Current Projects

CAREER: Programming the Existing and Emerging Memory Systems for Extreme-scale Parallel Performance

    Agency: National Science Foundation
    CCF 2015254, CCF 1833332, CCF 1652732
    Duration: 02/2017 – 02/2022

    This CAREER project develops innovative software techniques to address the programming and performance challenges of the existing and emerging memory systems. It combats the memory wall challenge by developing a memory-centric programming paradigm for helping achieve extreme-scale performance of parallel applications with minimum impairment to programmability. For education, the project will involve a broader community starting from high school in the area of HPC and computer science.

SHF: Medium: Compute on Data Path: Combating Data Movement in High Performance Computing

    Agency: National Science Foundation
    CISE SHF-1409946
    Duration: 05/2014 – 07/2017
    Collaborator: Yong Chen (PI), Robert Ross (Co-PI), Yonghong Yan (Co-PI), Barbara Chapman (Co-PI), Dries Kimpe (Former Co-PI)

    This project studies the feasibility of a new Compute on Data Path methodology that expects to improve the performance and energy efficiency for high performance computing.

SHF: Small:Collaborative Research: Application-aware Energy Modeling and Power Management for Parallel and High Performance Computing

    Agency: National Science Foundation
    CISE CCF-2001580, CISE CCF-1833312, CISE SHF-1551182
    Duration: 08/2014 – 08/2017
    Collaborator: Kirk Cameron (VT)

    One of the critical challenges in scaling out current and future high performance computing (HPC) and enterprise computing systems is the requirement that their power envelope remain comparable to that of today's systems. This project addresses this power wall challenge from the system software aspect by developing application-aware methodologies of energy modeling and power management.

High Performance Implementation using GPU and FPGA of for Deformable Image Registration for Cancer Treatment

    Agency: Cancer Institute of William Beaumont Health System,
    Duration: 07/2015 - present

    The project aims to develop the fastest algorithms and software/hardware implementation for deformable image registration algorithms for practical use in cancer treatment.

Past Projects

II-NEW: Image Processing Cloud (IPC): A Domain-Specific Cloud Computing Infrastructure for Research and Education

    Agency: National Science Foundation
    CISE CNS-1205708
    Duration: 06/2012 – 05/2016
    Collaborator: Lei Huang (PVAMU) and Xiaoming Li (University of Delaware)

    To deploy a high-level domain specific language to develop image processing applications using MapReduce framework and on the cloud computing environments.

Participated projects by Dr. Yan (not in a *PI role)

Sponsor and Support

Our research are supported through the College of Engineering of Computing at the University of South Carolina, National Science Foundation, Xilinx, Intel/Altera, Maxeler Technologies, and Beaumont Cancer Institute of Beaumont Health System.