Survey of Storage Systems for High-Performance Computing

Authors

  • Jakob Lüttgau Deutsches Klimarechenzentrum GmbH
  • Michael Kuhn Universität Hamburg
  • Kira Duwe Deutsches Klimarechenzentrum GmbH
  • Yevhen Alforov Deutsches Klimarechenzentrum GmbH
  • Eugen Betke Deutsches Klimarechenzentrum GmbH
  • Julian Kunkel Deutsches Klimarechenzentrum GmbH
  • Thomas Ludwig Deutsches Klimarechenzentrum GmbH Universität Hamburg

DOI:

https://doi.org/10.14529/jsfi180103

Abstract

In current supercomputers, storage is typically provided by parallel distributed file systems for hot data and tape archives for cold data. These file systems are often compatible with local file systems due to their use of the POSIX interface and semantics, which eases development and debugging because applications can easily run both on workstations and supercomputers. There is a wide variety of file systems to choose from, each tuned for different use cases and implementing different optimizations. However, the overall application performance is often held back by I/O bottlenecks due to insufficient performance of file systems or I/O libraries for highly parallel workloads. Performance problems are dealt with using novel storage hardware technologies as well as alternative I/O semantics and interfaces. These approaches have to be integrated into the storage stack seamlessly to make them convenient to use. Upcoming storage systems abandon the traditional POSIX interface and semantics in favor of alternative concepts such as object and key-value storage; moreover, they heavily rely on technologies such as NVM and burst buffers to improve performance. Additional tiers of storage hardware will increase the importance of hierarchical storage management. Many of these changes will be disruptive and require application developers to rethink their approaches to data management and I/O. A thorough understanding of today's storage infrastructures, including their strengths and weaknesses, is crucially important for designing and implementing scalable storage systems suitable for demands of exascale computing.

References

Ang, J.A.: High performance computing co-design strategies. In: Proceedings of the 2015 International Symposium on Memory Systems. pp. 51–52. MEMSYS ’15, ACM, New York, NY, USA (2015), DOI: 10.1145/2818950.2818959

Bennett, J., Abbasi, H., Bremer, P., Grout, R.W., Gyulassy, A., Jin, T., Klasky, S., Kolla, H., Parashar, M., Pascucci, V., Pébay, P.P., Thompson, D.C., Yu, H., Zhang, F., Chen, J.: Combining in-situ and in-transit processing to enable extreme-scale scientific analysis. In: SC Conference on High Performance Computing Networking, Storage and Analysis, SC ’12, Salt Lake City, UT, USA, November 11 - 15, 2012 (2012), DOI: 10.1109/SC.2012.31

Bornholt, J., Lopez, R., Carmean, D.M., Ceze, L., Seelig, G., Strauss, K.: A DNA-Based Archival Storage System. SIGPLAN Notices 51(4), 637–649 (2016), DOI: 10.1145/2954679.2872397

Boukhobza, J., Rubini, S., Chen, R., Shao, Z.: Emerging nvm: A survey on architectural integration and research challenges. ACM Transactions on Design Automation of Electronic Systems (TODAES) 23(2), 14:1–14:32 (2017), DOI: 10.1145/3131848

BoyukaII, D.A., Lakshminarasimhan, S., Zou, X., Gong, Z., Jenkins, J., Schendel, E.R., Podhorszki, N., Liu, Q., Klasky, S., Samatova, N.F.: Transparent in situ data transformations in ADIOS. In: 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2014, Chicago, IL, USA, May 26-29, 2014. pp. 256–266 (2014), DOI: 10.1109/CCGrid.2014.73

Breitenfeld, M.S., Fortner, N., Henderson, J., Soumagne, J., Chaarawi, M., Lombardi, J., Koziol, Q.: DAOS for extreme-scale systems in scientific applications. CoRR abs/1712.00423 (2017), http://arxiv.org/abs/1712.00423, accessed: 2018-03-01

Brinkmann, A., Mohror, K., Yu, W.: Challenges and opportunities of user-level file systems for HPC (dagstuhl seminar 17202). Dagstuhl Reports 7(5), 97–139 (2017), DOI: 10.4230/DagRep.7.5.97

CDI Developers: Climate Data Interface. https://code.mpimet.mpg.de/projects/cdi (2018), accessed: 2018-02-01

