 2017.
  3. Jonghwan Ko, Duckhwan Kim, Taesik Na, Jaeha Kung, and Saibal Mukhopadhyay, “Adaptive Weight Compression for Memory-Ecient Neural Networks,” submitted to Proc. IEEE Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.
  4. Mohammad Faisal Amir, Duckhwan Kim, Jaeha Kung, Denny Lie, Sudhakar Yalamanchili, and Saibal Mukhopadhyay, “NeuroSensor: a 3D image sensor with integrated neural accelerator,” IEEE SOI-3D-Subthreshold Microelectronics Technology Uni fied Conferece (S3S),2016. (Student Best Paper)
  5. Jaeha Kung, Duckhwan Kim, and Saibal Mukhopadhyay,”Dynamic approximation with feedback control for energy-efficient recurrent neural network hardware,” Proc. IEEE International Symposium on Low Power Electronics and Design (ISLPED), 2016.
  6. Duckhwan Kim, Jaeha Kung, Sek Chai, Sudhakar Yalamanchili, and Saibal Mukhopadhyay, “Neurocube: a programmable digital neuromorphic architecture with high-density 3D memory,” ACM/IEEE International Symposium on Computer Architecture (ISCA), June 2016. [paper] [slide]
  7. Duckhwan Kim, Jaeha Kung, Sek Chai, Sudhakar Yalamanchili, and Saibal Mukhopadhyay, “Neurocube: a scalable, ecient platform for neuro-inspired computing,” in GOMACTech, March, 2016.
  8. Jaeha Kung, Duckhwan Kim, and Saibal Mukhopadhyay, “A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses,” in Proc. IEEE International Symposium on Low Power Electronics and Design (ISLPED), July 2015. [paper][slide]
  9. Duckhwan Kim and Saibal Mukhopadhyay, “On the design of reliable 3D-ICs considering charged device model ESD events during die stacking,” in Proc. ACM/EDAC/IEEE Design Automation Conference (DAC), June 2014. [paper][slide]
  10. Sangmin Kim, Duckhwan Kim, and Youngsoo Shin, “Pulsed-latch ASIC synthesis in industrial design flow,” in Proc. IEEE Asia and South Paci c Design Automation Conference (ASPDAC), January 2013. [paper]
  11. Jonghwan Kim, Seunghwan Choi, Duckhwan Kim, Joonwoo Kim, and Minjoo Cho, “Animal-Robot Interaction for Pet Caring,” in Proc. IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), December 2009. [paper]

Workshops

  1. Duckhwan Kim, Jaeha Kung, Sek Chai, Sudhakar Yalamanchili, and Saibal Mukhopadhyay, “NeuroCube: A Scalable Ecient Platform for Neuro-inspired Computing,” presented in Student Computer Architecture Symposium at Georgia Tech (ArchiTECH), April 2016.
  2. Duckhwan Kim and Saibal Mukhopadhyay, “Energy-ecient Approximated Feedforward Neural Network Accelerator,” presented in Workshop on hardware and algorithms for learning on a chip (HALO) at IEEE/ACM International Conference on Computer Aided Design (ICCAD), November 2015.