User:Chris Szalwinski

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Revision as of 10:50, 25 March 2012 by Chris Szalwinski (talk | contribs) (Applied Research (Potential - Winter 2013))
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Chris Szalwinski
Chris Szalwinski.jpg
Faculty Picture
Occupation Seneca College
School of Information and Communications Technology
Faculty
Office T2093
Phone 416.491.5050 ext 33364
IRC
ICT Home Page https://scs.senecac.on.ca/~chris.szalwinski/
Blog
Email chris dot szalwinski at senecac dot on dot ca

Chris Szalwinski is a Professor at the School of Information and Communications Technology at Seneca College.

Chris teaches C, C++, DirectX Game Programming, and Human Computer Interaction.

Courses

Courses Taught

OOP244 - Introduction to Object-Oriented Programming
Further information: OOP244 Web Site OOP244 Wiki
BTP200 - The Object-Oriented Paradigm using C++
Further information: BTP200 Web Site
BTP300 - Object-Oriented Software Development I - C++
Further information: BTP300 Web Site BTP300 Wiki
BTH740 - Human Computer Interaction
Further information: BTH740 Web Site BTH740 Wiki
GAM666, DPS901 - Introduction to 3D Game Programming
Further information: GAM666 and DPS901 Web Site GAM666 and DPS901 Wiki
GAM670, DPS905 - 3D Game Programming Techniques
Further information: GAM670 and DPS905 Web Site GAM670 and DPS905 Wiki

New ICT Courses (Fall 2012)

  • GPU610 Parallel Programming Fundamentals
Modern GPU (Graphics Processing Unit) technology supports massively parallel computations, which complements the serial processing capabilities of CPU technology. This course teaches students how to parallelize serial code and how to program the GPU. Students learn to read, write, and debug simple heterogeneous programs. Students also study cases that have benefited from parallelization.
Pre-requisite: OOP344
  • DPS915 Introduction to Parallel Programming
Modern GPU (Graphics Processing Unit) technology supports massively parallel computations, which complements the serial processing capabilities of CPU technology. This course teaches students how to parallelize serial code and how to program the GPU. Students learn to read, write, and debug simple heterogeneous programs. Students also study cases that have benefited from parallelization and develop a heterogeneous application for a client.
Pre-requisite: BTP300

Applied Research (Potential - Winter 2013)

  • Heterogeneous Computing (CPU/GPU)

Personal Interests

  • numerical methods algorithms for open source libraries
  • direct heterogeneous solution techniques (frontal)
  • non-linear finite elements
  • friction and partial-slip

Cross-References

External links

Publications