PPT-ZygOS : Achieving Low Tail Latency for Microsecond-scale Networked Tasks

Author : trish-goza | Published Date : 2018-09-25

George Prekas Marios Kogias Edouard Bugnion 1 2 Problem Serve μ sscale RPCs Applications KVstores Inmemory DB Datacenter environment Complex fanout fanin

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ZygOS : Achieving Low Tail Latency for Microsecond-scale Networked Tasks: Transcript

George Prekas Marios Kogias Edouard Bugnion 1 2 Problem Serve μ sscale RPCs Applications KVstores Inmemory DB Datacenter environment Complex fanout fanin patterns. 6 94 319 539 634 736 264 5038 Agriculture 07 25 62 264 486 661 339 3180 Arabic 183 302 498 648 761 880 120 6010 Art 04 10 104 493 814 956 44 5090 Biology 75 186 417 623 752 862 138 7115 Business Studies 22 80 206 393 551 705 295 5070 Chemistry 93 190 Achieving Low, Consistent Latency in Market Data Distribution with With more trading decisions and order execution processes being automated, it is critical to make sure information flows quickly and . Scholarly Communication:. The Move . From Journal to Article. Barry Wellman, . FRSC. Jenna Jacobson. iSchool, University of Toronto. For Taylor & Francis Publishers’ Conference, March 2014, Toronto. Akash Adani, Brian Hou, Sabrina Jordan, Juliana Kemenosh, Kaitlyn MacMillan, . Kiera McKay, Anjali Prabhat, Astitva Soni, Aditya Venkatesh. Advisor: Patrick Dolan. Assistant: Bezalem Lemma. Introduction. The story thus far. Tail latency is bad. Causes:. Resource contention with background jobs. Device failure. Uneven-split of data between tasks. Network congestion for reducers. Ways to address tail latency. Need to get Processing closer to storage. Need to get tasks close to data. Rack locality: . Hadoop. Kill task and if a local slot is available: Quincy. Why?. Network is bad: gives horrible performance. Lecture 23 * 14-848 * Fall 2018. What Is “The Tail”?. Most requests are answered promptly. Some requests are slower. As response times get faster, the difference between the fast and the slow grows. Report tegus in the wild in Georgia! Note the location, take a photo and report the sighting online ( www.gainvasives.org/tegus ), by phone (478-994-1438) or by email ( gainvasives@dnr.ga.gov ). Lea Showan Esmail Asyabi, . Azer. . Bestavros. , . Erfan. . Sharafzadeh. , and Timothy Zhu. In-memory Key-Value stores. Non-persistent storage backbones. Tail latency impacts the overall performance. Saehoon Kim. §. , . Yuxiong He. *. ,. . Seung-won Hwang. §. , . Sameh Elnikety. *. , . Seungjin Choi. §. §. *. Web Search Engine . Requirement. 2. Queries. High quality + Low latency. This talk focuses on how to achieve low latency without compromising the quality. Jialin. . Li, Naveen Kr. Sharma. , Dan . R. K. Ports and Steven D. . Gribble . Presented By: Tejala . Thippeswamy. Agenda. Introduction and Background. The Approach. Ideal Latency Distribution. Testbed. Root Cause Analysis and Theory of Action. Agenda. Welcome and Introductions. Continuous Improvement . Overview. Root Cause . Analysis. Theory of . Action. Closing Remarks and Next . Steps. Welcome and Introductions. Resource Management II. Eva . Kalyvianaki. ek264@cam.ac.uk. Contents. Apollo: Scalable and Coordinated Scheduling . for Cloud-Scale Computing, . by Eric Boutin, . Jaliya. Ekanayake, Wei Lin, Bing Shi, and . June 1, 2014. Abstract. JESD204B links are the latest trend in data-converter digital interfaces. These links take advantage of high speed serdes technology to offer many compelling benefits including improved channel densities and simplified board...

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