The project work for this year will be the (re)implementation and test of an existing clustering algorithm using one of the MPI, TBB or OpenCL technologies (possibly more than one, in some cases).
To this extent, a few papers are listed that explain parallel clustering algorithms, which the student should analyze and implement. In a few cases, there is already a parallel implementation that the student can attempt to parallelize using a different technology.
The proposed implementation
must have a well recognizable, explicit parallel structure
must have an (expected) parallel performance model
must be verified with experiments
must be accompanied with a short report explaining the problem tackled, the choices made, the performance model; the report shall contain the experments results and analysis.
The student
should be able to understand the parallel algorithm and implement/port it with the choosen support
can exploit libraries and data structures as needed
should be able to verify the program and its model with experimental data, identifying performance and scalability issues
Please contact the teacher :
In case you are stuck or miss datasets to test your program with.
If you need computing resources for running the experiments.
If you have a different proposal for you project
As stated many times before, obtaining the fastest program is not the absolute goal in this case. Being able to use a technology and understand its issues is as much important. Try to keep the balance.