Chen, J., Wei, Q., Chen, C., Wu, L.: FSMAC: A file system metadata accelerator with non-volatile memory. In: IEEE 29th Symposium on Mass Storage Systems and Technologies, MSST 2013, May 6-10, 2013, Long Beach, CA, USA. pp. 1–11 (2013), DOI: 10.1109/MSST.2013.6558440

Corbett, P., Feitelson, D., Fineberg, S., Hsu, Y., Nitzberg, B., Prost, J.P., Snir, M., Traversat, B., Wong, P.: Overview of the MPI-IO Parallel I/O Interface. In: IPPS ’95 Workshop on Input/Output in Parallel and Distributed Systems. pp. 1–15 (1995), http://lovelace.nas.nasa.gov/MPI-IO/iopads95-paper.ps, accessed: 2018-03-01

Cray: CRAY XC40 DataWarp Applications I/O Accelerator. http://www.cray.com/sites/default/files/resources/CrayXC40-DataWarp.pdf, accessed: 2018-03-01

DDN: Worlds’s most advanced application aware I/O acceleration solutions. http://www.ddn.com/products/infinite-memory-engine-ime14k, accessed: 2018-03-01

Dennis, J.M., Edwards, J., Loy, R.M., Jacob, R.L., Mirin, A.A., Craig, A.P., Vertenstein, M.: An application-level parallel I/O library for earth system models. The International Journal of High Performance Computing Applications (IJHPCA) 26(1), 43–53 (2012), DOI: 10.1177/1094342011428143

Depardon, B., Le Mahec, G., Séguin, C.: Analysis of Six Distributed File Systems. Research report (2013), https://hal.inria.fr/hal-00789086, accessed: 2018-02-01

Deuzeman, A., Reker, S., Urbach, C.: Lemon: An MPI parallel I/O library for data encapsulation using LIME. Computer Physics Communications 183(6), 1321–1335 (2012), DOI: 10.1016/j.cpc.2012.01.016

DOE, NISA: Exascale Computing Project (ECP). https://www.exascaleproject.org/ (2017), accessed: 2018-03-01

Dongarra, J.J., Tomov, S., Luszczek, P., Kurzak, J., Gates, M., Yamazaki, I., Anzt, H., Haidar, A., Abdelfattah, A.: With extreme computing, the rules have changed. Computing in Science and Engineering 19(3), 52–62 (2017), DOI: 10.1109/MCSE.2017.48

Dulloor, S., Roy, A., Zhao, Z., Sundaram, N., Satish, N., Sankaran, R., Jackson, J., Schwan, K.: Data tiering in heterogeneous memory systems. In: Proceedings of the Eleventh European Conference on Computer Systems, EuroSys 2016, London, United Kingdom, April 18-21, 2016. pp. 15:1–15:16 (2016), DOI: 10.1145/2901318.2901344

Duran-Limon, H.A., Flores-Contreras, J., Parlavantzas, N., Zhao, M., Meulenert-Peña, A.: Efficient execution of the WRF model and other HPC applications in the cloud. Earth Science Informatics 9(3), 365–382 (2016), DOI: 10.1007/s12145-016-0253-7

ESiWACE: Centre of Excellence in Simulation of Weather and Climate in Europe. https: //www.esiwace.eu/, accessed: 2018-03-01

Fraunhofer ITWM, ThinkParQ: BeeGFS - The Leading Parallel Cluster File System. https://www.beegfs.io (2018), accessed: 2018-02-01

Frings, W., Wolf, F., Petkov, V.: Scalable massively parallel I/O to task-local files. In: Proceedings of the ACM/IEEE Conference on High Performance Computing, SC 2009, November 14-20, 2009, Portland, Oregon, USA (2009), DOI: 10.1145/1654059.1654077

Geist, A., Reed, D.A.: A survey of high-performance computing scaling challenges. The International Journal of High Performance Computing Applications (IJHPCA) 31(1), 104–113 (2017), DOI: 10.1177/1094342015597083

Gensel, J., Josselin, D., Vandenbroucke, D. (eds.): Bridging the Geographic Information Sciences - International AGILE’2012 Conference, Avignon, France, April 24-27, 2012. Lecture Notes in Geoinformation and Cartography, Springer (2012), DOI: 10.1007/978-3-642-29063-3

