Abstract
With the advent of parallel computing, CS departments must face the question of how to integrate the parallel computing knowledge into the curricula. In this paper, we introduced our practice in the parallel computing education which used simulation methodology. In our course, students learned the basics of GPU architectures, parallel computing along with optimization techniques to tuning the performance. Furthermore, we elaborated the work which combined simulation-based architecture research and parallel computing – a cache simulator based on GPU. In this part, the common architecture research methodology with tool, such as simulation methodology and Pin tool were introduced. This study case has shown as an effective supplement to our teaching philosophy: balance design based on quantitative characterization.
References
The Joint Task Force on Computing Curricula Association For Computing Machinery (ACM). IEEE Computer Society, Computer science curricula 2013, 20 December 2013. DOI: 10.1145/2534860
Hennessy, J.L., Patterson, D.A.: Computer Architecture: A Quantitative Approach, 5th edn. Morgan Kaufmann, Burlington (2011). ISBN 978-0-12-383872-8
Programming Massively Parallel Processors [EB/OL]. http://www.greatlakesconsortium.org/events/GPUMulticore/agenda.html
Methods in Numerical Analysis [EB/OL]. http://www.stanfordcourses.com/CME342
GPU Programming [EB/OL]. http://www.evl.uic.edu/aej/525/
High-Performance Computing for Applications in Engineering [EB/OL]. http://sbel.wisc.edu/Courses/ME964/
CS 179, GPU Programming [EB/OL]. http://courses.cms.caltech.edu/cs101gpu/
Engineering Tool IV - Introduction to GPU Programming [EB/OL]. http://www.cse-lab.ethz.ch/index.php/teaching/42-teaching/classes/576-etvgpufall2013
CUDA University Courses [EB/OL]. http://www.nvidia.cn/object/cuda_university_courses_cn_old.html
Nvidia CUDA Zone [EB/OL]. https://developer.nvidia.com/cuda-zone
Applied Parallel Programming [EB/OL]. http://courses.engr.illinois.edu/ece408/
Kirk, D.B., Hwu, W.-M.W.: Programming Massively Parallel Processors: A Hands-On Approach. Morgan Kaufmann Publishers, Burlington (2010). ISBN 0-123-81472-3
Wan, H., Long, X., Gao, X.P., Li, Y.: GPU accelerating for rapid multi-core cache simulation. In: 25th IEEE International Parallel & Distributed Processing Symposium, IPDPS2011, Anchorage, AL, United states, pp. 1387–1396. IEEE Computer Society (2011)
Pin - A Dynamic Binary Instrumentation Tool (EB/OL). https://software.intel.com/en-us/articles/pintool
Uhlig, R.A., Mudge, T.N.: Trace-driven memory simulation: a survey. ACM Comput. Surv. 29, 128–170 (1997)
Reddi, V., Settle, A.M., Connors, D.A. Cohn, R.S.: Pin: a binary instrumentation tool for computer architecture research and education. In: Proceedings of the Workshop on Computer Architecture Education, June 2004
Han, W., Gao, X., Long, X., Wang, Z.: Using GPU to accelerate a pin-based multi-level Cache simulator. In: Spring Simulation Multiconference 2010, SpringSim 2010
Kiesling, T.: Using approximation with time-parallel simulation. Simulation. 81(4), 255–266 (2005)
Denning, P.J.: Great principles of computing. Commun. ACM 46(11), 15–20 (2003)
Acknowledgments
This work is funded by China Scholarship Council (No. 201406025114) and the National High Technology Research and Development Program (2007AA01Z183).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Wan, H., Luo, X., Gao, X., Long, X. (2016). Parallel Computing Education Through Simulation. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 643. Springer, Singapore. https://doi.org/10.1007/978-981-10-2663-8_60
Download citation
DOI: https://doi.org/10.1007/978-981-10-2663-8_60
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-2662-1
Online ISBN: 978-981-10-2663-8
eBook Packages: Computer ScienceComputer Science (R0)