(Zhang 2015 fpga) Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks.
(Chippa 2014 islped) StoRM: A Stochastic Recognition and Mining Processor.
Day 3, Tue 11/10, Yesung Kang, Sunmin Kim, #401-11
Approximate multiplier (Yesung Kang)
Cong Liu; Jie Han; Lombardi, F., "A low-power, high-performance approximate multiplier with configurable partial error recovery," in Design, Automation and Test in Europe Conference and Exhibition (DATE), 2014 , vol., no., pp.1-4, 24-28 March 2014.
Yuan-Ho Chen, "An Accuracy-Adjustment Fixed-Width Booth Multiplier Based on Multilevel Conditional Probability," in Very Large Scale Integration (VLSI) Systems, IEEE Transactions on , vol.23, no.1, pp.203-207, Jan. 2015.
Zervakis, Georgios; Xydis, Sotirios; Tsoumanis, Kostas; Soudris, Dimitrios; Pekmestzi, Kiamal, "Hybrid approximate multiplier architectures for improved power-accuracy trade-offs," in Low Power Electronics and Design (ISLPED), 2015 IEEE/ACM International Symposium on , vol., no., pp.79-84, 22-24 July 2015.
Neuromorphic design (Sunmin Kim)
Sinha, S.; Jounghyuk Suh; Bakkaloglu, B.; Cao, Yu, "Workload-aware neuromorphic design of low-power supply voltage controller," in Low-Power Electronics and Design (ISLPED), 2010 ACM/IEEE International Symposium on , vol., no., pp.241-246, 18-20 Aug. 2010.
Day 4, Thu 11/26, Hyeonuk, Sangyun, #411
FPGA implementation of deep belief network (Hyeonuk Sim)
An energy efficient approximate adder with carry skip for error resilient neuromorphic VLSI systems, ICCAD, 2013.
2.4X faster and 43% more energy-efficient (in EDP) adder
Similar to carry lookahead adder, with approximation applied to carry prediction
Day 6, Wed 12/30 (4pm), Atul, Dong, #511
Efficient FPGA Acceleration of Convolutional Neural Networks Using Logical-3D Compute Array (Atul Rahman, DATE 2016 dry-run)
Deep Learning Accelerator Architecture: SIMD on FPGA (Dong Nguyen, Current Work-in-progress)
Day 7, Thu 01/07, Yesung Kang, Jaemin Lee, #511
Approximate Synthesis Algorithm for the Energy-Efficient FIR filter, on-going work (Yesung Kang)
Design Methodology for Error-Resilient Circuits, on-going work (Jaemin Lee)
Day 8, Thu 01/14, Hyeonuk Sim, Sangyun Oh, #511
Design and implementation of CNN accelerator (Sangyun Oh)
A CGRA-Based Approach for Accelerating Convolutional Neural Networks, IEEE 9th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 2015.
by Tanomoto, M., Takamaeda-Yamazaki, S., Jun Yao, Nakashima, Y. (Nara Inst. of Sci. & Technol., Nara, Japan)