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--- teaching:mfe:is [2018/04/23 09:54]
svsummer [Master Thesis in Collaboration with Euranova]
+++ teaching:mfe:is [2018/04/23 09:57]
svsummer [Master Thesis in Collaboration with Euranova]
@@ Line 25: / Line 25: @@
   * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]]
-** Dynamic Query Processing on GPU Accelerators
+===== Dynamic Query Processing on GPU Accelerators =====
-   This master thesis is put forward in the context of the DFAQ
-   Research Project:  "Dyanmic Processing of Frequently Asked
-   Queries", funded by the Wiener-Anspach foundation.
-   Within this project, our lab is hence developing novel ways for
+This master thesis is put forward in the context of the DFAQ Research Project: "Dyanmic Processing of Frequently Asked Queries", funded by the Wiener-Anspach foundation.
-   processing "fast Big Data", i.e., processing of analytical queries
-   where the underlying data is constantly being updated.  The
-   analytics problems envisioned cover wide areas of computer science
-   and include database aggregate queries, probabilistic inference,
-   matrix chain computation, and building statistical models.
-   The objective of this master thesis is to build upon the novel
+Within this project, our lab is hence developing novel ways for processing "fast Big Data", i.e., processing of analytical queries where the underlying data is constantly being updated. The analytics problems envisioned cover wide areas of computer science and include database aggregate queries, probabilistic inference, matrix chain computation, and building statistical models.
-   dynamic processing algorithms being developed in the lab, and
-   complement these algorithms by proposing dynamic evaluation
-   algorithms that execute on modern GPU architectures, thereby
-   exploiting their massive parallel processing capabilities.
-   Since our current development is done in the Scala programming
+The objective of this master thesis is to build upon the novel dynamic processing algorithms being developed in the lab, and complement these algorithms by proposing dynamic evaluation algorithms that execute on modern GPU architectures, thereby exploiting their massive parallel processing capabilities.
-   language, prospective students should either know Scala, or being
-   willing to learn it within the context of the master thesis.
-   *Validation of the approach* Validation of master thesis' work
+Since our current development is done in the Scala programming language, prospective students should either know Scala, or being willing to learn it within the context of the master thesis.
-   should be done on two levels:
-  - a theoretical level; by proposing and discussing alternative ways
-    to do incremental computation on GPU architectures, and comparing
-    these from a theoretical complexity viewpoint
-  - an experimental level; by proposing a benchmark collection of CEP
-    queries that can be used to test the obtained versions of the
-    interpreter/compiler, and report on the experimentally observed
-    performance on this benchmark.
-  *Deliverables* of the master thesis project
-   - An overview of query processing on GPUs
-   - A definition of the analytics queries under consideration
-   - A description of different possible dynamic evaluation algorithms
-     for the analytical queries on GPU architectures.
-   - A theoretical comparison of these possibilities
-   - The implementaiton of the evaluation algorithm(s) (as an interpreter/compiler)
-   - A benchmark set of queries and associated data sets for
-     the experimental validation
-   - An experimental validation of the compiler, and analysis of the results.
-   *Interested?*
+**Validation of the approach** Validation of master thesis' work should be done on two levels:
-   - Contact :  [[svsummer@ulb.ac.be][Stijn Vansummeren]]
+  * a theoretical level; by proposing and discussing alternative ways to do incremental computation on GPU architectures, and comparing these from a theoretical complexity viewpoint
+  * an experimental level; by proposing a benchmark collection of CEP queries that can be used to test the obtained versions of the interpreter/compiler, and report on the experimentally observed performance on this benchmark.
-   *Status*: available
+**Deliverables** of the master thesis project
+  * An overview of query processing on GPUs
+  * A definition of the analytics queries under consideration
+  * A description of different possible dynamic evaluation algorithms for the analytical queries on GPU architectures.
+  * A theoretical comparison of these possibilities
+  * The implementaiton of the evaluation algorithm(s) (as an interpreter/compiler)
+  * A benchmark set of queries and associated data sets for the experimental validation
+  * An experimental validation of the compiler, and analysis of the results.
+**Interested?**
+  * Contact : //Stijn Vansummeren//
-** Complex Event Processing in Apache Spark and Apache Storm
+**Status**: available
-  The master thesis is put forward in the context of the SPICES
-  "Scalable Processing and mIning of Complex Events for
-  Security-analytics" research project, funded by Innoviris.
-  Within this project, our lab is developping a declarative language
-  for Complex Event Processing (CEP for short). The goal in Complex
-  Event Processing is to derive pre-defined patterns in a stream of
-  raw events. Raw events are typically sensor readings (such as
-  "password incorrect for user X trying to log in on machine Y" or
-  "file transfer from machine X to machine Y"). The goal of CEP is
-  then to correlate these events into complex events. For example,
-  repeated failed login attempts by X to Y should trigger a complex
-  event "password cracking warning" that refers to all failed login
-  attempts.
-  The objective of this master thesis is to build an
-  interpreter/compiler for this declarative CEP language that targets
-  the distributed computing frameworks Apache Spark and/or Apache
-  Storm as backends.  Getting aquaintend with these technologies is
-  part of the master thesis objective.
-  *Validation of the approach* Validation of the proposed
-  interpreter/compiler should be done on two levels:
-  - a theoretical level; by comparing the generated Spark/Storm
-    processors to a processor based on "Incremental computation" that
-    is being developped at the lab
-  - an experimental level; by proposing a benchmark
-    collection of CEP queries that can be used to test the obtained
-    interpreter/compiler, and report on the experimentally observed
-    performance on this benchmark.
-  *Deliverables* of the master thesis project
-   - An overview of the processing models of Spark and Storm
-   - A definition of the declarative CEP language under consideration
-   - A description of the interpretation/compilation algorithm
-   - A theoretical comparison of this algorithm wrt an incremental
-     evaluation algorithm.
-   - The interpreter/compiler itself (software artifact)
-   - A benchmark set of CEP queries and associated data sets for
-     the experimental validation
-   - An experimental validation of the compiler, and analysis of the results.
-   *Interested?*
-   - Contact :  [[svsummer@ulb.ac.be][Stijn Vansummeren]]
-   *Status*: available
-** Graph Indexing  for Fast Subgraph Isomorphism Testing
-   There is an increasing amount of scientific data, mostly from the
-   bio-medical sciences, that can be represented as collections of
-   graphs (chemical molecules, gene interaction networks, ...). A
-   crucial operation when searching in this data is that of subgraph
-   isomorphism testing: given a pattern P that one is interested in
-   (also a graph) in and a collection D of graphs (e.g., chemical
-   molecules), find all graphs in G that have P as a
-   subgraph. Unfortunately, the subgraph isomorphism problem is
-   computationally intractable. In ongoing research, to enable
-   tractable processing of this problem, we aim to reduce the number
-   of candidate graphs in D to which a subgraph isomorphism test needs
-   to be executed. Specifically, we index the graphs in the collection
-   D by means of decomposing them into graphs for which subgraph
-   isomorphism *is* tractable. An associated algorithm that filters
-   graphs that certainly cannot match P can then formulated based on
-   ideas from information retrieval.
-   In this master thesis project, the student will emperically
-   validate on real-world datasets the extent to which graphs can be
-   decomposed into graphs for which subgraph isomorphism is
-   tractable, and run experiments to validate the effectiveness of
-   the proposed method in terms of filtering power.
-   *Interested?*
-   - Contact :  [[svsummer@ulb.ac.be][Stijn Vansummeren]]
-   *Status*: available
 ===== Complex Event Processing in Apache Spark and Apache Storm =====
@@ Line 259: / Line 157: @@
 **Status**: available