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University of Wisconsin–Madison
Research into novel solutions to complex computing problems

Prof. Li profiled by WARF for invention on deep learning accelerator in the Cloud

In the ultracompetitive Wild West of AI a new generation of pioneers is emerging

Armed with the Cloud and a mission to push the limits of deep learning, Jing Li and her team of student “hackers” have bested industry titans and set a performance record.

With support from the WARF Accelerator Program, her latest project is developing a deep learning accelerator in the Cloud. The goal: faster, smarter and more energy-efficient systems for deep learning, with applications like improved speech recognition.

Three regular papers accepted at FPGA’18. Congratulations to Yue, Jialiang and Soroosh!

Yue Zha and Jing Li, “Liquid Silicon: A data-centric recongurable architecture enabled by RRAM technolog“, FPGA’18

Jialiang Zhang and Jing Li, “Degree-aware hybrid graph traversal on FPGA-HMC platform“, FPGA’18

Soroosh Khoram, Jialiang ZhangS, and Jing Li, “Accelerating graph analytics by co-optimizing storage and access on an FPGA-HMC platform“, FPGA’18