"At Seattle Pacific University we have used Work Queue in the CSC/CPE 4760 Advanced Computer Architecture course in Spring 2014 and Spring 2016. Work Queue serves as our primary example of a distributed system in our “Distributed and Cloud Computing” unit for the course. Work Queue was chosen because it is easy to deploy, and undergraduate students can quickly get started working on projects that harness the power of distributed resources."
The main project in this unit had the
students obtain benchmark results for three systems: a high performance workstation; a cluster of 12 Raspberry Pi 2 boards, and a cluster of A1 instances in
Microsoft Azure. The task for each benchmark
used Dr. Peter Bui’s Work Queue MapReduce framework; the students
tested both a Word Count and Inverted Index on the Linux
kernel source. In testing the three systems the students were exposed to
the principles of distributed computing and the MapReduce model as they investigated tradeoffs in price, performance, and overhead.
- Prof. Aaron Dingler, Seattle Pacific University.
Post a Comment