I would like to invite you to attend this week's CSCE 791 seminar. These seminars highlight research being performed in our department and across the world. All CSCE 791 seminars are open to anybody who wishes to attend - not just students registered for the course. Speaker: Dr. Yonghong Yan, University of South Carolina Abstract: Today’s computer systems are becoming much more heterogeneous and complex from both computer architecture and memory system. High performance computing systems and large-scale enterprise clusters are often built with the combination of multiple architectures including multicore CPUs, Nvidia manycore GPUs, Intel Xeon Phi vector manycores, and domain-specific processing units, such as DSP and deep-learning tensor units. The introduction of non-volatile memory and 3D-stack DRAM known as high-bandwidth memory further complicated computer systems by significantly increasing the complexity of the memory hierarchy. For users, parallel programming for those systems has thus become much more challenging than ever. In this talk, the speaker will highlight the latest development of parallel programming models for the existing and emerging architectures for high performance computing. He will introduce the ongoing work in his research team (http://passlab.github.io) for improving productivity and portability of parallel programming for heterogeneous systems with the combination of shared and discrete memory. The speaker will conclude that this is an exciting time for performing computer system research and also share some of his unsuccessful experiences for studying his Ph.D. Bio: Dr. Yonghong Yan joined University of South Carolina as an Assistant Professor in Fall 2017 and he is a member of OpenMP Architectural Review Board and OpenMP Language Committee. Dr. Yan calls himself a nerd for parallel computing, compiler technology and high-performance computer architecture and systems. He is an NSF CAREER awardee. His research team develop intra-/inter-node programming models, compiler, runtime systems and performance tools based on OpenMP, MPI and LLVM compiler, explore conventional and advanced computer architectures including CPU, vector, GPU, MIC, FPGA, and dataflow system, and support applications ranging from classical HPC, to big data analysis and machine learning, and to computer imaging. The ongoing development can be found from https://github.com/passlab. Dr. Yan received his PhD degree in computer science from University of Houston and has a bachelor degree in mechanical engineering