Abstract
This work studies the storage subsystem for scientific big data applications to be running on the cloud. Although cloud computing has become one of the most popular paradigms for executing data-intensive applications, the storage subsystem has not been optimized for scientific applications. In particular, many scientific applications were originally developed assuming a tightly coupled cluster of compute nodes with network-attached storage allowing massively parallel I/O accesses—the high-performance computing (HPC) systems. These applications, in turn, struggle in leveraging cloud platforms whose design goal is fundamentally different than that of HPC systems. We believe that when executing scientific applications in the cloud, a node-local distributed storage architecture is a key approach to overcome the challenges from the storage subsystem. We analyze and evaluate four representative file systems (S3FS, HDFS, Ceph, and FusionFS) on multiple platforms (Kodiak cluster, Amazon EC2) with a variety of benchmarks to explore how well these storage systems can handle metadata-intensive, write-intensive, and read-intensive workloads. Moreover, we elaborate the design and implementation of FusionFS that employs a scalable approach to managing both metadata and data in addition to its unique features on cooperative caching, dynamic compression, GPU-accelerated data redundancy, lightweight provenance, and parallel serialization.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
because it gets replicated on multiple nodes, physically.
References
Shvachko, K., Kuang, H., Radia, S., Chansler, R.: The hadoop distributed file system. In: Proceedings of IEEE Symposium on Mass Storage Systems and Technologies (2010)
Carns, P., Lang, S., Ross, R., Vilayannur, M., Kunkel, J., Ludwig, T.: Small-file access in parallel file systems. In: Proceedings of IEEE International Symposium on Parallel and Distributed Processing (2009)
Ghemawat, S., Gobioff, H., Leung, S.T.: The Google file system. In: ACM Symposium on Operating Systems Principles (2003)
S3FS: https://code.google.com/p/s3fs/. Accessed 6 March 2015
FUSE: http://fuse.sourceforge.net. Accessed 5 Sept 2014
Weil, S.A., Brandt, S.A., Miller, E.L., Long, D.D.E., Maltzahn, C.: Ceph: a scalable, high-performance distributed file system. In: Proceedings of the 7th Symposium on Operating Systems Design and Implementation (2006)
Zhao, D., Zhang, Z., Zhou, X., Li, T., Wang, K., Kimpe, D., Carns, P., Ross, R., Raicu, I.: FusionFS: Toward supporting data-intensive scientific applications on extreme-scale distributed systems. In: Proceedings of IEEE International Conference on Big Data, pp. 61–70 (2014)
Zhao, D., Liu, N., Kimpe, D., Ross, R., Sun, X.H., Raicu, I.: Towards exploring data-intensive scientific applications at extreme scales through systems and simulations. IEEE Trans. Parallel Distrib. Syst. 1–14 (2015). doi:10.1109/TPDS.2015.2456896
Weil, S.A., Brandt, S.A., Miller, E.L., Maltzahn, C.: Crush: controlled, scalable, decentralized placement of replicated data. In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (2006)
Zhao, D., Raicu, I.: Distributed file systems for exascale computing. In: International Conference for High Performance Computing, Networking, Storage and Analysis (SC ’12), doctoral showcase (2012)
Zhao, D., Burlingame, K., Debains, C., Alvarez-Tabio, P., Raicu, I.: Towards high-performance and cost-effective distributed storage systems with information dispersal algorithms. In: IEEE International Conference on Cluster Computing (2013)
Zhao, D., Shou, C., Malik, T., Raicu, I.: Distributed data provenance for large-scale data-intensive computing. In: IEEE International Conference on Cluster Computing (2013)
Zhao, D., Qiao, K., Raicu, I.: Hycache+: towards scalable high-performance caching middleware for parallel file systems. In: Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 267–276 (2014)
Zhao, D., Raicu, I.: HyCache: a user-level caching middleware for distributed file systems. In: Proceedings of IEEE 27th International Symposium on Parallel and Distributed Processing Workshops and PhD Forum (2013)
