Parallel & Distributed Systems

:::Home > Teaching Activities > Mentorship > Student Research Themes > Parallel & Distributed Systems

As problems grow larger and data sets become massive, a single computer is no longer enough to handle the workload. The theme “Parallel & Distributed Systems: Scale, Scheduling & HPC” focuses on how multiple processors, machines, or even entire clusters can work together to solve complex problems efficiently. From high-performance computing (HPC) that drives scientific discovery to distributed systems that power modern cloud services, this field lies at the core of scalable computing.

The rationale for this theme is that performance and efficiency are not just about faster processors, but about smarter coordination. Students learn how to break big problems into smaller parts, schedule tasks across resources, and design systems that remain reliable even as they grow in scale. By mastering these concepts, they gain the skills to push the boundaries of computation, from simulations of natural phenomena to real-time services used every day.

AGARRADO, Mark Timothy S., BSCS 2008
Parallel implementation of text searching algorithms on a grid environment
AGCAOILI, Vanny Claire, BSCS 2000
Online Network Statistics: Dialup1
AYCO, Ramon Jr. P., BSCS 2011
Implementation of various loop scheduling algorithms on desktop grids
DE ROBLES, Marie Yvette B., MSCS 2013
A Comparison of various distributed architectures for a desktop web grid
DE ROBLES, Marie Yvette B., BSCS 2009 cum laude
A prototype distributed desktop web grid
ITOL, Mark R.G., BSCS 2006
Near-optimal TDMA scheduling using ant colony optimization
JAMON, Marc Glenn O., BSCS 2006
A framework for memory-bound parallel graphics rendering using a cluster of tiled display and independent controls
MAGA, Bernadette Rose G., BSCS 2006 cum laude
Parallel stream delineation
SABLE, Roel, BSCS 1998
A preprocessor for a multiple objective linear programming software

Students are encouraged to join this theme by building solutions that leverage parallelism and distribution. Whether the students' projects involve optimizing algorithms for multicore processors, designing efficient schedulers, or exploring large-scale simulations, the projects help push computing into new frontiers. By contributing here, the student takes part in shaping the backbone of tomorrow’s computational systems.