Applying selectively parallel I/O compression to parallel storage systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8632 LNCS, Issue , 2014, Pages 282-293

  Filgueira, Rosa ^a   Atkinson, Malcolm ^a   Tanimura, Yusuke ^b   Kojima, Isao ^b  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

Author keywords

Adaptive systems; Compression algorithms; Data Intensive Computing; Parallel File System

Indexed keywords

ADAPTIVE SYSTEMS; DIGITAL STORAGE; FILE ORGANIZATION;

COMPRESSION ALGORITHMS; COMPRESSION TECHNIQUES; DATA MOVEMENTS; DATA-INTENSIVE COMPUTING; PARALLEL FILE SYSTEM; PARALLEL STORAGE SYSTEMS; STORAGE AND ACCESS; STORAGE SYSTEMS; PARALLEL I/O;

DATA COMPRESSION;

EID: 84958531976     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-09873-9_24     Document Type: Conference Paper

References (25)

1. Gu, Y., Grossman, R.L.: Toward efficient and simplified distributed data intensive computing. IEEE Trans. Parallel Distrib. Syst., 974-984 (2011)
2. CFS Inc., Lustre: A scalable, high-performance file system, cluster File Systems Inc. white paper, version 1.0 (2002)
3. Schmuck, F., Haskin, R.: GPFS: A shared-disk file system for large computing clusters. In: Proc. of the First Conference on File and Storage Technologies (FAST), pp. 231-244 (January 2002)
4. Tanimura, Y., Hidetaka, K., Kudoh, T., Kojima, I., Tanaka, Y.: A distributed storage system allowing application users to reserve i/o performance in advance for achieving sla. In: GRID, pp. 193-200 (2010)
5. Kella, K.K., Khanum, A.: Apcfs: Autonomous and parallel compressed file system. International Journal of Parallel Programming 39(4), 522-532 (2011)
6. Fusecompress, a linux file-system that transparently compresses its contents (2011), http://code.google.com/p/fusecompress/
7. Klonatos, Y., Makatos, T., Marazakis, M., Flouris, M.D., Bilas, A.: Transparent online storage compression at the block-level. TOS 8(2), 5 (2012)
8. Harnik, D., Kat, R., Sotnikov, D., Traeger, A., Margalit, O.: To zip or not to zip: Effective resource usage for real-time compression. Presented as Part of the 11th USENIX Conference on File and Storage Technologies. USENIX, Berkeley (2013), https://www.usenix.org/conference/fast13/zip-or-not-zip- effectiveresource- usage-real-time-compression
9. Filgueira, R., Singh, D.E., Carretero, J., Calderón, A., García, F.: Adaptive-compi: Enhancing mpi-based applications performance and scalability by using adaptive compression. IJHPCA 25(1), 93-114 (2011)
10. Filgueira, R., Atkinson, M., Nuñez, A., Fernández, J.: An adaptive, scalable, and portable technique for speeding upmpi-based applications. In:Kaklamanis,C., Papatheodorou, T., Spirakis, P.G. (eds.) Euro-Par 2012. LNCS, vol. 7484, pp. 729-740. Springer, Heidelberg (2012)
11. Real time data compress (2012), http://fastcompression.blogspot.co.uk/p/ lz4.html
12. Russell, J., Cohn, R.: Snappy. Book on Demand (2012), http://books.google.co.uk/books?id=PXajMQEACAAJ
13. Filgueira, R., Singh, D.E., Calderón, A., Carretero, J.: Compi: Enhancing mpi based applications performance and scalability using run-time compression. In: Ropo, M.,Westerholm, J., Dongarra, J. (eds.) EuroPVM/MPI 2009. LNCS, vol. 5759, pp. 207-218. Springer,Heidelberg (2009)
14. Loureiro, A., González, J., Pena, T.F.: A parallel 3D semiconductor device simulator for gradual heterojunction bipolar transistors. Int. Journal of Numerical Modelling: Electronic Networks, Devices and Fields 16, 53-66 (2003)
15. Raskhodnikova, S., Ron, D., Rubinfeld, R., Smith, A.: Sublinear algorithms for approximating string compressibility. Algorithmica 65(3), 685-709 (2013), http://dblp.uni-trier.de/db/journals/algorithmica/algorithmica65. htmlRaskhodnikovaRRS13
16. Fan, D., Zhang, H.,Wang, D., Ye, X., Song, F., Li, G., Sun, N.: Godson-t: An efficient manycore processor exploring thread-level parallelism. IEEE Micro 99(1), 5555
17. Pusukuri, K.K., Gupta, R., Bhuyan, L.N.: Thread reinforcer: Dynamically determining number of threads via os level monitoring. In: Proceedings of the 2011 IEEE International Symposium on Workload Characterization. IISWC 2011, pp. 116-125. IEEE Computer Society, Washington, DC (2011)
18. Pusukuri, K.K., Gupta, R., Bhuyan, L.N.: Adapt: A framework for coscheduling multithreaded programs. ACM Trans. Archit. Code Optim. 9(4), 45:1-45:24 (2013)
19. Linked geo data (July 18, 2009), http://downloads.linkedgeodata.org/ releases/2009-07-01/
20. Geo names (September 2009), http://www.geonames.org/ontology/ documentation.html
21. Mahoney, M.: Large text compression benchmark (August 2013), http://mattmahoney.net/dc/text.html
22. Bell, A.F., Greenhough, J., Heap, M.J., Main, I.G.: Challenges for forecasting based on accelerating rates of earthquakes at volcanoes and laboratory analogues. Geophysical Journal International 185(2), 718-723 (2011)
23. Jégou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. IEEE Transactions on Pattern Analysis & Machine Intelligence 33(1), 117-128 (2011) (to appear)
24. Torralba, A., Fergus, R., Freeman,W.T.: 80 million tiny images: A large data set for nonparametric object and scene recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(11), 1958-1970 (2008)
25. Greshock, J., Bachman, K.E., Degenhardt, Y.Y., Jing, J., Wen, Y.H., Eastman, S., McNeil, E., Moy, C., Wegrzyn, R., Auger, K., Hardwicke, M.A.: Molecular target class is predictive of in vitro response profile. Cancer Res. 70(9), 3677-3686 (2010)