Grawinkel, M., Nagel, L., Mäsker, M., Padua, F., Brinkmann, A., Sorth, L.: Analysis of the ecmwf storage landscape. In: Proceedings of the 13th USENIX Conference on File and Storage Technologies. pp. 15–27. FAST ’15, USENIX Association, Berkeley, CA, USA (2015), http://dl.acm.org/citation.cfm?id=2750482.2750484, accessed: 2018-03-01

Guest, M.: Prace: The Scientific Case for HPC in Europe. Insight publishers, Bristol (2012)

Gupta, A., Kalé, L.V., Gioachin, F., March, V., Suen, C.H., Lee, B., Faraboschi, P., Kaufmann, R., Milojicic, D.S.: The who, what, why, and how of high performance computing in the cloud. In: IEEE 5th International Conference on Cloud Computing Technology and Science, CloudCom 2013, Bristol, United Kingdom, December 2-5, 2013. vol. 1, pp. 306–314 (2013), DOI: 10.1109/CloudCom.2013.47

Gupta, A., Milojicic, D.: Evaluation of hpc applications on cloud. In: Proceedings of the 2011 Sixth Open Cirrus Summit. pp. 22–26. OCS ’11, IEEE Computer Society, Washington, DC, USA (2011), DOI: 10.1109/OCS.2011.10

HDF Group: RFC: Virtual Object Layer (2014)

HDF5: Hierarchical data model. https://www.hdfgroup.org/hdf5/, accessed: 2018-03-01

He, W., Du, D.H.C.: Smart: An approach to shingled magnetic recording translation. In: 15th USENIX Conference on File and Storage Technologies, FAST 2017, Santa Clara, CA, USA, February 27 - March 2, 2017. pp. 121–134 (2017), https://www.usenix.org/conference/fast17/technical-sessions/presentation/he, accessed: 2018-03-01

HGST: Ultrastar-Hs14-DS. https://www.hgst.com/sites/default/files/resources/Ultrastar-Hs14-DS.pdf, accessed: 2018-03-01

HGST: Ultrastar-SN200. https://www.hgst.com/sites/default/files/resources/Ultrastar-SN200-Series-datasheet.pdf, accessed: 2018-03-01

High Performance Storage System: Publicly disclosed HPSS deployments. http://www.hpss-collaboration.org/customersT.shtml (2018), accessed: 2018-02-01

Hubovsky, R., Kunz, F.: Dealing with Massive Data: from Parallel I/O to Grid I/O. Master’s thesis, University of Vienna, Department of Data Engineering (2004)

Hughes, J., Fisher, D., Dehart, K., Wilbanks, B., Alt, J.: HPSS RAIT Architecture. White paper of the HPSS collaboration (2009), http://www.hpss-collaboration.org/documents/HPSS_RAIT_Architecture.pdf, accessed: 2018-03-01

IBM: Flash Storage. https://www.ibm.com/storage/flash, accessed: 2018-03-01

IBM: General Parallel File System. https://www.ibm.com/support/knowledgecenter/en/SSFKCN/gpfs_welcome.html (2016), accessed: 2018-02-01

IBM: Ibm spectrum scale: Overview. http://www.ibm.com/systems/storage/spectrum/scale/ (2016), accessed: 2018-03-01

IEEE, T., Group, T.O.: Standard for Information Technology – Portable Operating System Interface (POSIX) Base Specifications, Issue 7. IEEE Std 1003.1, 2013 Edition (incorporates IEEE Std 1003.1-2008, and IEEE Std 1003.1-2008/Cor 1-2013) pp. 1–3906 (2013), DOI: 10.1109/IEEESTD.2013.6506091

Intel: Intel® 3D NAND Technology Transforms the Economics of Storage. https://www.intel.com/content/www/us/en/solid-state-drives/3d-nand-technology-animation.html, accessed: 2018-03-01

Intel: Intel® QuickAssist Technology (Intel® QAT) Improves Data Center... https://www.intel.com/content/www/us/en/architecture-and-technology/intel-quick-assist-technology-overview.html, accessed: 2018-03-01

Intel: Optane SSD DC P4800X. https://www.intel.com/content/dam/www/public/us/en/documents/product-briefs/optane-ssd-dc-p4800x-brief.pdf, accessed: 2018-03-01

