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education [2019/03/28 18:02]
zablotch
education [2019/05/24 17:34]
fablpd
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 ====== Education ====== ====== Education ======
  
 +\\
  
 The lab is teaching the following courses: The lab is teaching the following courses:
 \\ \\
 +
 +  * [[education/​ca_2018|Concurrent Algorithms]] (theory & practice)
 +  * [[education/​da|Distributed Algorithms]] (theory & practice)
 \\ \\
-  * [[education/​ca_2018|Concurrent Algorithms]] +The lab taught in the past the following courses: 
-  * [[education/​da|Distributed Algorithms]]+
   * <​html><​a href="​http://​moodle.epfl.ch/​course/​view.php?​id=14044">​Information,​ Calcul et Communication</​a></​html>​   * <​html><​a href="​http://​moodle.epfl.ch/​course/​view.php?​id=14044">​Information,​ Calcul et Communication</​a></​html>​
   * <​html><​a href="​http://​cowww.epfl.ch/​proginfo/​wwwhiver/">​Introduction à la Programmation Orientée Objet</​a></​html>​   * <​html><​a href="​http://​cowww.epfl.ch/​proginfo/​wwwhiver/">​Introduction à la Programmation Orientée Objet</​a></​html>​
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 DCL offers master projects in the following areas: DCL offers master projects in the following areas:
  
-  * **Dynamically Distributed Spatial Indexing**:  ​a project here would consist in studying existing spatial index data structures and algorithmse.g., simple gridsQuadtrees, R-Trees etc., and how they may be dynamically ​distributed ​for indexing ​large number ​of moving objects; please ​contact [[mailto:​benoit.garbinato@unil.ch|Benoit Garbinato]] to get more information.+  * **Probabilistic Byzantine Resilience**:  ​Development of high-performanceByzantine-resilient distributed systems with provable probabilistic guaranteesTwo options are currently availableboth building on previous work on probabilistic Byzantine broadcast: (i) a theoretical projectfocused the correctness of probabilistic Byzantine-tolerant ​distributed ​algorithms; (ii) practical project, focused on numerically evaluating ​of our theoretical results. Please ​contact [[matteo.monti@epfl.ch|Matteo Monti]] to get more information.
  
- 
-  * **Multicore computing**:​ a project here would consist for instance in designing and implementing efficient lock-based or lock-free shared objects; please contact [[https://​people.epfl.ch/​igor.zablotchi|Igor Zablotchi]] to get more information. 
  
   * **Distributed computing using RDMA and/or NVRAM**: contact [[https://​people.epfl.ch/​igor.zablotchi|Igor Zablotchi]] for more information.   * **Distributed computing using RDMA and/or NVRAM**: contact [[https://​people.epfl.ch/​igor.zablotchi|Igor Zablotchi]] for more information.
  
-  ​* **Dynamic distributed computing**:​ a project here would consist for instance in designing and implementing applications that would run in a simulation of a cloud with high churn, but possibly robust to arbitrary behavior of some of its components; please contact [[http://​people.epfl.ch/​matej.pavlovic|Matej Pavlovic]] to get more information. +  * **[[Distributed ML|Distributed Machine Learning]]**:​ contact [[http://​people.epfl.ch/​georgios.damaskinos|Georgios Damaskinos]] for more information.
- +
-  ​* **[[Distributed ML|Distributed Machine Learning]]** +
- +
-  * **Distributed and Fault-tolerant algorithms**: projects here would consist in designing failure detection mechanisms suited for large-scale systems, real-time systems, and systems with unreliable communication or partial synchrony. This task also involves implementing,​ evaluating, and simulating the performance of the developed mechanisms to verify the achievable guarantees; please ​contact [[http://​people.epfl.ch/​david.kozhaya|David Kozhaya]] to get more information.+
  
-  * **Consistency in global-scale storage systems**: We offer several projects in the context ​of storage systemsranging from implementation ​of social applications (similar to [[http://retwis.redis.io/​|Retwis]]or [[https://​github.com/​share/​sharejs|ShareJS]]) ​to recommender systemsstatic content storage services ​(à la [[https://​www.usenix.org/legacy/event/osdi10/​tech/​full_papers/​Beaver.pdf|Facebook'​s Haystack]]), or experimenting with well-known cloud serving benchmarks (such as [[https://github.com/brianfrankcooper/​YCSB|YCSB]]); please contact ​[[http://​people.epfl.ch/​dragos-adrian.seredinschi|Adrian Seredinschi]] for further ​information.+  * **Robust Distributed Machine Learning**: With the proliferation ​of big datasets and models, Machine Learning is becoming distributed. Following the standard parameter server modelthe learning phase is taken by two categories ​of machinesparameter servers and workersAny of these machines could behave arbitrarily (i.e., said Byzantine) affecting the model convergence in the learning phaseOur goal in this project is to build a system that is robust against Byzantine behavior of both parameter server and workers. Our first prototypeAggregaThor(https://​www.sysml.cc/doc/2019/54.pdf), ​describes the first scalable robust Machine Learning framework. It fixed a severe vulnerability in TensorFlow and it showed how to make TensorFlow even faster, while robust. Contact ​[[https://people.epfl.ch/arsany.guirguis|Arsany Guirguis]] or [[https://​people.epfl.ch/​sebastien.rouault|Sébastien Rouault]] for more information.
  
-  * **Distributed database algorithms**: a project here would consist ​in implementing and evaluating protocols that are running in today'​s database ​systems, ​e.g., [[https://en.wikipedia.org/wiki/Two-phase_commit_protocol|2PC]], and comparing them with those protocols that can  potentially be used in future database systems; please contact [[http://​people.epfl.ch/​jingjing.wang|Jingjing Wang]] to get more information.+  * **Consistency in global-scale storage systems**: We offer several projects ​in the context of storage ​systems, ​ranging from implementation of social applications (similar to [[http://​retwis.redis.io/​|Retwis]]or [[https://github.com/​share/​sharejs|ShareJS]]) to recommender systems, static content storage services (à la [[https://​www.usenix.org/legacy/event/​osdi10/​tech/​full_papers/​Beaver.pdf|Facebook'​s Haystack]])or experimenting ​with well-known cloud serving benchmarks (such as [[https://​github.com/​brianfrankcooper/​YCSB|YCSB]]); please contact [[http://​people.epfl.ch/​dragos-adrian.seredinschi|Adrian Seredinschi]] or [[https://​people.epfl.ch/​karolos.antoniadis|Karolos Antoniadis]] ​ for further ​information.