Abstract
An energy consumption analysis of the Nussinov RNA folding algorithm implementations is discussed in this paper. We consider parallel and cache-efficient Nussinov codes generated automatically by the Traco and PluTo optimizing compilers and the manual implementation known as Transpose (Li et al.). The experimental study presents the times and power consumption of optimized code using the modern Intel i7 processor with 12 threads. We apply the Intel RAPL technique to measure energy on the processor socket, cores, and RAM. The access to the Linux kernel energy events is provided by the perf tool. We analyze the power consumption in terms of the execution times of the Nussinov codes for various RNA sequences lengths and number of threads.
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
Almeida, F., Andonov, R., Gonzalez, D., Moreno, L.M., Poirriez, V., Rodriguez, C.: Optimal tiling for the RNA base pairing problem. In: Proceedings of the Fourteenth Annual ACM Symposium on Parallel Algorithms and Architectures, SPAA 2002, pp. 173–182. ACM, New York (2002)
Bielecki, W., Palkowski, M.: A parallelizing and optimizing compiler - TRACO (2013). http://traco.sourceforge.net
Bielecki, W., Palkowski, M.: Tiling of arbitrarily nested loops by means of the transitive closure of dependence graphs. Int. J. Appl. Math. Comput. Sci. (AMCS) 26(4), 919–939 (2016)
Bondhugula, U., Hartono, A., Ramanujam, J., Sadayappan, P.: A practical automatic polyhedral parallelizer and locality optimizer. SIGPLAN Not. 43(6), 101–113 (2008)
Frid, Y., Gusfield, D.: An improved Four-Russians method and sparsified Four-Russians algorithm for RNA folding. Algorithms Mol. Biol. 11(1), 22 (2016). https://doi.org/10.1186/s13015-016-0081-9
Intel Corporation: Intel\(^{\textregistered }\) 64 and IA-32 Architectures Software Developer’s Manual, Volume 3B: System Programming Guide, Part 2, September 2016. https://www.intel.com/content/dam/www/public/us/en/documents/manuals/64-ia-32-architectures-software-developer-vol-3b-part-2-manual.pdf
Jacob, A.C., Buhler, J.D., Chamberlain, R.D.: Rapid RNA folding: analysis and acceleration of the Zuker recurrence. In: 2010 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), pp. 87–94 (2010)
Li, J., Ranka, S., Sahni, S.: Multicore and GPU algorithms for Nussinov RNA folding. BMC Bioinf. 15(8), S1 (2014). https://doi.org/10.1186/1471-2105-15-S8-S1
Liu, L., Wang, M., Jiang, J., Li, R., Yang, G.: Efficient nonserial polyadic dynamic programming on the cell processor. In: 25th IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2011, Anchorage, Alaska, USA, 16–20 May 2011 - Workshop Proceedings, pp. 460–471 (2011)
Mullapudi, R.T., Bondhugula, U.: Tiling for dynamic scheduling. In: Rajopadhye, S., Verdoolaege, S. (eds.) Proceedings of the 4th International Workshop on Polyhedral Compilation Techniques, Vienna, Austria, January 2014
Nussinov, R., Pieczenik, G., Griggs, J.R., Kleitman, D.J.: Algorithms for loop matchings. SIAM J. Appl. Mat. 35(1), 68–82 (1978)
OpenMP Architecture Review Board: OpenMP application program interface version 4.0 (2013). http://www.openmp.org/mp-documents/OpenMP4.0.0.pdf
Palkowski, M.: Finding free schedules for RNA secondary structure prediction. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS (LNAI), vol. 9693, pp. 179–188. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39384-1_16
Palkowski, M., Bielecki, W.: Parallel tiled Nussinov RNA folding loop nest generated using both dependence graph transitive closure and loop skewing. BMC Bioinf. 18(1), 290 (2017)
Palkowski, M., Bielecki, W.: Tuning iteration space slicing based tiled multi-core code implementing Nussinov’s RNA folding. BMC Bioinf. 19(1), 12 (2018)
de Melo, A.C.: The new linux ‘perf’ tools. Technical report, Linux Kongress, Georg Simon Ohm University Nuremberg/Germany (2010)
Tan, G., Feng, S., Sun, N.: Locality and parallelism optimization for dynamic programming algorithm in bioinformatics. In: SC 2006 Conference, Proceedings of the ACM/IEEE, p. 41 (2006)
Wonnacott, D., Jin, T., Lake, A.: Automatic tiling of “mostly-tileable” loop nests. In: IMPACT 2015: 5th International Workshop on Polyhedral Compilation Techniques, at Amsterdam, The Netherlands (2015)
Zhao, C., Sahni, S.: Cache and energy efficient algorithms for Nussinov’s RNA folding. BMC Bioinf. 18(15), 518 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Palkowski, M. (2019). Energy Consumption Analysis of the Nussinov RNA Folding Implementations. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-20915-5_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-20914-8
Online ISBN: 978-3-030-20915-5
eBook Packages: Computer ScienceComputer Science (R0)