"Modeling and Optimization for Customized Computing"

Peipei Zhou, Research Scientist, Shanghai Enflame Technology

February 18th (Tuesday), 2:00pm
Harold Frank Hall (HFH), Rm 4164 (ECE Conf. Rm.)

FPGAs have gained popularity in the acceleration of a wide range of applications with 10x-100x performance/energy efficiency over the general-purpose processors. The design choices of FPGA accelerators for different targets at different levels are enormous. To guide the designers to find the best design choices, modeling is inevitable. In this talk, I will discuss design target, modeling, and optimization for field-programmable gate array (FPGA) customized computing at chip-level, node-level and cluster-level.

About Peipei Zhou:

Peipei Zhou is a research scientist in Shanghai Enflame Technology (AI Chip Startup). She received her Ph.D. in Computer Science from the University of California, Los Angeles in 2019. In 2012, she received a B.S. in Electrical Engineering from Chien-Shiung Wu Honors College, Southeast University. Her research work investigates modeling and optimization of FPGA based reconfigurable architecture from performance, energy, and cost perspective for applications including deep learning, precision medicine and other big-data and machine learning applications. She has in total 9 papers published in FCCM, ISPASS, DAC, ICCAD, TCAD with 4 first authored paper. She has won 2019 IEEE Donald O. Pederson Best Paper Award (TCAD Best Paper), 2019 UCLA CS Outstanding Researcher Award, 2018 ICCAD Best Paper Nominee, 2018 ISPASS Best Paper Nominee, 2018 Phi Tau Phi Scholarship, 2018 DAC PhD Travel Grant. She is passionate in computer architecture research and teaching. More details can be found in her personal website:

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