Abstract
The increased use of virtualized environments has led to numerous research efforts about the possibilities and restrictions of the use of these virtualized environments in cloud computing or for resource consolidation. However, most of these studies are limited to a level of performance analysis, that does not address the effects of concurrency among the various virtual environments, and how to mitigate these effects. The study presented below proposes the concept of affinity, based on the correct combination of certain applications classes, that are able to share the same environment, at the same time, causing less loss of performance. The results show that there are combinations of applications that could share the same environment with minimum loss, but there are combinations that must be avoided. This study also shows the influence of the type of parallel library used for the implementation of these applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lee, C.A.: A perspective on scientific cloud computing. In: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC 2010, pp. 451–459. ACM, New York (2010)
Tudoran, R., Costan, A., Antoniu, G., Bougé, L.: A performance evaluation of azure and nimbus clouds for scientific applications. In: Proceedings of the 2nd International Workshop on Cloud Computing Platforms, CloudCP 2012, pp. 4:1–4:6. ACM, New York (2012)
U.S., E.D.: The magellan report on cloud computing for science (2011). http://magellan.alcf.anl.gov/
CERN: Helix nebula the science cloud: A catalyst for change in europe (2013). http://cds.cern.ch/record/1537032/files/HelixNebula-2013-002.pdf
Bientinesi, P., Iakymchuk, R., Napper, J.: HPC on competitive cloud resources. In: Furht, B., Escalante, A. (eds.) Handbook of Cloud Computing, pp. 493–516. Springer, US (2010)
Cholia, S., Shalf, J., Wasserman, H.J., Wright, N.J.: Performance analysis of high performance computing applications on the amazon web services cloud. In: Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science, CLOUDCOM 2010, pp. 159–168. IEEE Computer Society, Washington, DC (2010)
He, Q., Zhou, S., Kobler, B., Duffy, D., McGlynn, T.: Case study for running HPC applications in public clouds. In: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC 2010, pp. 395–401. ACM, New York (2010)
El-Khamra, Y., Kim, H., Jha, S., Parashar, M.: Exploring the performance fluctuations of HPC workloads on clouds. In: Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science, CLOUDCOM 2010, pp. 383–387. IEEE Computer Society, Washington, DC (2010)
Ekanayake, J., Fox, G.: High performance parallel computing with clouds and cloud technologies. In: Avresky, D.R., Diaz, M., Bode, A., Ciciani, B., Dekel, E. (eds.) CloudComp 2009. LNICST, vol. 34, pp. 20–38. Springer, Heidelberg (2009)
Skinner, D., Kramer, W.: Understanding the causes of performance variability in HPC workloads. In: 2013 IEEE International Symposium on Workload Characterization (IISWC), pp. 137–149 (2005)
Technologies, C.: The complete guide to monitoring virtualized environments (2013). http://cai.com/co/media/Files/eBooks/the-complete-guide-to-monitoring-virtualized-environments.PDF
Goscinski, W., Abramson, D.: Motor: A virtual machine for high performance computing. In: International Symposium on High-Performance Distributed Computing, pp. 171–182 (2006)
Vasić, N., Novaković, D., Miučin, S., Kostić, D., Bianchini, R.: Dejavu: accelerating resource allocation in virtualized environments. SIGARCH Comput. Archit. News 40(1), 423–436 (2012)
Colella, P.: Defining software requirements for scientific computing. DARPA HPCS Presentation (2004)
Asanovic, K., Bodik, R., Catanzaro, B.C., Gebis, J.J., Husbands, P., Keutzer, K., Patterson, D.A., Plishker, W.L., Shalf, J., Williams, S.W., Yelick, K.A.: The landscape of parallel computing research: a view from berkeley. Technical report UCB/EECS-2006-183, EECS Department, University of California, Berkeley, December 2006
Kaiser, A., Williams, S., Madduri, K., Ibrahim, K., Bailey, D., Demmel, J., Strohmaier, E.: TORCH computational reference kernels: a testbed for computer science research. Technical report UCB/EECS-2010-144, EECS Department, University of California, Berkeley, December 2010
Springer, P.: Berkeley’s Dwarfs on CUDA. Technical report, RWTH Aachen University, Seminar Project (2011)
Frigo, M., Johnson, G.S.: The design and implementation of FFTW3. In: Proceedings of the IEEE, pp. 216–231 (2005)
Blackford, L.S., Choi, J., Cleary, A.J., Demmel, J., Dhillon, I.S., Dongarra, J., Hammarling, S., Henry, G., Petitet, A., Stanley, K., Walker, D.W., Whaley, R.C.: ScaLAPACK: a portable linear algebra library for distributed memory computers - design issues and performance. In: Proceedings of the 1996 ACM/IEEE conference on Supercomputing, p. 5. IEEE (1996)
Williams, S., Oliker, L., Vuduc, R., Shalf, J., Yelick, K., Demmel, J.: Optimization of sparse matrix-vector multiplication on emerging multicore platforms. In: Proceedings of the 2007 ACM/IEEE Conference on Supercomputing, SC 2007, pp. 38:1–38:12. ACM, New York (2007)
Che, S., Boyer, M., Meng, J., Tarjan, D., Sheaffer, J.W., Lee, S.H., Skadron, K.: Rodinia: A benchmark suite for heterogeneous computing. In: IISWC, pp. 44–54. IEEE (2009)
Stratton, J.A., Rodrigrues, C., Sung, I.J., Obeid, N., Chang, L., Liu, G., Hwu, W.M.W.: Parboil: a revised benchmark suite for scientific and commercial throughput computing. Technical report IMPACT-12-01, University of Illinois at Urbana-Champaign, Urbana, March 2012
Chapman, B., Jost, G.: Pas, Rvd: Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation). The MIT Press, Cambridge (2007)
Stone, J.E., Gohara, D., Shi, G.: Opencl: a parallel programming standard for heterogeneous computing systems. IEEE Des. Test 12(3), 66–73 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Mury, A.R., Schulze, B., Licht, F.L., de Bona, L.C.E., Ferro, M. (2015). A Concurrency Mitigation Proposal for Sharing Environments: An Affinity Approach Based on Applications Classes. In: Al-Saidi, A., Fleischer, R., Maamar, Z., Rana, O. (eds) Intelligent Cloud Computing. ICC 2014. Lecture Notes in Computer Science(), vol 8993. Springer, Cham. https://doi.org/10.1007/978-3-319-19848-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-19848-4_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19847-7
Online ISBN: 978-3-319-19848-4
eBook Packages: Computer ScienceComputer Science (R0)