~ ESTR4316 ~
Course Assessment for ESTR4316
Your grade will be based on the following components:
- Homework & Programming assignments (4 sets in total): 45%
- Mid-term Exam: 9% (1-hour mid-term examination)
- Final Exam: 37% (2-hour final examination)
- Oral Paper Presentations: 9%
Presentation Schedule
| Date of presentation | Paper | Presenter | Link to the presentation |
|---|---|---|---|
| Jan 20 | S. Keshav, “How to Read a Paper”, ACM SIGCOMM Computer Communication Review, July 2007 | Prof. Lau | |
| Feb 10 | A1 [YARN] V.K. Vavilapalli, A.C.Murthy, “Apache Hadoop YARN: Yet Another Resource Negotiator,” ACM Symposium on Cloud Computing (SoCC) 2013 | FAN Junbo | yarn.pdf |
| B1 [Mesos] B. Hindman et al, “Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center”, NSDI 2011 | BAO Ergute | mesos.pdf mesos.pptx | |
| Feb 17 | C2 [Omega] M. Schwarzkopf, A. Konwinski, M.Abd-El-Malek, J. Wilkes, “Omega: flexible, scalable schedulers for large compute clusters,” Eurosys 2013 | Allen Zhong | omega.pdf |
| D1 [Apollo] E. Boutin et al, “Apollo: Scalable and Coordinated Scheduling for Cloud-Scale Computing”, OSDI 2014 | SUN Weize | apollo.pptx | |
| Feb 24 | A2 [Sparrow] K. Ousterhout et al, “Sparrow: Distributed, Low Latency Scheduling”, ACM SOSP 2013 | FAN Junbo | sparrow.pdf |
| B2 [DRF] A. Ghodsi et al, “Dominant Resource Fairness: Fair Allocation of Multiple Resource Types,” NSDI 2011 | BAO Ergute | DRF.pptx | |
| **No Meeting on Mar 3 due to Instructor’s conference trip. An extra hour of Make-up meeting will be held on Apr 21.** | |||
| Mar 10 | C1 [Borg] A. Verma, L. Pedrosa, “Large-scale cluster management at Google with Borg”, Eurosys 2015 | Allen Zhong | Borg.pdf |
| D2 [Mercury] K. Karanasos et al, “Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters”, Usenix ATC 2015 | SUN Weize | Mercury.pptx | |
| Mar 17 | [PowerGraph] Joseph Gonzalez et al, “PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs,” OSDI 2012 | Fan Junbo | powergraph.pdf |
| [Heron] Sanjeev Kulkarni et al, "Twitter Heron: Stream Processing at Scale,” SIGMOD 2015 | Bao Ergute | HERON.pptx | |
| Mar 24 | [KafkaSamza] Martin Kleppmann and Jay Kreps, “Kafka, Samza and the Unix philosophy of distributed data,” IEEE Data Engineering Bulletin, 38(4), Dec 2015 | Sun Weize | kafka&samza.pptx |
| [HiveAdvances] Yin Huai et al, “Major Technical Advancements in Apache Hive,” ACM SIGMOD 2014 | Allen Zhong | Hive.pdf | |
| Mar 31 | [FlumeJava] Craig Chambers et al, “FlumeJava: Easy, Efficient Data-Parallel Pipelines,” PLDI 2010 | Bao Ergute | |
| [MillWheel] Tyler Akidau et al, “MillWheel: Fault-Tolerant Stream Processing at Internet Scale,” VLDB 2013 | Fan Junbo | millwheel.pdf | |
| Apr 7 | [SummingBird] Oscar Boykin et al, “Summingbird: A Framework for Integrating Batch and Online MapReduce Computations,” VLDB 2014 | Allen Zhong | summingbird.pdf |
| [TwitterExperience] Jimmy Lin and Dmitriy Ryaboy, “Scaling Big Data Mining Infrastructure: The Twitter Experience,” ACM SIGKDD Explorations, Vol. 14, Issue 2, 2013 | Sun Weize | Twitter.pptx | |
| Apr 21 (2-hr section) | [StratosphereFlink] Alexander Alexandrov et al,” The Stratosphere platform for Big Data Analytics,” VLDB Journal 2014. [Stratophere is the basis of the Apache Flink platform] | Bao Ergute | stratosphere.pptx |
| [Naiad1] Derek G. Murray et al, "Naiad: A Timely Dataflow System,” ACM SOSP 2013 ( A more gentle introduction of this paper can be found at: “Incremental, Iterative Data Processing with Timely Dataflow,” Communications of ACM, Oct 2016) | Fan Junbo | naiad.pdf | |
| [TensorFlow] Martin Abadi et al, “TensorFlow: A System for Large-Scale Machine Learning,” OSDI 2016 | Sun Weize | TensorFlow– A system for large-scale machine learning.pptx | |
| [Petuum] Eric P. Xing et al, “Strategies and Principles of Distributed Machine Learning on Big Data,” Engineering (The Journal of Chinese Academy of Engineering), 2016 | Allen Zhong | Petuum.pdf | |