DBSJ & ACM SIGMODJ 講演会のご案内（8月5日午前11時〜） ★ Virtualized Cloud ★
日本データベース学会の皆様、 以下の講演会が8月5日に東大生研にて行われます。 ふるってご参加ください。 東京大学生研 中野美由紀 ☆☆☆ 8月5日 講演会のご案内 ☆☆☆ 共催 日本データベース学会 ACM SIGMOD日本支部 特定領域研究「情報爆発IT基盤」 日時 8月5日（木） 午前11時〜12時半 場所 東京大学生産技術研究所 E棟 5階 会議室A（Ew-501） http://www.iis.u-tokyo.ac.jp/map/index.html Speaker : Prof. Ling Liu (Georgia Institute of Technology) Title : Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud 参加費 無料 参加ご希望の方は、 日本データベース学会のホームページにて ( http://www.dbsj.org/ ) 会員登録の後（会費無料、すでに登録されている方は結構です）、 sigmodj_lecture@tkl.iis.u-tokyo.ac.jpに 下記の参加申込書をお送り下さい。 皆様のご参加をお待ちしております。 日本データベース学会 国際関係委員会 委員長 （ACM SIGMOD日本支部 支部長） 横田 治夫 連絡先 中野 美由紀 連絡(問合せ)先 日本データベース学会、 ACM SIGMOD 日本支部 sigmodj_lecture@tkl.iis.u-tokyo.ac.jp http://www.dbsj.org/ ----------------------------------------------------------------- To: sigmodj_lecture@tkl.iis.u-tokyo.ac.jp 日本データベース学会・ACM SIGMOD日本支部共催 講演会 参加申し込み 8月5日（木）の講演会に参加 ・名前 ・ご所属 ------------------------------------------------------------------ Program Title : Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud Speaker: Prof. Ling Liu (Georgia Insitute of Technology) Server virtualization offers the ability to slice large, underutilized physical servers into smaller, parallel virtual machines (VMs), enabling diverse applications to run in isolated environments on a shared hardware platform. However, current implementation of virtual machine monitor does not provide sufficient performance isolation to guarantee the effectiveness of resource sharing, especially when the applications running on multiple virtual machines of the same physical machine are competing for computing and communication resources. In this talk, we present our performance measurement study of network I/O applications in virtualized cloud. We first report our experimental study on the performance interference in parallel processing of CPU and network intensive workloads in the Xen Virtual Machine Monitors (VMMs). . We focus our measurement based analysis on performance impact of co-locating applications in a virtualized cloud platform in terms of throughput and resource sharing effectiveness, including the impact of idle instances on applications that are running concurrently on the same physical host. We present four key findings that are critical to effective management of virtualized cloud environments for both cloud service providers and cloud consumers. First, running network-intensive workloads in isolated environments on a shared hardware platform can lead to high overheads due to extensive context switches and events in driver domain and VMM. Second, co-locating CPU-intensive workloads in isolated environments on a shared hardware platform can incur high CPU contention due to the demand for fast memory pages exchanges in I/O channel. Third, identifying factors that impact the total demand of the exchanged memory pages is critical to the in-depth understanding of the interference overheads in I/O channel in the driver domain and VMM. Last but not least, running CPU-intensive workloads and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. We show that by strategically co-locating network I/O applications, performance improvement for cloud consumers can be as high as 34%, and the cloud providers can achieve over 40% performance gain. Bio: Ling Liu is a full Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large scale data intensive systems with the focus on performance, availability, security, privacy, and energy efficiency. Prof. Liu and her students have released a number of open source software tools, including WebCQ, XWRAP, PeerCrawl, GTMobiSim. Prof. Liu has published over 250 International journal and conference articles in the areas of databases, distributed systems, and Internet Computing. She is a recipient of the best paper award of ICDCS 2003, WWW 2004, the 2005 Pat Goldberg Memorial Best Paper Award, and 2008 Int. conf. on Software Engineering and Data Engineering. Prof. Liu has served as general chair and PC chairs of several IEEE and ACM conferences in data engineering and distributed computing fields and editorial board of a number of International journals. Currently Prof. Liu is on the editorial board of Distributed and Parallel Databases (Springer), Journal of Parallel and Distributed Computing (JPDC), IEEE Transactions on Service Computing (TSC), and Wireless Network (WINET, Springer). Dr. Liu’s current research is primarily sponsored by NSF, IBM, and Intel. -- ----------------------------------------------------------------------- 中野 美由紀 東京大学 生産技術研究所 戦略情報融合国際研究センタ Miyuki NAKANO Institute of Industrial Science, Univ. of Tokyo Center for Information Fusion miyuki@tkl.iis.u-tokyo.ac.jp
