劉磊，男，出生於新疆烏魯木齊市，祖籍遼寧瀋陽，現任中科院計算所國家重點實驗室副研究員，Sys-Inventor研究組負責人。劉磊分別於大連理工大學、中國科學技術大學、中國科學院大學（中科院計算所）獲得計算機科學與技術工學學士學位、軟體系統設計工程碩士學位和計算機體系結構工學博士學位（導師：吳承勇、馮曉兵），並於2014年進入計算所工作。在進入計算所之前，劉磊在工業界有5年的軟體工程師、架構師及項目管理經驗。劉磊的研究涉及計算機系統軟體、體系結構及可擴展性、系統性能評測等多個方面。
自2011年起，劉磊帶領其課題組在面向多核平台的作業系統、記憶體資源的利用率、訪存最佳化機制等方向開展了一系列研究，並主導研發了面向主流多核、多通道伺服器，及異構存儲體系的記憶體資源管理系統原型。研究成果以第一作者並通訊作者發表於ISCA，PACT，IEEE TC，ACM TACO，ICCD等領域內旗艦級學術會議和刊物，並在業內產生了影響力。劉磊曾參與或主持多項國家級項目（包括863、973、自然科學基金青年項目等），此外，他還擔任了若干國際學術會議的程式委員會委員、外部評審委員、組委會成員，及學術期刊的審稿人，曾獲得 “中國科學院院長優秀獎”、“國家獎學金”、“國科大優秀畢業生”、“計算所優秀科研人員” 等榮譽。
基本介紹
- 中文名：劉磊
- 國籍：中國
- 民族：蒙古
- 出生地：新疆烏魯木齊
- 出生日期：1981年9月
- 職業：計算機體系結構領域科研工作者
- 畢業院校：中國科學院大學、中國科學技術大學、大連理工大學
- 信仰：共產主義
- 主要成就：提出記憶體Bank/通道劃分、“垂直”管理及最佳化等技術
為記憶體管理、最佳化領域做出貢獻 - 代表作品：第一併通訊作者發表ISCA,PACT,IEEE TC,ACM TACO等高水平論文
- 研究領域：現代作業系統、新型記憶體體系結構
劉磊主導（第一作者）的部分研究成果，以及合作（非一作）發表如下論文：
- Memos: A Full Hierarchy Hybrid Memory Management Framework (Short Paper)
Lei Liu, Hao Yang, Yong Li, Mengyao Xie, Lian Li, Chenggang Wu. The 34th International Conf. on Computer Design (ICCD):2016 - Rethinking Memory Management in Modern Operating System: Horizontal, Vertical or Random?
Lei Liu, Yong Li, Chen Ding, Hao Yang, Chengyong Wu. IEEE Transactions on Computers (TC):2016 - Going Vertical in Memory Management
Lei Liu,et al. ACM SIGARCH Computer Architecture News:October, 2014 - Going Vertical in Memory Management: Handling Multiplicity by Multi-policy
Lei Liu, Yong Li, Zehan Cui, et al. The 41st ACM/IEEE International Symposium on Computer Architecture (ISCA):2014 (acceptance rate: 17.8%，大陸歷史第9篇) - BPM/BPM+: Software-based Dynamic Memory Partitioning Mechanisms for Mitigating DRAM Bank-/Channel-level Interferences in Multicore Systems
Lei Liu, Zehan Cui, Yong Li, et al. ACM Trans. on Architecture and Code Optimization (TACO):2014 - A Software Memory Partition Approach for Eliminating Bank-level Interference in Multicore Systems
Lei Liu, Zehan Cui, Mingjie Xing, et al. The 21st ACM/IEEE International Conference on Parallel Architectures and Compilation Techniques (PACT):2012 (acceptance rate: 18.8%) - WiseThrottling: A New Asynchronous Task Scheduler for Mitigating I/O Bottleneck in Large-Scale Datacenter Servers
Fang Lv, Lei Liu, Huimin Cui, Lei Wang, Ying Liu, Xiaobing Feng, P.C. Yew (UMN). J. of Supercomputing:2015 (Fang Lv is the corresponding author) - Dynamic I/O-Aware Scheduling for Batch-Mode Applications on Chip Multiprocessor Systems of Cluster Platforms
Fang Lv, Huimin Cui, Lei Wang, Lei Liu, Cheng-Gang Wu, Xiao-Bing Feng, and Pen-Chung Yew (UMN). JCST:2014 (Fang Lv is the corresponding author)
研究項目介紹
1. DRAM Bank and Channel Partitioning Mechanism (BPM/BPM+) on Real Systems
This work begins with the contention and interference issue in main memory systems, and I approach it from the Operating System angle. In existing OS, memory resources are "blindly" allocated to applications (threads), leading to memory contentions in DRAM Banks in the root. Order to solve this problem, I use a software method that is an extension of well-known Page-Coloring to eliminate/mitigate the interferences across threads in main memory. The efforts are in PACT-2012 and ACM TACO-2014.