Zhao, D., Yin, J., Qiao, K., Raicu, I.: Virtual chunks: on supporting random accesses to scientific data in compressible storage systems. In: Proceedings of IEEE International Conference on Big Data, pp. 231–240 (2014)
Zhao, D., Yin, J., Raicu, I.: Improving the i/o throughput for data-intensive scientific applications with efficient compression mechanisms. In: International Conference for High Performance Computing, Networking, Storage and Analysis (SC ’13), poster session (2013)
Zhao, D., Qiao, K., Zhou, Z., Li, T., Zhou, X., Wang, K., Raicu, I.: Exploiting multi-cores for efficient interchange of large messages in distributed systems. Concurrency Comput.: Pract. Experience 2015 (accepted)
Kodiak: https://www.nmc-probe.org/wiki/Machines:Kodiak. Accessed 5 Sept 2014
Amazon EC2: http://aws.amazon.com/ec2. Accessed 6 March 2015
Welch, B., Noer, G.: Optimizing a hybrid SSD/HDD HPC storage system based on file size distributions. In: IEEE 29th Symposium on Mass Storage Systems and Technologies (2013)
Nagle, D., Serenyi, D., Matthews, A.: The Panasas activescale storage cluster: delivering scalable high bandwidth storage. In: Proceedings of ACM/IEEE Conference on Supercomputing (2004)
Zhao, D., Zhang, D., Wang, K., Raicu, I.: Exploring reliability of exascale systems through simulations. In: Proceedings of the 21st ACM/SCS High Performance Computing Symposium (HPC) (2013)
Schmuck, F., Haskin, R.: GPFS: a shared-disk file system for large computing clusters. In: Proceedings of the 1st USENIX Conference on File and Storage Technologies (2002)
Schwan, P.: Lustre: building a file system for 1,000-node clusters. In: Proceedings of the Linux Symposium (2003)
Wu, H., Ren, S., Garzoglio, G., Timm, S., Bernabeu, G., Chadwick, K., Noh, S.-Y.: A reference model for virtual machine launching overhead. IEEE Trans. Cloud Comput. (pp. 99), 1–1 (2014)
Wu, H., Ren, S., Garzoglio, G., Timm, S., Bernabeu, G., Noh, S.-Y.: Modeling the virtual machine launching overhead under fermicloud. In: 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), May 2014
Li, T., Zhou, X., Brandstatter, K., Zhao, D., Wang, K., Rajendran, A., Zhang, Z., Raicu, I.: ZHT: A light-weight reliable persistent dynamic scalable zero-hop distributed hash table. In: Proceedings of IEEE International Symposium on Parallel and Distributed Processing (2013)
Li, T., Ma, C., Li, J., Zhou, X., Wang, K., Zhao, D., Raicu, I.: Graph/z: a key-value store based scalable graph processing system. In: IEEE International Conference on Cluster Computing (2015)
Zhao, Y., Hategan, M., Clifford, B., Foster, I., von Laszewski, G., Nefedova, V., Raicu, I., Stef-Praun, T., Wilde, M.: Swift: Fast, reliable, loosely coupled parallel computation. In: IEEE Congress on Services (2007)
Raicu, I., Foster, I.T., Zhao, Y., Little, P., Moretti, C.M., Chaudhary, A., Thain, D.: The quest for scalable support of data-intensive workloads in distributed systems. In: Proceedings of ACM International Symposium on High Performance Distributed Computing (2009)
Shou, C., Zhao, D., Malik, T., Raicu, I.: Towards a provenance-aware distributed filesystem. In: 5th Workshop on the Theory and Practice of Provenance (TaPP) (2013)
Protocol Buffers: http://code.google.com/p/protobuf/. Accessed 5 Sept 2014
Carns, P.H., Ligon, W.B., Ross, R.B., Thakur, R.: PVFS: a parallel file system for linux clusters. In: Proceedings of the 4th Annual Linux Showcase and Conference (2000)
Li, T., Zhou, X., Wang, K., Zhao, D., Sadooghi, I., Zhang, Z., Raicu, I.: A convergence of key-value storage systems from clouds to supercomputer. Concurrency Comput.: Pract. Experience (2016)
Zhao, D., Yang, X., Sadooghi, I., Garzoglio, G., Timm, S., Raicu, I.: High-performance storage support for scientific applications on the cloud. In: Proceedings of the 6th Workshop on Scientific Cloud Computing (ScienceCloud) (2015)
Li, T., Keahey, K., Wang, K., Zhao, D., Raicu, I.: A dynamically scalable cloud data infrastructure for sensor networks. In: Proceedings of the 6th Workshop on Scientific Cloud Computing (ScienceCloud) (2015)
Raicu, I., Zhao, Y., Foster, I.T., Szalay, A.: Accelerating large-scale data exploration through data diffusion. In: Proceedings of the 2008 International Workshop on Data-aware Distributed Computing (2008)
