A module-based introduction to heterogeneous computing in core courses.

• Heterogeneous parallel computing is rarely taught in required undergraduate courses. • Concepts of heterogeneous computing can be taught even in CS1 and CS2. • Pollack's Rule and Amdahl's Law help motivate the shift to heterogeneous processors. • Using ARM processors, an instructor can show a low-power mode and SIMD operations. Heterogeneous architectures have emerged as a dominant platform, not only in high-performance computing but also in mobile processing, cloud computing, and the Internet of Things (IoTs). Because the undergraduate computer science curriculum includes so many topics, adding a new course as a required part of the curriculum without increasing the number of hours to graduation is difficult. Integration of heterogeneous computing requires a module-driven approach in which coverage of the topics is broken down into smaller units and dispersed throughout the curriculum. The module-driven approach has been successfully implemented in introducing parallel and distributed computing concepts. In this paper, we present a set of four teaching modules that introduce fundamental concepts in heterogeneous computing in lower-division computer science courses. The goal of these modules is not to teach students how to program heterogeneous systems but rather to expose them to this emerging trend and prepare them for material in future classes. Although concepts are covered at a high level, the modules emphasize active learning and include lab assignments that provide students with hands-on experience. We also present initial evaluation results for two of these modules based on their use in undergraduate courses at Texas State University. The results are quite encouraging both in terms of learning outcomes and student engagement and interest. [ABSTRACT FROM AUTHOR]