The High Performance Data Analytics and Computing (HiPDAC) lab conducts research and development in the broad area of high performance computing and big data analytics. The lab mission is to develop techniques, design algorithms, and build software to improve the performance, reliability, and energy efficiency for large-scale computations and big data applications. The current research topics include (but not limited to) accelerator-based computing (GPU/FPGA/MIC), fault tolerance and resilience techniques at extreme scale, energy-efficient computing, scientific data analytics, compression algorithms and software, numerical algorithms and software, HPC simulations, and large-scale machine learning.
Dr. Dingwen Tao is a faculty member in School of Electrical Engineering and Computer Science Washington State University. He received his Ph.D. degree in Computer Science and Engineering from University of California, Riverside in 2018 and his B.S. degree in Mathematics from University of Science and Technology of China in 2013. Contact him at email@example.com.
SIAN JIN (PH.D. STUDENT, JOINED IN FALL 2018)
Mr. Sian Jin received his B.S. degree in Physics from Beijing Normal University (BNU) in 2018. During his undergraduate studies at BNU, Mr. Jin received twice Scholarship of Beijing Normal University. He won First Prize in National Olympiad in Informatics (Advanced group) in 2012. He also won First Prize in the 12th China Adolescent Robotics Competition. Mr. Jin joined HiPDAC Lab in Fall 2018. His research interests include High Performance Computing, Compression Algorithms, Artificial Neural Networks, and Parallel Computing. He did summer internships at Los Alamos National Laboratory in Summer 2019 and Summer 2020. Contact him at firstname.lastname@example.org.
JIANNAN TIAN (PH.D. STUDENT, JOINED IN SPRING 2019)
Mr. Jiannan Tian received his bachelor's degree in Electrical and Computer Engineering from Dalian Maritime University in 2013 and received his master's degree in Computer Engineering from University of Massachusetts, Amherst in 2017. He finished his master thesis "Analyzing Spark Performance on Spot Instances". Jiannan Tian joined The University of Alabama in Spring 2019. He is interested in High Performance Computing, Cloud Computing, Parallel Computing, Energy Efficient Computing, and general technologies for Big Data Analytics. He did internships at Argonne National Laboratory in Fall 2019 and Summer 2020. Contact him at email@example.com.
CHENGMING ZHANG (PH.D. STUDENT, JOINED IN FALL 2019)
Mr. Chengming Zhang received his B.S. degree in Integrated circuit design from University of Electronic Science and Technology of China (UESTC) in 2017. He respectively won the third prize and the first prize in the National Undergraduate Electronic Design Contest in 2015 and 2016. He designed three digital chips for accelerating artificial neural network in 2018, and all chips were fabricated with standard 130 nm or 55 nm CMOS technology. Mr. Zhang joined HiPDAC Lab in Fall 2019. His research interests include High Performance Computing, Data Mining, Machine Learning, and Parallel Computing. Contact him at firstname.lastname@example.org.
DAOE WANG (PH.D. STUDENT, JOINED IN FALL 2020)
Mr. Daoce Wang received his bachelor's degree in Computer Science from University of Electronic Science and Technology of China (UESTC) in 2018 and received his master's degree in Computer Science from University of Florida in 2020. Mr. Wang joined HiPDAC Lab in Fall 2020. His research interests include parallel computing algorithms, databases, data analysis and computer network topology. Contact him at email@example.com.