Li, S., Huang, H.H.: Black-box performance modeling for solid-state drives. In: 2010 IEEE International Symposium on Modeling, Analysis Simulation of Computer and Telecommunication Systems (MASCOTS) (2010)
Rizvi, S., Chung, T.-S.: Flash SSD vs HDD: High performance oriented modern embedded and multimedia storage systems. In: 2nd International Conference on Computer Engineering and Technology (ICCET) (2010)
Chen, F., Koufaty, D.A., Zhang, X.: Hystor: making the best use of solid state drives in high performance storage systems. In: Proceedings of the International Conference on Supercomputing (2011)
Guerra, J., Pucha, H., Glider, J., Belluomini, W., Rangaswami, R.: Cost effective storage using extent based dynamic tiering. In: Proceedings of the 9th USENIX Conference on File and Stroage Technologies (2011)
Zhang, X., Davis, K., Jiang, S.: iTransformer: using SSD to improve disk scheduling for high-performance I/O. In: Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium (2012)
Zhang, X., Ke, L., Davis, K., Jiang, S.: iBridge: improving unaligned parallel file access with solid-state drives. In: Proceedings of the 2013 IEEE 27th International Parallel and Distributed Processing Symposium (2013)
Mao, B., Jiang, H., Feng, D., Wu, S., Chen, J., Zeng, L., Tian, L.: HPDA: a hybrid parity-based disk array for enhanced performance and reliability. In: 2010 IEEE International Symposium on Parallel Distributed Processing (IPDPS) (2010)
Badam, A., Pai, V.S.: SSDAlloc: hybrid SSD/RAM memory management made easy. In: Proceedings of the 8th USENIX Conference on Networked systems design and implementation (2011)
Wang, C., Vazhkudai, S.S., Ma, X., Meng, F., Kim, Y., Engelmann, C.: Nvmalloc: exposing an aggregate ssd store as a memory partition in extreme-scale machines. In: Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium (2012)
Wu, X., Narasimha Reddy, A.L.: SCMFS: a file system for storage class memory. In: Proceedings of International Conference for High Performance Computing, Networking, Storage and Analysis (2011)
Joo, Y., Ryu, J., Park, S., Shin, K.G.: FAST: quick application launch on solid-state drives. In: Proceedings of the 9th USENIX Conference on File and Stroage Technologies (2011)
Yang, Q., Ren, J.: I-CASH: intelligently coupled array of SSD and HDD. In: Proceedings of the 2011 IEEE 17th International Symposium on High Performance Computer Architecture (2011)
Fares, R., Romoser, B., Zong, Z., Nijim, M., Qin, X.: Performance evaluation of traditional caching policies on a large system with petabytes of data. In: 2012 IEEE 7th International Conference on Networking, Architecture and Storage (NAS) (2012)
Podlipnig, S., Böszörmenyi, L.: A survey of web cache replacement strategies. ACM Comput. Surv. 35(4) (2003)
Shi, L., Liu, Z., Xu, L.: Bwcc: a fs-cache based cooperative caching system for network storage system. In: Proceedings of the 2012 IEEE International Conference on Cluster Computing (2012)
Wu, C., Xubin, H., Qiang, C., Changsheng, X., Shenggang, W.: Hint-k: an efficient multi-level cache using k-step hints. IEEE Trans. Parallel Distrib. Syst. 99 (2013)
Meister, D., Kaiser, J., Brinkmann, A.: Block locality caching for data deduplication. In: Proceedings of the 6th International Systems and Storage Conference (2013)
Xia, P., Feng, D., Jiang, H., Tian, L., Wang, F.: Farmer: a novel approach to file access correlation mining and evaluation reference model for optimizing peta-scale file system performance. In: Proceedings of the 17th International Symposium on High Performance Distributed Computing (2008)
Lin, J., Lu, Q., Ding, X., Zhang, Z., Zhang, X., Sadayappan, P.: Enabling software management for multicore caches with a lightweight hardware support. In: Proceedings of the 2009 ACM/IEEE Conference on Supercomputing (2009)
Zhan, D., Jiang, H., Seth, S.C.: Locality & utility co-optimization for practical capacity management of shared last level caches. In: Proceedings of the 26th ACM International Conference on Supercomputing (2012)
Gonzalez-Ferez, P., Piernas, J., Cortes, T.: The ram enhanced disk cache project (redcap). In: Proceedings of the 24th IEEE Conference on Mass Storage Systems and Technologies (2007)