Intel, The HDF Group, EMC, Cray: Fast Forward Storage and I/O - Final Report. https://wiki.hpdd.intel.com/display/PUB/Fast+Forward+Storage+and+IO+Program+Documents?preview=/12127153/22872065/M8.5%20FF-Storage%20Final%20Report%20v3.pdf (2014), accessed: 2018-03-01

ITRS: International technology roadmap for semiconductors - 2.0. Tech. rep. (2015)

Kimpe, D., Ross, R.: Storage models: Past, present, and future. High Performance Parallel I/O pp. 335–345 (2014)

Kingston: KSM24LQ4/64HAI. https://www.kingston.com/dataSheets/KSM24LQ4_64HAI.pdf, accessed: 2018-03-01

Klein, A.: Backblaze Hard Drive Stats for 2017. https://www.backblaze.com/blog/hard-drive-stats-for-2017/ (2018), accessed: 2018-03-01

Kove Corporation: About xpress disk (xpd) (2015), http://www.hamburgnet.de/products/kove/Kove-XPD-L3-4-datasheet.pdf, accessed: 2018-03-01

Kuhn, M., Kunkel, J., Ludwig, T.: Data Compression for Climate Data. Supercomputing Frontiers and Innovations 3(1), 75–94 (2016), DOI: 10.14529/jsfi160105

Kunkel, J.M., Betke, E.: An MPI-IO in-memory driver for non-volatile pooled memory of the kove XPD. In: High Performance Computing - ISC High Performance 2017 International Workshops, DRBSD, ExaComm, HCPM, HPC-IODC, IWOPH, IXPUG, Pˆ3MA, VHPC, Visualization at Scale, WOPSSS, Frankfurt, Germany, June 18-22, 2017, Revised Selected Papers. pp. 679–690 (2017), DOI: 10.1007/978-3-319-67630-2_48

Labs, C.: Open-Channel Solid State Drives. https://openchannelssd.readthedocs.io/en/latest, accessed: 2018-02-01

Latham, R., Ross, R.B., Thakur, R.: Implementing MPI-IO atomic mode and shared file pointers using MPI one-sided communication. The International Journal of High Performance Computing Applications (IJHPCA) 21(2), 132–143 (2007), DOI: 10.1177/1094342007077859

Lawson, M., Ulmer, C., Mukherjee, S., Templet, G., Lofstead, J.F., Levy, S., Widener, P.M., Kordenbrock, T.: Empress: extensible metadata provider for extreme-scale scientific simulations. In: Proceedings of the 2nd Joint International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems, PDSW-DISCS@SC 2017, Denver, CO, USA, November 13, 2017. pp. 19–24 (2017), DOI: 10.1145/3149393.3149403

Ledyayev, R., Richter, H.: High performance computing in a cloud using Open-Stack. Cloud Computing pp. 108–113 (2014), https://pdfs.semanticscholar.org/2a5d/9c7afcf6b70ad83bca0c4262b66ef654415a.pdf, accessed: 2018-03-01

Liu, Q., Logan, J., Tian, Y., Abbasi, H., Podhorszki, N., Choi, J.Y., Klasky, S., Tchoua, R., Lofstead, J.F., Oldfield, R., Parashar, M., Samatova, N.F., Schwan, K., Shoshani, A., Wolf, M., Wu, K., Yu, W.: Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. Concurrency and Computation: Practice and Experience 26(7), 1453–1473 (2014), DOI: 10.1002/cpe.3125

Lockwood, G.K.: Reviewing the state of the art of burst buffers. https://glennklockwood.blogspot.de/2017/03/reviewing-state-of-art-of-burst-buffers.html (2017), accessed: 2018-02-01

Lockwood, G.: What’s So Bad About POSIX I/O https://www.nextplatform.com/2017/09/11/whats-bad-posix-io/ (2017), accessed: 2018-02-01

Lockwood, G.K., Hazen, D., Koziol, Q., Canon, R., Antypas, K., Balewski, J., Balthaser, N., Bhimji, W., Botts, J., Broughton, J., et al.: Storage 2020: A vision for the future of hpc storage (2017), https://escholarship.org/uc/item/744479dp, accessed: 2018-03-01

Lofstead, J.F., Jimenez, I., Maltzahn, C., Koziol, Q., Bent, J., Barton, E.: DAOS and friends: a proposal for an exascale storage system. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2016, Salt Lake City, UT, USA, November 13-18, 2016. pp. 585–596 (2016), DOI: 10.1109/SC.2016.49

