Integrating PDC Topics with Software Engineering and Computer Network Courses at Undergraduate Level An Early Adopter Experience EduHPC-2014, New Orleans, USA Dr. Sandeep Kumar Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee (India)

Acknowledgements NSF/TCPP Early Adopter Award, Fall-2014 NSF Travel Support for EduHPC-2014

About Institute Indian Institute of Technology Roorkee (India) A premier tier-1 institute of Government of India Situated 160 KM from New Delhi in hilly and holy area in state of Uttarakhand Early Adopter Program in Department of Computer Science and Engineering

Target Course 4 Software Engineering Computer Networks Both core/compulsory courses at undergraduate level

Goals 5 Pedagogical goals corresponding to the PDC topics: Developing interest in PDC: not only learn in the class, but also perform self-learning. Equipping students with fundamental concepts of PDC. Making students to ‘think in parallel’ by providing them with ample opportunities in this direction, so that it become the part of normal practice for students in dealing with the design or development projects of any domain. Participating students to review and explore the literature to understand the effect of PDC on Software Engineering practices from various dimensions. It will prepare students to handle PDC related design and development projects with systematic methods. Participating students in using parallel computing tools and practices for existing conventional algorithms for their parallelization and to do projects using parallel programming and algorithms based aspects. It will enable students to understand the practical benefits of PDC.

Integration of PDC topics 6 TopicBloom LevelLearning OutcomeWhere integrated Web ServicesK/CKnow that web service technology forms the basis of all online user interaction With discussion on types of softwares Cloud ComputingK/CRecognize cloud w.r.t. to service- oriented software development With discussion on types of softwares Data Vs. Control ParallelismKDescribe opportunities for multiple instruction issue and execution With Software Process models Performance Issues: Computation Decomposition Strategies, Decomposition into atomic tasks CUnderstand different ways to assign computations to threads or processes With Software Measures Performance requirements of PDC systems CEffect of non-functional and functional requirements of PDC systems With discussion on SRS Performance metrics: Speepup, Efficiency, cost, Amdahl’s law, Gustafson’s law K/CKnow the basic definitions of performance metrics With discussion on Software Measures Tasks GraphsKSee it as a mechanism for exposing inter-task dependencies. With Design part Performance metrics in architecture: Bandwidth benchmark, peak performance, sustained performance, LinPack K/CAwareness of various benchmarks and how they test different aspects of performance With Performance testing With Software Engineering

7 Some Sample Project Problems Generation of Madelbrot Set on a GPU Parallel Architecture for Multiple Face Detection A cross site (programming) problem recommendation system. Ontology based automated semantic analysis of Natural Language Feedback Calculating Word Count in several documents using MapReduce

Resources Central High Performance Computing Facility of institute. GPU enabled workstations in P.G. Laboratory, along with remote login. Students owned GPU enabled laptops Microsoft Azure licenses GSU cluster under early adopter award

Conclusions Students are exposed to ‘parallel thinking’. Students liked this integration as is evident from the feedback. From pre-test and post-test results, significant improvement w.r.t. PDC topics was noticed. Students were encouraged to do research in this direction. Encouraged from this, students opted for PDC based projects and even many of them chosen problem of their interest.