CS402 High Performance Computing Skip to main content Skip to navigation Sign in Study Research Business Alumni News Engagement Search Warwick Search Department of Computer Science Study with us Undergraduate Degrees Postgraduate Taught Degrees Degree Apprenticeships Teaching Coronavirus(Restricted permissions) DCS Self Isolation Notification Student Support Appointment Booking Form Course Structures Student Handbook(Restricted permissions) Modules Taught Research Doctoral Studies Interdisciplinary Research Centres Impact and Innovation Applied Computing Artificial Intelligence and Human-Centred Computing Data Science, Systems and Security Theory and Foundations People News Events Computer Science Colloquium Outreach News Upcoming Events Past Events Projects Staff Resources(Restricted permissions) Report(Restricted permissions) Welfare Athena SWAN Dignity at Warwick Equality, Diversity and Inclusion News Vacancies Intranet(Restricted permissions) Teaching Modules Taught CS402 CS402 High Performance Computing CS402-15 High Performance Computing Academic year 21/22 Department Computer Science Level Undergraduate Level 4 Module leader Ligang He Credit value 15 Module duration 10 weeks Assessment Multiple Study location University of Warwick main campus, Coventry Download as PDF Description Study Assessment Availability Introductory description The module provides a solid foundation in High Performance Computing (HPC) and its role in science and engineering. Module aims The module provides a solid foundation in High Performance Computing (HPC) and its role in science and engineering. The aim of the module is to study the fundamental techniques for developing HPC applications, the commonly used HPC platforms, the methods for measuring, assessing and analysing the performance of HPC applications, and the role of administration, workload and resource management in an HPC management software. The students will be introduced to the issues related to the use of HPC techniques in solving large scientific problems. Outline syllabus This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ. Fundamental concepts in High Performance Computing. Shared memory programming (OpenMP). Message passing programming (MPI). GPU programming. Parallel decomposition. Performance measurement and analysis. High performance I/O. High performance networking. High Performance Computing systems. Typical scientific applications. Learning outcomes By the end of the module, students should be able to: Understand the role of HPC in science and engineering. Be familiar with popular parallel programming paradigms. Understand commonly used HPC platforms with particular reference to Cluster system. Understand the means by which to measure, assess and analyse the performance of HPC applications. Understand the role of administration, workload and resource management in an HPC management software. Understand the mechanisms for evaluating the suitability of different HPC solutions to solving scientific problems. Indicative reading list Suggested Reading: Peter Pacheco, Introduction to Parallel Programming, Morgan Kaufmann Publishers, 2011; Michael J. Quinn, Parallel programming in C with MPI and OpenMP, McGraw-Hill Higher Education, 2004; William Gropp, Using MPI: portable parallel programming with the message-passing interface, MIT press, 1999; Further reading: Introduce the Graph 500; Further Reading: A Note on the Zipf Distribution of Top500 Supercomputers; Further Reading: Vectorizing C Compilers - How Good Are They?; Further Reading: Further Reading in High Performance Compilers for Parallel Computing; Subject specific skills analytical skills by applying the HPC knowledge learned in this module to develop HPC applications and analyzing their performance, mathmatical thinking skills by linking rigor in performance modelling with the design of parallelization strategies, problem solving and IT skills by applying the learned knowledge to do practical lab sesssions and the courseworks; presentation and communication skills by writing the report of presenting the practical work conducted in the courseworks and discussing the experimental results; critical thinking skills by analyzing and comparing the pros and cons of different HPC solutions. Transferable skills Communication and presentation skills Study time Type Required Lectures 20 sessions of 1 hour (13%) Practical classes 10 sessions of 1 hour (7%) Private study 120 hours (80%) Total 150 hours Private study description Private study for comprehending the teaching contents. Reading further materials given in the lectures. Independent studies for doing the practical lab sessions. Private studies for doing the coursework. Revision for the final exam. Costs No further costs have been identified for this module. You do not need to pass all assessment components to pass the module. Students can register for this module without taking any assessment. Assessment group D4 Weighting Study time Coursework 1 10% Develop a parallel application with OpenMP. Benchmark and analyze the runtime of the code. Write a report to present the development and benchmarking work, and present and discuss the experimental results. Coursework 2 20% Develop a parallel application in the area of computational fluid dynamics with the pure MPI model and with the hybrid approach combining MPI and OpenMP. Benchmark and analyze the runtime of the developed code. Write a report to present the development and benchmarking work, and present and discuss the experimental results. On-campus Examination 70% CS402 examination ~Platforms - AEP Answerbook Pink (12 page) Students may use a calculator Assessment group R1 Weighting Study time Online Examination 100% CS402 resit examination ~Platforms - AEP Online examination: No Answerbook required Students may use a calculator Feedback on assessment Individual written feedback on Assessed Coursework. Oral feedback where appropriate, e.g. for presentations. Past exam papers for CS402 Pre-requisites MEng students must have studied the material in CS132. Courses This module is Optional for: Year 5 of UCSA-G504 MEng Computer Science (with intercalated year) Year 4 of UCSA-G402 MEng Computing Systems Year 5 of UCSA-G403 MEng Computing Systems (Intercalated Year) Year 1 of TCSA-G5PD Postgraduate Taught Computer Science Year 1 of TCSA-G5P8 Postgraduate Taught Computer Science and Applications Year 1 of TCSA-G5PB Postgraduate Taught Data Analytics (CUSP) Year 1 of TESA-H121 Postgraduate Taught Information Engineering (CUSP) Year 4 of UCSA-G503 Undergraduate Computer Science MEng Year 4 of USTA-G1G3 Undergraduate Mathematics and Statistics (BSc MMathStat) Year 5 of USTA-G1G4 Undergraduate Mathematics and Statistics (BSc MMathStat) (with Intercalated Year) This module is Option list A for: Year 4 of UCSA-G402 MEng Computing Systems Year 5 of UCSA-G403 MEng Computing Systems (Intercalated Year) Year 4 of UCSA-G408 Undergraduate Computer Systems Engineering Year 4 of USTA-G304 Undergraduate Data Science (MSci) This module is Option list B for: Year 5 of UCSA-G504 MEng Computer Science (with intercalated year) Year 4 of UCSA-G503 Undergraduate Computer Science MEng Year 4 of UCSA-G4G3 Undergraduate Discrete Mathematics Further Information Term 2 15 CATS (7.5 ECTS) Online Material Additional Information Module Organisers: Ligang He Richard Kirk Department of Computer Science, University of Warwick, CV4 7AL E-mail: comp-sci at dcs dot warwick dot ac dot uk, Telephone: +44 (0)24 7652 3193 DCS Intranet FacebookTwitterLinkedIn Page contact: Jennifer Mills Last revised: Tue 22 Feb 2022 Powered by Sitebuilder © MMXXII Terms Privacy Cookies Accessibility Coronavirus (Covid-19): Latest updates and information Let us know you agree to cookies We use cookies to give you the best online experience. 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