2. "Going Vertical" in Memory Management
The "Gap" between architecture and operating system research brings challenges to computer systems. One typical issue is that the memory management mechanism in existing OS or runtime is oblivious to architecture details in memory systems, thus always leading to serious memory contentions and underutilization. In this project, the approach "Going Vertical" and "Vertical Partitioning" (having the idea of B/C/O-bits in ISCA-2014) are proposed to vertically mitigate the memory interferences in the entire memory hierarchy, as well as improve the memory utilization. Based on them, we further devise dynamic memory optimization and Curve-Vertical Partitioning approach to handle the diverse memory behaviors exhibited by the appearing "memory-diversity" workloads on multi-/many-core platforms. The efforts are published in ISCA-2014 and IEEE TC-2016 (Featured article invited).
3. Memos: Embracing Hybrid Memory Management in Modern Operating System
In this project, we try to develop a memory-centric computing model, operating system, and architecture with hybrid and heterogeneous memory systems. Our goal is to provide a new computing technology, which is not limited by "Memory Wall" in the era marked as "DRAM technology scaling is ending".
Our recent work introduces memos, a framework that can flexibly and efficiently manage main memory system with “horizontal” DRAM-NVM (or Fast-Slow) architecture. Memos has several advantages: (1) Memos integrates several typical memory policies that can benefit the NVM performance and the overall memory utilization, such as memory bank partitioning/re-balancing and vertical memory optimization approaches. (2) Powered by an OS kernel level monitoring tool, memos can obtain the memory patterns online, and then leverage them to guide the memory preference data mapping. (3) Memos can schedule appropriate cache, DRAM, NVM, and channel resources together according to memory features (or user demands), and thus achieving a higher performance. We test memos with diverse workloads, including Memcached. Current experimental results show that memos can benefit memory utilization, and contribute to system throughput and QoS.
4. SysMon
A light-weight OS level system monitoring tool suite, which is able to profile the system on-the-fly and get the memory utilization (including cache utilization, memory footprint, approximate row-buffer locality, physical page level logic re-use time, access frequency, hot/cold features and write/read patterns) without any hardware or PMU supporting. SysMon is especially useful in VM and system level research work. Sysmon is now open source on Github. The beta version is introduced in ISCA-2014 and TC-2016.
項目參與者:
ICT: Lei Liu, Mingjie Xing, Zehan Cui (2011~2013), and Chenyong Wu (2010~2014).
PITT and VMware: Yong Li (2013~2016).
Students: Hao Yang, Mengyao Xie and Hongna Geng.
資金支持:
NSFC under grant No. 61502452 (PI: Lei Liu).
Innovation research project support, SKL (PI: Lei Liu).
863 Program under grant No.2012AA010902 (PI: Xiaobing Feng).
973 Program under grant No.2011CB302504 (PI: Chengyong Wu).