Lofstead, J.F., Klasky, S., Schwan, K., Podhorszki, N., Jin, C.: Flexible IO and integration for scientific codes through the adaptable IO system (ADIOS). In: 6th International Workshop on Challenges of Large Applications in Distributed Environments, CLADE@HPDC 2008, Boston, MA, USA, June 23, 2008. pp. 15–24 (2008), DOI: 10.1145/1383529.1383533

LTO: Linear Tape Open (LTO) Website. https://www.lto.org/technology/what-is-lto-technology/, accessed: 2018-03-01

Matri, P., Alforov, Y., Brandon, A., Kuhn, M., Carns, P.H., Ludwig, T.: Could blobs fuel storage-based convergence between HPC and big data? In: 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017, Honolulu, HI, USA, September 5-8, 2017. pp. 81–86 (2017), DOI: 10.1109/CLUSTER.2017.63

Matri, P., Costan, A., Antoniu, G., Montes, J., Pérez, M.S.: Týr: blob storage meets built-in transactions. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2016, Salt Lake City, UT, USA, November 13-18, 2016. pp. 573–584 (2016), DOI: 10.1109/SC.2016.48

McKee, S.A.: Reflections on the memory wall. In: Proceedings of the First Conference on Computing Frontiers, 2004, Ischia, Italy, April 14-16, 2004. p. 162 (2004), DOI: 10.1145/977091.977115

Message Passing Interface Forum: MPI: A Message-Passing Interface Standard. Version 3.0. http://www.mpi-forum.org/docs/mpi-3.0/mpi30-report.pdf (2012), accessed: 2014-11-01

Micheloni, R., Crippa, L., Zambelli, C., Olivo, P.: Architectural and integration options for 3d NAND flash memories. Computers 6(3), 27 (2017), DOI: 10.3390/computers6030027

NetCDF: Network common data format. https://www.unidata.ucar.edu/software/netcdf/, accessed: 2018-03-01

NEXTGenIO: Next Generation I/O for the exascale. http://www.nextgenio.eu/, accessed: 2018-03-01

Oe, K., Nanri, T., Okamura, K.: Feasibility study for building hybrid storage system consisting of non-volatile DIMM and SSD. In: Fourth International Symposium on Computing and Networking, CANDAR 2016, Hiroshima, Japan, November 22-25, 2016. pp. 454–457 (2016), DOI: 10.1109/CANDAR.2016.0085

Oh, M., Eom, J., Yoon, J., Yun, J.Y., Kim, S., Yeom, H.Y.: Performance optimization for all flash scale-out storage. In: 2016 IEEE International Conference on Cluster Computing, CLUSTER 2016, Taipei, Taiwan, September 12-16, 2016. pp. 316–325 (2016), DOI: 10.1109/CLUSTER.2016.11

ORNL: Adios. https://www.olcf.ornl.gov/center-projects/adios/ (2017), accessed: 2018-03-01

Peng, I.B., Gioiosa, R., Kestor, G., Laure, E., Markidis, S.: Exploring the Performance Benefit of Hybrid Memory System on HPC Environments. arXiv:1704.08273 [cs] pp. 683–692 (2017), DOI: 10.1109/IPDPSW.2017.115

Perarnau, S., Zounmevo, J.A., Gerofi, B., Iskra, K., Beckman, P.H.: Exploring data migration for future deep-memory many-core systems. In: 2016 IEEE International Conference on Cluster Computing, CLUSTER 2016, Taipei, Taiwan, September 12-16, 2016. pp. 289–297 (2016), DOI: 10.1109/CLUSTER.2016.42

Petersen, T.K., Bent, J.: Hybrid flash arrays for HPC storage systems: An alternative to burst buffers. In: 2017 IEEE High Performance Extreme Computing Conference, HPEC 2017, Waltham, MA, USA, September 12-14, 2017. pp. 1–7 (2017), DOI: 10.1109/HPEC.2017.8091092

Rew, R., Davis, G.: Netcdf: an interface for scientific data access. IEEE Computer Graphics and Applications 10(4), 76–82 (1990), DOI: 10.1109/38.56302

