Professor Jason Cong, the Volgenau Chair for Engineering Excellence at UCLA, has been honored with the 10-Year Retrospective Most Influential Paper Award at the 2025 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). The award recognizes the lasting impact of the 2016 paper, “Caffeine: Towards uniformed representation and acceleration for deep convolutional neural networks.” Professor Cong co-authored this paper with Chen Zhang, Zhenman Fang, Peipei Zhou, and Peichen Pan.
The paper presented Caffeine, a full-stack design automation tool that synthesizes deep neural networks specifically onto field-programmable gate-arrays (FPGA). At the hardware level, it automatically extracts operator sets from AI models, optimally maps them to a reconfigurable intermediate representation, and generates efficient FPGA hardware implementations. At the software level, it automatically generates instruction streams based on the hardware configuration (matrix engines, caches, pipelines, etc.), optimizing operator scheduling and memory management.
Deep neural networks are built from distinct computational stages called layers. Before Caffeine, most FPGA accelerators focused only on the convolution layers, which limited performance at the fully-connected layers. Caffeine introduced a novel unified convolutional representation to efficiently accelerate the entire network on a single FPGA. This approach included key techniques like automated memory access transformation to solve the critical challenge of optimizing for the limited memory bandwidth of FPGAs. The paper’s lasting influence is highlighted by its nearly 800 citations, including from nearly every major company in the AI hardware acceleration industry such as AMD, Google, Intel, and Nvidia.
Cong received his Ph.D. in Computer Science from UIUC in 1990. He directs the Center for Domain-Specific Computing and the VAST Laboratory at UCLA. A leading researcher in VLSI, customizable, and quantum computing, he is a member of the National Academy of Engineering and a Fellow of ACM, IEEE, and NAI. He has received top honors including the IEEE Robert N. Noyce Medal and the ACM Charles P. Thacker Breakthrough Award. He also co-founded successful startups such as AutoESL (acquired by Xilinx) and Falcon Computing (acquired by AMD).