An integrated course on parallel and distributed processing
SIGCSE '98 Proceedings of the twenty-ninth SIGCSE technical symposium on Computer science education
A concurrency simulator designed for sophomore-level instruction
SIGCSE '98 Proceedings of the twenty-ninth SIGCSE technical symposium on Computer science education
UML Distilled: A Brief Guide to the Standard Object Modeling Language
UML Distilled: A Brief Guide to the Standard Object Modeling Language
ThreadMentor: a pedagogical tool for multithreaded programming
Journal on Educational Resources in Computing (JERIC)
Performance implications of single thread migration on a chip multi-core
ACM SIGARCH Computer Architecture News - Special issue: dasCMP'05
Computer
Parallel Programming in C with MPI and OpenMP
Parallel Programming in C with MPI and OpenMP
A visual tool for teaching multithreading in Java
Journal of Computing Sciences in Colleges - Papers of the twelfth annual CCSC Northeastern Conference
Multi-core design automation challenges
Proceedings of the 44th annual Design Automation Conference
Building Parallel Programs: SMPs, Clusters & Java
Building Parallel Programs: SMPs, Clusters & Java
Measuring CS1 perceptions of parallelism
FIE '11 Proceedings of the 2011 Frontiers in Education Conference
Proceeding of the 44th ACM technical symposium on Computer science education
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Laboratory work in the CS classroom is intended to solidify essential concepts and core design principles. Because of recent advances and the widespread adoption of multicore technologies, one area of investigation that has become increasingly important across all levels of CS instruction is parallel computing. This paper describes the initial version of the Parallel Analysis Tool (PAT), a pedagogical tool designed to assist undergraduate students in visualizing concurrency and effectively connecting parallel processing to applied coding strategies. The PAT is a complete Java development environment, with an emphasis on (1) helping students to identify appropriate code locations where parallelization can be applied and (2) allowing students to subsequently examine the practical performance tradeoffs of these parallelization decisions in a laboratory setting. The Parallel Quotient (PQ), a fundamental dimensionless metric generated by the PAT, supports the student's conceptual understanding and analysis of the relative benefits of employing various parallel programming strategies.