Ross, R.B., Latham, R., Gropp, W., Thakur, R., Toonen, B.R.: Implementing MPI-IO atomic mode without file system support. In: 5th International Symposium on Cluster Computing and the Grid (CCGrid 2005), 9-12 May, 2005, Cardiff, UK. pp. 1135–1142 (2005), DOI: 10.1109/CCGRID.2005.1558687

SAGE: SAGE | Redefining Data Storage for Extreme Data and Exascale Computing. http://www.sagestorage.eu/, accessed: 2018-03-01

Sai Anuhya, D., Agrawal, S., Publication, I.: 3-d holographic data storage 4, 232–239 (2013)

Sato, K., Mohror, K., Moody, A., Gamblin, T., de Supinski, B.R., Maruyama, N., Matsuoka, S.: A user-level infiniband-based file system and checkpoint strategy for burst buffers. In: 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid

, Chicago, IL, USA, May 26-29, 2014. pp. 21–30 (2014), DOI: 10.1109/CCGrid.2014.24

Seagate: Nytro 5910. https://www.seagate.com/files/www-content/datasheets/pdfs/nytro-5910-nvme-ssdDS1953-3-1801DE-de_DE.pdf, accessed: 2018-03-01

Seagate: Nytro3000. https://www.seagate.com/files/www-content/datasheets/pdfs/nytro-3000-sas-ssdDS1950-2-1711DE-de_DE.pdf, accessed: 2018-03-01

Sebastian, A.: IBM and Sony cram up to 330 terabytes into tiny tape cartridge. https://arstechnica.com/information-technology/2017/08/ibm-and-sony-cram-up-to-330tb-into-tiny-tape-cartridge/ (2017), accessed: 2018-03-01

Sehrish, S.: Improving Performance and Programmer Productivity for I/O-Intensive High Performance Computing Applications. PhD thesis, School of Electrical Engineering and Computer Science in the College of Engineering and Computer Science at the University of Central Florida (2010), http://purl.fcla.edu/fcla/etd/CFE0003236, accessed: 2018-03-01

Shehabi, A., Smith, S., Sartor, D., Brown, R., Herrlin, M., Koomey, J., Masanet, E., Horner, N., Azevedo, I., Lintner, W.: United States data center energy usage report. https://pubarchive.lbl.gov/islandora/object/ir%3A1005775/ (2016), accessed: 2018-03-01

Shi, W., Ju, D., Wang, D.: Saga: A cost efficient file system based on cloud storage service. In: Economics of Grids, Clouds, Systems, and Services - 8th International Workshop, GECON 2011, Paphos, Cyprus, December 5, 2011, Revised Selected Papers. pp. 173–184 (2011), DOI: 10.1007/978-3-642-28675-9_13

Smart, S.D., Quintino, T., Raoult, B.: A Scalable Object Store for Meteorological and Climate Data. In: Proceedings of the Platform for Advanced Scientific Computing Conference. pp. 13:1–13:8. PASC ’17, ACM, New York, NY, USA (2017), DOI: 10.1145/3093172.3093238

Spectralogic: LTO Roadmap. https://www.spectralogic.com/features/lto-7/ (2017), accessed: 2018-03-01

Sterling, T., Lusk, E., Gropp, W.: Beowulf Cluster Computing with Linux. MIT Press, Cambridge, MA, USA, 2 edn. (2003)

Takatsu, F., Hiraga, K., Tatebe, O.: Design of object storage using opennvm for high performance distributed file system. Journal of Information Processing 24(5), 824–833 (2016), DOI: 10.2197/ipsjjip.24.824

Takatsu, F., Hiraga, K., Tatebe, O.: PPFS: A scale-out distributed file system for postpetascale systems. In: 18th IEEE International Conference on High Performance Computing and Communications; 14th IEEE International Conference on Smart City; 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016, Sydney, Australia, December 12-14, 2016. pp. 1477–1484 (2016), DOI: 10.1109/HPCC-SmartCity-DSS.2016.0210

Tang, H., Byna, S., Dong, B., Liu, J., Koziol, Q.: Someta: Scalable object-centric metadata management for high performance computing. In: 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017, Honolulu, HI, USA, September 5-8, 2017. pp. 359–369 (2017), DOI: 10.1109/CLUSTER.2017.53

Top500: Top500 Supercomputer Sites. http://www.top500.org/ (2017), accessed: 2018-03-01