日本データベース学会の皆様、 さきほど、ご案内した講演会ですが、恐縮ですが、都合により ３０分早くなりまして、明日の★１０時半★から開始です。 以下の講演会が8月5日に東大生研にて行われます。 ふるってご参加ください。 東京大学生研 中野美由紀 ☆☆☆ 8月5日 講演会のご案内 ☆☆☆
共催 日本データベース学会 ACM SIGMOD日本支部 特定領域研究「情報爆発IT基盤」
日時 8月5日（木） 午前10時半〜12時半
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場所 東京大学生産技術研究所 E棟 5階 会議室A（Ew-501） http://www.iis.u-tokyo.ac.jp/map/index.html
Speaker : Prof. Ling Liu (Georgia Institute of Technology) Title : Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud
参加費 無料
参加ご希望の方は、 日本データベース学会のホームページにて ( http://www.dbsj.org/ ) 会員登録の後（会費無料、すでに登録されている方は結構です）、 sigmodj_lecture@tkl.iis.u-tokyo.ac.jpに 下記の参加申込書をお送り下さい。
皆様のご参加をお待ちしております。
日本データベース学会 国際関係委員会 委員長 （ACM SIGMOD日本支部 支部長） 横田 治夫
連絡先 中野 美由紀 連絡(問合せ)先 日本データベース学会、 ACM SIGMOD 日本支部 sigmodj_lecture@tkl.iis.u-tokyo.ac.jp http://www.dbsj.org/
----------------------------------------------------------------- To: sigmodj_lecture@tkl.iis.u-tokyo.ac.jp
日本データベース学会・ACM SIGMOD日本支部共催 講演会 参加申し込み
8月5日（木）の講演会に参加 ・名前 ・ご所属 ------------------------------------------------------------------
Program
Title : Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud
Speaker: Prof. Ling Liu (Georgia Insitute of Technology)
Server virtualization offers the ability to slice large, underutilized physical servers into smaller, parallel virtual machines (VMs), enabling diverse applications to run in isolated environments on a shared hardware platform. However, current implementation of virtual machine monitor does not provide sufficient performance isolation to guarantee the effectiveness of resource sharing, especially when the applications running on multiple virtual machines of the same physical machine are competing for computing and communication resources. In this talk, we present our performance measurement study of network I/O applications in virtualized cloud. We first report our experimental study on the performance interference in parallel processing of CPU and network intensive workloads in the Xen Virtual Machine Monitors (VMMs). . We focus our measurement based analysis on performance impact of co-locating applications in a virtualized cloud platform in terms of throughput and resource sharing effectiveness, including the impact of idle instances on applications that are running concurrently on the same physical host. We present four key findings that are critical to effective management of virtualized cloud environments for both cloud service providers and cloud consumers. First, running network-intensive workloads in isolated environments on a shared hardware platform can lead to high overheads due to extensive context switches and events in driver domain and VMM. Second, co-locating CPU-intensive workloads in isolated environments on a shared hardware platform can incur high CPU contention due to the demand for fast memory pages exchanges in I/O channel. Third, identifying factors that impact the total demand of the exchanged memory pages is critical to the in-depth understanding of the interference overheads in I/O channel in the driver domain and VMM. Last but not least, running CPU-intensive workloads and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. We show that by strategically co-locating network I/O applications, performance improvement for cloud consumers can be as high as 34%, and the cloud providers can achieve over 40% performance gain. Bio: Ling Liu is a full Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large scale data intensive systems with the focus on performance, availability, security, privacy, and energy efficiency. Prof. Liu and her students have released a number of open source software tools, including WebCQ, XWRAP, PeerCrawl, GTMobiSim. Prof. Liu has published over 250 International journal and conference articles in the areas of databases, distributed systems, and Internet Computing. She is a recipient of the best paper award of ICDCS 2003, WWW 2004, the 2005 Pat Goldberg Memorial Best Paper Award, and 2008 Int. conf. on Software Engineering and Data Engineering. Prof. Liu has served as general chair and PC chairs of several IEEE and ACM conferences in data engineering and distributed computing fields and editorial board of a number of International journals. Currently Prof. Liu is on the editorial board of Distributed and Parallel Databases (Springer), Journal of Parallel and Distributed Computing (JPDC), IEEE Transactions on Service Computing (TSC), and Wireless Network (WINET, Springer). Dr. Liu’s current research is primarily sponsored by NSF, IBM, and Intel.
-- ----------------------------------------------------------------------- 中野 美由紀 東京大学 生産技術研究所 戦略情報融合国際研究センタ Miyuki NAKANO Institute of Industrial Science, Univ. of Tokyo Center for Information Fusion miyuki@tkl.iis.u-tokyo.ac.jp
participants (1)
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Miyuki Nakano