PPT-Dominant Resource Fairness:

Author : danika-pritchard | Published Date : 2016-04-12

Fair Allocation of Multiple Resource Types Ali Ghodsi Matei Zaharia Benjamin Hindman Andy Konwinski Scott Shenker Ion Stoica University of California

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Dominant Resource Fairness:: Transcript

Fair Allocation of Multiple Resource Types Ali Ghodsi Matei Zaharia Benjamin Hindman Andy Konwinski Scott Shenker Ion Stoica University of California Berkeley. Lecture 24. Aditya Akella. Performance Isolation and Fairness in Multi-Tenant Cloud Storage. , D. . Shue. , M. Freedman and A. . Shaikh. , OSDI 2012.. 3. Setting: Shared Storage in the Cloud. Z. Y. T. Advanced Topics in Computer Systems. Lecture 13. Resource allocation: . Lithe/DRF. October 16. th. . , 2012. John Kubiatowicz and Anthony D. Joseph. Electrical Engineering and Computer Sciences. University of California, Berkeley. for . Cluster Schedulers. Robert Grandl. Aditya Akella. Srikanth Kandula. Ganesh Ananthanarayanan. Sriram Rao. Diverse Resource Requirements. Tasks need varying amounts of each resource. E.g., Memory [100MB to 17GB]. Why did it rain this morning?. Why are you at this lecture?. Why did TCP give me throughput √2/(. rtt. . √p)?. Why did TCP give me throughput √2. /(. rtt. . √p)?. τελος. teleology. The doctrine or study of ends or final causes, especially as related to the evidences of design or purpose in nature; also . David Parkes (Harvard). Ariel Procaccia (CMU). Nisarg Shah (CMU). Motivation. Allocation of multiple resources (e.g., CPU, RAM, bandwidth) . Users have heterogeneous demands. Today: fixed bundles (slots). Why did it rain this morning?. Why are you at this lecture?. Why did TCP give me throughput √2/(. rtt. . √p)?. Why did TCP give me throughput √2. /(. rtt. . √p)?. τελος. teleology. The doctrine or study of ends or final causes, especially as related to the evidences of design or purpose in nature; also . Ali . Ghodsi. , . Matei. . Zaharia. , Benjamin . Hindman. , Andy . Konwinski. , Scott . Shenker. , Ion . Stoica. University of California, Berkley. EECS 582 – W16. 1. Outlines. Introduction. Motivation. David Parkes (Harvard). Ariel Procaccia (CMU). Nisarg Shah (CMU). Motivation. Allocation of multiple resources (e.g., CPU, RAM, bandwidth) . Users have heterogeneous demands. Today: fixed bundles (slots). Robert Grandl, Mosharaf Chowdhury, . Aditya Akella, Ganesh Ananthanarayanan. Carbyne. Performance of Cluster Schedulers. We observe that:. Existing cluster schedulers focus on. . instantaneous. . fairness. Robert Grandl, Ganesh Ananthanarayanan, . Srikanth Kandula, Sriram Rao, Aditya Akella. Tetris. Performance of cluster schedulers. We find that:. 1. Time to finish a set of jobs. Resources are . fragmented. Ali . Ghodsi. , . Matei. . Zaharia. , Benjamin . Hindman. , Andy . Konwinski. , Scott . Shenker. , Ion . Stoica. What is Fair Sharing?. n users want to share a resource (e.g., CPU). Solution: . Allocate each 1/n of the shared resource. Ali . Ghodsi. , . Matei. . Zaharia. , Benjamin Hindman, Andy . Konwinski. , Scott . Shenker. , Ion . Stoica. . University of California, Berkeley . Resource Sharing. Multiple users share the resource from a system. Anupam. . Datta. With many slides from Moritz . Hardt. Fall . 2017. 18734: Foundations of Privacy. Fairness in Classification. . Advertising. ✚. Health Care. Education. many more.... $. Banking. Mingwei. Hu. . . F. airness criteria in network resource allocation. How do we achieve fairness between multiplexed packets traffic ?. By allocating rate among flows (flow rate fairness). Flow rate fairness has been the goal behind fair...

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