Toshiba: eSSD-PX05SHB. https://toshiba.semicon-storage.com/content/dam/toshiba-ss/asia-pacific/docs/product/storage/product-manual/eSSD-PX05SHB-product-overview.pdf, accessed: 2018-03-01

Vilayannur, M., Lang, S., Ross, R., Klundt, R., Ward, L.: Extending the POSIX I/O Interface: A Parallel File System Perspective. Tech. Rep. ANL/MCS-TM-302 (2008), http://www.mcs.anl.gov/uploads/cels/papers/TM-302-FINAL.pdf, accessed: 2018-03-01

Vilayannur, M., Ross, R.B., Carns, P.H., Thakur, R., Sivasubramaniam, A., Kandemir, M.T.: On the performance of the POSIX I/O interface to PVFS. In: 12th Euromicro Workshop on Parallel, Distributed and Network-Based Processing (PDP 2004), 11-13 February 2004, A Coruna, Spain. pp. 332–339 (2004), DOI: 10.1109/EMPDP.2004.1271463

Wang, T., Oral, S., Wang, Y., Settlemyer, B.W., Atchley, S., Yu, W.: Burstmem: A highperformance burst buffer system for scientific applications. In: 2014 IEEE International Conference on Big Data, Big Data 2014, Washington, DC, USA, October 27-30, 2014. pp. 71–79 (2014), DOI: 10.1109/BigData.2014.7004215

Watson, R.W.: High performance storage system scalability: Architecture, implementation and experience. In: 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST 2005), Information Retrieval from Very Large Storage Systems, CD-ROM, 11-14 April 2005, Monterey, CA, USA. pp. 145–159 (2005), DOI: 10.1109/MSST.2005.17

Wei, Q., Chen, J., Chen, C.: Accelerating file system metadata access with byteaddressable nonvolatile memory. ACM Transactions on Storage (TOS) 11(3), 12:1–12:28 (2015), DOI: 10.1145/2766453

Weil, S.A., Brandt, S.A., Miller, E.L., Long, D.D.E., Maltzahn, C.: Ceph: A scalable, high-performance distributed file system. In: 7th Symposium on Operating Systems Design and Implementation (OSDI ’06), November 6-8, Seattle, WA, USA. pp. 307–320 (2006),

http://www.usenix.org/events/osdi06/tech/weil.html, accessed: 2018-03-01

Weil, S.A., Leung, A.W., Brandt, S.A., Maltzahn, C.: RADOS: a scalable, reliable storage service for petabyte-scale storage clusters. In: Proceedings of the 2nd International Petascale Data Storage Workshop (PDSW ’07), November 11, 2007, Reno, Nevada, USA. pp. 35–44 (2007), DOI: 10.1145/1374596.1374606

Xu, J., Swanson, S.: NOVA: A log-structured file system for hybrid volatile/non-volatile main memories. In: 14th USENIX Conference on File and Storage Technologies, FAST 2016, Santa Clara, CA, USA, February 22-25, 2016. pp. 323–338 (2016), https://www.usenix.org/conference/fast16/technical-sessions/presentation/xu, accessed: 2018-03-01

Xuan, P., Luo, F., Ge, R., Srimani, P.K.: Dynims: A dynamic memory controller for inmemory storage on HPC systems. CoRR abs/1609.09294 (2016), http://arxiv.org/abs/1609.09294, accessed: 2018-03-01

Yang, J., Tan, C.P.H., Ong, E.H.: Thermal analysis of helium-filled enterprise disk drive. Microsystem Technologies 16(10), 1699–1704 (2010), DOI: 10.1007/s00542-010-1121-x

Zhang, Z., Barbary, K., Nothaft, F.A., Sparks, E.R., Zahn, O., Franklin, M.J., Patterson, D.A., Perlmutter, S.: Scientific computing meets big data technology: An astronomy use case. In: 2015 IEEE International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, October 29 - November 1, 2015. pp. 918–927 (2015), DOI: 10.1109/Big-Data.2015.7363840

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2018-04-23

How to Cite

Lüttgau, J., Kuhn, M., Duwe, K., Alforov, Y., Betke, E., Kunkel, J., & Ludwig, T. (2018). Survey of Storage Systems for High-Performance Computing. Supercomputing Frontiers and Innovations, 5(1), 31–58. https://doi.org/10.14529/jsfi180103