Our research has been recognized for many pioneering research projects on developing high performance computing and data management systems on emerging hardware (particularly on GPUs and FPGAs) and cloud computing.
Unlike citation-centric impact factor measurement for journal publications, we strongly believe that the impact of system research should have more comprehensive measurements to reflect its value to academia and industry. Specifically, we have the following “Impact Factors” for system research: Citations, Relevance to Industry and Open-Source Community, System Repeatability and Academic Impacts, Educational Adoptions, and Media Coverage. (see detailed definition)
Our system Mars has inspired the usage of heterogeneous architectures in big data systems such as Hadoop and Spark. Our Mars paper is the 2nd mostly cited among all the papers published in ACM PACT (a leading conference in parallel computing), according to ACM Digital Library (see details)
Our system GPUQP is the pioneering system of accelerating databases on GPUs. GPUQP has been the source of inspirations for many GPU-accelerated relational databases in academia and industry players including Brytlyt, BlazingDB, Omnisci (formerly MapD) and SQream. (see details)
Our system Medusa is the pioneering system of accelerating graph processing on GPUs, which inspired many GPU-based large graph processing systems in academia and industry players such as BlazeGraph. (see details)
The open-source systems ThunderSVM and ThunderGBM have attracted over 1,600 stars, 5000+ repostings on social media and dozens of adoptions in research publications in two years. (see details)
Our research has significant practical impacts in GPU virtualizations and scheduling (nowadays an important infrastructure component in cloud computing with GPUs). gScale has been integrated into Intel's Open GPU virtualization platform. (see details)
The poineering work related to FPGA optimizations have led the rethinking of system optimizations and performance tuning on new-generation FPGAs, and have attracted broad industry interests (e.g., Microsoft (gift grant) and Xilinx research (infrastructure gift)). (see details)
This page on my influential works was inspired by the page on "Influential Papers" from Prof. Xiaodong Zhang.
I consider myself very fortunate to work with many wonderful students and collaborators. Without their hardworking and warm-hearted contributions, those works won’t be possible.
Credits of "details" pages to: Mr. Xinyu Chen, Mr. Hongshi Tan and Mr. Qinbin Li.
All Rights Reserved to Bingsheng He © 2020