报告题目：On Optimizing Mobile Memory and Storage
报告时间：2024年5月22日14:00-15:00
报告地点：威尼斯432888cam大楼B405
报告人：薛春
报告人国籍：中国
报告人单位：穆罕默德·本·扎耶德人工智能大学
报告人简介：Prof. Chun Jason Xue is a professor at the Department of Computer Science, MBZUAI, Abu Dhabi. He received Ph.D. in Computer Science from the University of Texas at Dallas in 2007 and joined the City University of Hong Kong in the same year. He is currently an associate editor of ACM Transactions on Embedded Computing Systems, ACM Transactions on Storage, and ACM Transactions on CPS.
He has served/serves as General Chair, Program Chair, and Program Committee Member on a number of technical conferences and workshops. He is currently the Steering Committee Chair of ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES) since 2020.
His research interest includes system software for memory and storage optimizations, considering mobile and embedded platforms, with a focus on memory technologies such as non-volatile memories and flash memories.
薛春教授是穆罕默德·本·扎耶德人工智能大学（MBZUAI）计算机科学系的教授。他于2007年获得德克萨斯大学达拉斯分校的计算机科学博士学位，并于同年加入香港城市大学。他目前是ACM Transactions on Embedded Computing Systems、ACM Transactions on Storage和ACM Transactions on CPS的副编辑。他曾担任多个技术会议和研讨会的大会主席、程序主席和程序委员会成员。自2020年以来，他一直担任ACM SIGPLAN/SIGBED会议LCTES的指导委员会主席。他的研究兴趣包括面向移动和嵌入式平台的内存和存储优化系统软件，重点关注非易失性内存和闪存等内存技术。
报告摘要：Current mobile operating systems, such as Android, inherit the Linux kernel. As a result, system software designs that were targeted for servers are now applied in mobile devices. In this series of work, through analyzing mobile application characteristics on files, memory, and storage usage, we found that mobile applications have their own unique characteristics which differ from applications on servers. These differences present new optimization opportunities in mobile memory and storage management. In this talk, I will present several mobile memory and storage management-related works that improve user experience on mobile devices based on mobile application characterization.
邀请人：李清安、袁梦霆
报告题目：Enabling Efficient and Scalable Parallelization for Data-Intensive Computations
报告时间：2024年5月22日15:00-16:00
报告地点：威尼斯432888cam大楼B405
报告人：邱俊乔
报告人国籍：中国
报告人单位：香港城市大学
报告人简介：Dr. Junqiao QIU is an Assistant Professor in the Department of Computer Science at City University of Hong Kong. Prior to joining CityU, he was a tenure-track assistant professor at Michigan Technological University and earned his Ph.D. from the University of California Riverside. His research interests span the areas of compilers and systems, with a focus on enabling efficient parallel computing for data-intensive applications and those with irregular data access patterns. He is a recipient of the ACM SIGPLAN PAC Award, the NSF CRII Award, and the Best Paper Award at ASPLOS 2020.
邱俊乔博士是香港城市大学计算机科学系的助理教授。在加入城市大学之前，他曾在密歇根理工大学担任助理教授，并在加利福尼亚大学河滨分校获得博士学位。他的研究兴趣涵盖编译器和系统领域，重点关注为数据密集型应用和具有不规则数据访问模式的应用实现高效的并行计算。他曾获得ACM SIGPLAN PAC奖、NSF CRII奖和ASPLOS 2020最佳论文奖。
报告摘要：Exploiting parallelism is crucial for achieving high-performance data processing on modern processors. However, many data processing routines still run serially due to the sequential nature of their underlying computation models. In this presentation, I will demonstrate how to effectively break inherent data dependencies and enable scalable and efficient data-parallel processing.
I will begin by introducing our previous work on using speculation to auto-parallelize bitstream processing applications. Following this, I will discuss our ongoing projects that push the boundaries of speculative parallelization. These include leveraging non-SIMD vector instructions to accelerate speculative parallelization, integrating speculation into pattern-aware graph mining applications, and enabling efficient concurrent GPU-based inferences.
Finally, I will conclude the talk by sharing my ideas on parallelizing more general applications, aiming to broaden the applicability of these techniques.
邀请人：李清安、袁梦霆
