Making parallel programming accessible to inexperienced programmers through cooperative learning
Proceedings of the thirty-second SIGCSE technical symposium on Computer Science Education
Experience teaching hands-on parallel computing at a small college
Journal of Computing Sciences in Colleges
Parallel and Distributed Programming Using C++
Parallel and Distributed Programming Using C++
The potential of the cell processor for scientific computing
Proceedings of the 3rd conference on Computing frontiers
Getting more from your virtual machine
Journal of Computing Sciences in Colleges
Hands-on grid computing with Globus Toolkit 4
Journal of Computing Sciences in Colleges
The role of large scale computing in computer science education: panel presentation
Journal of Computing Sciences in Colleges - Papers of the twelfth annual CCSC Northeastern Conference
A visual tool for teaching multithreading in Java
Journal of Computing Sciences in Colleges - Papers of the twelfth annual CCSC Northeastern Conference
Journal of Computing Sciences in Colleges
Teaching high-performance computing in the undergraduate college CS curriculum
Journal of Computing Sciences in Colleges
Journal of Computing Sciences in Colleges
Comparing parallel programming models
Journal of Computing Sciences in Colleges
A pilot study to compare programming effort for two parallel programming models
Journal of Systems and Software
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Fitting scientific computing training in a small liberal arts college curricula has always been a challenge, and even more so in an era when new hardware and architecture are emerging almost on a yearly basis which makes some of the learning objectives a moving target. When video game consoles are commanded by the 'supercomputing on a chip' processor CELL, and multi-core CPUs become the mainstream of lower end desktop solution, we are witnessing a renewed demand from students to offer a course in parallel computing. This paper attempts to address these challenges by weighing the interest of students, the efficiency of various parallel programming models as well as the resource limitations of a small college. In a progressive way, we present a pragmatic approach of teaching parallel computing designed particularly in response to the changing landscape in scientific computing and the wide adoption of multi-core processors.