報告題目：On Optimizing Mobile Memory and Storage
報告時間：2024年5月22日14:00-15:00
報告地點：437bwin必贏國際官網大樓B405
報告人：薛春
報告人國籍：中國
報告人單位：穆罕默德·本·扎耶德人工智能大學
報告人簡介：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·扎耶德人工智能大學（MBZUAI）計算機科學系的教授。他于2007年獲得德克薩斯大學達拉斯分校的計算機科學博士學位，并于同年加入香港城市大學。他目前是ACM Transactions on Embedded Computing Systems、ACM Transactions on Storage和ACM Transactions on CPS的副編輯。他曾擔任多個技術會議和研討會的大會主席、程序主席和程序委員會成員。自2020年以來，他一直擔任ACM SIGPLAN/SIGBED會議LCTES的指導委員會主席。他的研究興趣包括面向移動和嵌入式平臺的內存和存儲優化系統軟件，重點關注非易失性內存和閃存等內存技術。
報告摘要：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.
邀請人：李清安、袁夢霆
報告題目：Enabling Efficient and Scalable Parallelization for Data-Intensive Computations
報告時間：2024年5月22日15:00-16:00
報告地點：437bwin必贏國際官網大樓B405
報告人：邱俊喬
報告人國籍：中國
報告人單位：香港城市大學
報告人簡介：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.
邱俊喬博士是香港城市大學計算機科學系的助理教授。在加入城市大學之前，他曾在密歇根理工大學擔任助理教授，并在加利福尼亞大學河濱分校獲得博士學位。他的研究興趣涵蓋編譯器和系統領域，重點關注為數據密集型應用和具有不規則數據訪問模式的應用實現高效的并行計算。他曾獲得ACM SIGPLAN PAC獎、NSF CRII獎和ASPLOS 2020最佳論文獎。
報告摘要：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.
邀請人：李清安、袁夢霆
