Comprehensive Collection of Time-Consuming Problems for Intensive Training on High Performance Computing

  • Iosif Meyerov
  • Sergei Bastrakov
  • Alexander Sysoyev
  • Victor GergelEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 965)


Training specialists capable of applying models, methods, technologies and tools of parallel computing to solve problems is of great importance for further progress in many areas of modern science and technology. Qualitative training of such engineers requires the development of appropriate curriculum, largely focused on practice. In this paper, we present a new handbook of problems on parallel computing. The book contains methodological materials, problems and examples of their solution. The final section describes the automatic solution verification software. The handbook of problems will be employed to train students of the Lobachevsky University of Nizhni Novgorod.


Parallel computing High performance computing Education 


  1. 1.
    Andrews, G.R.: Foundations of Parallel and Distributed Programming. Addison-Wesley Longman Publishing Co., Inc., Boston (1999)Google Scholar
  2. 2.
    Kumar, V., Grama, A., Gupta, A., Karypis, G.: Introduction to Parallel Computing, 612 p. Pearson Education, Harlow (2003)Google Scholar
  3. 3.
    Wilkinson, B., Allen, M.: Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers. Prentice Hall, Upper Saddle River (1999)Google Scholar
  4. 4.
    Voevodin V.V., Voevodin V.V.: Parallel Computations. BHV-Petersburg, Saint-Petersburg (2002, in Russian)Google Scholar
  5. 5.
    Gergel, V.P.: Theory and Practice of Parallel Computations. Binom, Moscow (2007). (in Russian)Google Scholar
  6. 6.
    Pacheco, P.: Parallel Programming with MPI. Morgan Kaufmann, San Francisco (1996)zbMATHGoogle Scholar
  7. 7.
    Gropp, W., Lusk, E., Skjellum, A.: Using MPI – 2nd Edition: Portable Parallel Programming with the Message Passing Interface (Scientific and Engineering Computation). MIT Press, Cambridge (1999a)Google Scholar
  8. 8.
    Gropp, W., Lusk, E., Thakur, R.: Using MPI-3: Advanced Features of the Message Passing Interface (Scientific and Engineering Computation). MIT Press, Cambridge (1999b)Google Scholar
  9. 9.
    Nemnyugin, S., Stecik, O.: Parallel Programming for Multiprocessor Computing Systems. BHV-Petersburg, Saint-Petersburg (2002)Google Scholar
  10. 10.
    Gergel, V., et al.: Parallel Numerical Methods and Technologies. UNN Press (2013, in Russian)Google Scholar
  11. 11.
    Chandra, R., et al.: Parallel Programming in OpenMP. Morgan Kaufmann Publishers, Burlington (2000)Google Scholar
  12. 12.
    Jeffers, J., Reinders, J.: Intel Xeon Phi Coprocessor High Performance Programming. Newnes, Oxford (2013)Google Scholar
  13. 13.
    Jeffers, J., Reinders, J., Sodani, A.: Intel Xeon Phi Processor High Performance Programming: Knights Landing Edition. Morgan Kaufmann, Boston (2016)Google Scholar
  14. 14.
    Jeffers, J., Reinders, J.: High Performance Parallelism Pearls Volume One: Multicore and Many-Core Programming Approaches. Morgan Kaufmann, San Francisco (2014)Google Scholar
  15. 15.
    Jeffers, J., Reinders, J.: High Performance Parallelism Pearls Volume Two: Multicore and Many-core Programming Approaches. Morgan Kaufmann, San Francisco (2015)Google Scholar
  16. 16.
    Sanders, J., Kandrot, E.: CUDA By Example: An Introduction to General-Purpose GPU Programming. Addison-Wesley Professional, Boston (2010)Google Scholar
  17. 17.
    Pharr, M., Fernando, R.: GPU Gems 2: programming Techniques for High-Performance Graphics and General-Purpose Computation. Addison-Wesley Professional, Reading (2005)Google Scholar
  18. 18.
    Nguyen, H.: GPU Gems 3. Addison-Wesley Professional, Reading (2007)Google Scholar
  19. 19.
    Quinn, M.J.: Parallel Programming in C with MPI and OpenMP. McGraw-Hill, New York (2004)Google Scholar
  20. 20.
    Prasad, S.K., et al.: NSF/IEEE-TCPP curriculum initiative on parallel and distributed computing – core topics for undergraduates, Version I (2012).
  21. 21.
    Prasad, S.K., Gupta, A., Rosenberg, A.L., Sussman, A., Weems, C.C. (eds.): Topics in Parallel and Distributed Computing: Introducing Concurrency in Undergraduate Courses. Morgan Kaufmann, San Francisco (2015)Google Scholar
  22. 22.
    Voevodin, V., Gergel, V., Popova, N.: Challenges of a systematic approach to parallel computing and supercomputing education. In: Hunold, S., et al. (eds.) Euro-Par 2015. LNCS, vol. 9523, pp. 90–101. Springer, Cham (2015). Scholar
  23. 23.
    Gergel, V., Liniov, A., Meyerov, I., Sysoyev, A.: NSF/IEEE-TCPP curriculum implementation at University of Nizhni Novgorod. In: Proceedings of Fourth NSF/TCPP Workshop on Parallel and Distributed Computing Education, pp. 1079–1084 (2014)Google Scholar
  24. 24.
    Gergel, V., Kozinov, E., Linev, A., Shtanyk, A.: Educational and research systems for evaluating the efficiency of parallel computations. In: Carretero, J., et al. (eds.) ICA3PP 2016. LNCS, vol. 10049, pp. 278–290. Springer, Cham (2016). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Iosif Meyerov
    • 1
  • Sergei Bastrakov
    • 2
    • 1
  • Alexander Sysoyev
    • 1
  • Victor Gergel
    • 1
    Email author
  1. 1.Lobachevsky State University of Nizhni NovgorodNizhni NovgorodRussia
  2. 2.Helmholtz-Zentrum Dresden-RossendorfDresdenGermany

Personalised recommendations