SIGCSE 2020 Workshop 105: part of Parallel Computing in the Computer Science Curriculum:Workshops
Wednesday 3/11/20, 7:00-10:00pm, B112 Instructors: Elizabeth Shoop (Macalester College); Joel Adams (Calvin University); Suzanne Matthews (West Point); Richard Brown (St. Olaf College) Do you need a fast way to ...

SIGCSE 2019 Workshop 102: part of Parallel Computing in the Computer Science Curriculum:Workshops
Wednesday 2/27/19, 7:00-10:00pm Hyatt Greenway B (2nd floor) Instructors: Suzanne Matthews (West Point), Joel Adams (Calvin College), Dick Brown (St. Olaf College), and Libby Shoop (Macalester College) Are you ...

SIGCSE 2022 Workshop 101: part of Parallel Computing in the Computer Science Curriculum:Workshops
Wednesday 3/2/22, 7:00-10:00pm Narragansett Ballroom A (Omni) Instructors: Elizabeth Shoop (Macalester College); Joel Adams (Calvin University); Suzanne Matthews (West Point); Richard Brown (St. Olaf College) Do ...

CSinParallel Summer 2021 Virtual Workshop part of Parallel Computing in the Computer Science Curriculum:Workshops
June 21-23, 2021 This workshop will bring together a community of educators who are committed to increasing the amount of parallel and distributed computing knowledge and skills of undergraduates in their Computer ...

SC '12 HPC Educator Workshop: part of Parallel Computing in the Computer Science Curriculum:Workshops:SC12 HPC Educator Workshop
CSInParallel: An incremental approach to adding PDC throughout the CS curriculum Presented by Richard Brown, Libby Shoop, and Joel Adams Thursday, Nov. 15, 1:30 - 5:30 Welcome The CSInParallel project ...

Map-reduce Computing for Introductory Students using WebMapReduce part of Parallel Computing in the Computer Science Curriculum:Modules:Modules Mini-collection
This module emphasizes data-parallel problems and solutions, the so-called 'embarrassingly parallel' problems where processing of input data can easily be split among several parallel processes. Students use a web application called WebMapReduce (WMR) to write map and reduce functions that operate on portions of a massive dataset in parallel.

Concurrent Access to Data Structures part of Parallel Computing in the Computer Science Curriculum:Modules:Modules Mini-collection
This module enables students to experiment with creating a task-parallel solution to the problem of crawling the web by using Java threads and thread-safe data structures available in the java.util.concurrent package.

Parallel Computing Concepts part of Parallel Computing in the Computer Science Curriculum:Modules:Modules Mini-collection
This concept module will introduce a core of parallel computing notions that CS majors and minors should know in preparation for the era of manycore computing, including parallelism categories, concurrency issues and solutions, and programming strategies.

Multicore Programming with OpenMP part of Parallel Computing in the Computer Science Curriculum:Modules:Modules Mini-collection
In this lab, we will create a program that intentionally uses multi-core parallelism, upload and run it on the MTL, and explore the issues in parallelism and concurrency that arise. This module uses OpenMP.

Workshop Overview part of Parallel Computing in the Computer Science Curriculum:Workshops:Delaware Valley 2016
Multi-core computers with increasing core counts are here to stay, and distributed cloud computation has become a staple of industry innovation. How can instructors help today's undergraduate computer science ...