Huang, S., Wei, Q., Chen, J., Chen, C., Feng, D.: Improving flash-based disk cache with lazy adaptive replacement. In: 2013 IEEE 29th Symposium on Mass Storage Systems and Technologies (MSST) (2013)
Zhu, Z., Zhang, X.: Access-mode predictions for low-power cache design. IEEE Micro 22(2) (2002)
Yue, J., Zhu, Y., Cai, Z., Lin, L.: Energy and thermal aware buffer cache replacement algorithm. In: Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST) (2010)
Manzanares, A., Ruan, X., Yin, S., Xie, J., Ding, Z., Tian, Y., Majors, J., Qin, X.: Energy efficient prefetching with buffer disks for cluster file systems. In: Proceedings of the 2010 39th International Conference on Parallel Processing (2010)
Li, Z., Wilson, C., Jiang, Z., Liu, Y., Zhao, B., Jin, C., Zhang, Z.L., Dai, Y.: Efficient batched synchronization in dropbox-like cloud storage services. In: Proceedings of the 14th International Middleware Conference (2013)
Xu, Y., Xing, C., Zhou, L.: A cache replacement algorithm in hierarchical storage of continuous media object. In: Advances in Web-Age Information Management: 5th International Conference (2004)
Li, R., Guo, R., Xu, Z., Feng, W.: A prefetching model based on access popularity for geospatial data in a cluster-based caching system. Int. J. Geogr. Inf. Sci. 26(10) (2012)
Qiao, K., Tao, F., Zhang, L., Li, Z.: A ga maintained by binary heap and transitive reduction for addressing psp. In: 2010 International Conference on Intelligent Computing and Integrated Systems (ICISS) (2010)
Tao, F., Qiao, K., Zhang, L., Li, Z., Nee, A.: GA-BHTR: an improved genetic algorithm for partner selection in virtual manufacturing. Int. J. Prod. Res. 50(8) (2012)
Calinescu, G., Qiao, K.: Asymmetric topology control: exact solutions and fast approximations. In: IEEE International Conference on Computer Communications (INFOCOM ’12) (2012)
Calinescu, G., Kapoor, S., Qiao, K., Shin, J.: Stochastic strategic routing reduces attack effects. In: Global Telecommunications Conference (GLOBECOM 2011), 2011. IEEE (2011)
Zhao, D,, Yang, L.: Incremental isometric embedding of high-dimensional data using connected neighborhood graphs. IEEE Trans. Pattern Anal. Mach. Intell. 31(1), 86–98 (2009)
Lohfert, R., Lu, J., Zhao, D.; Solving sql constraints by incremental translation to sat. In: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (2008)
Zhao, D., Yang, L.: Incremental construction of neighborhood graphs for nonlinear dimensionality reduction. In: Proceedings of 18th International Conference on Pattern Recognition, vol. 3, pp. 177–180 (2006)
Ferreira, K.B., Riesen, R., Arnold, D., Ibtesham, D., Brightwell, R.: The viability of using compression to decrease message log sizes. In: Proceedings of International Conference on Parallel Processing Workshops (2013)
Zerin Islam, T., Mohror, K., Bagchi, S., Moody, A., de Supinski, B.R., Eigenmann, R.: McrEngine: a scalable checkpointing system using data-aware aggregation and compression. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC) (2012)
Slim Bouguerra, M., Gainaru, A., Gomez, L.B., Cappello, F., Matsuoka, S., Maruyam, N.: Improving the computing efficiency of hpc systems using a combination of proactive and preventive checkpointing. In: IEEE International Symposium on Parallel Distributed Processing (2013)
Noeth, M., Marathe, J., Mueller, F., Schulz, M., de Supinski, B.: Scalable compression and replay of communication traces in massively parallel environments. In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (SC) (2006)
Laney, D., Langer, S., Weber, C., Lindstrom, P., Wegener, A.: Assessing the effects of data compression in simulations using physically motivated metrics. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (2013)
Lakshminarasimhan, S., Jenkins, J., Arkatkar, I., Gong, Z., Kolla, H., Ku, S.-H., Ethier, S., Chen, J., Chang, C.S., Klasky, S., Latham, R., Ross, R., Samatova, N.F.: ISABELA-QA: query-driven analytics with ISABELA-compressed extreme-scale scientific data. In: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC’11) (2011)
MPEG-1: http://en.wikipedia.org/wiki/MPEG-1. Accessed 5 Sept 2014
Bicer, T., Yin, J., Chiu, D., Agrawal, G., Schuchardt, K.: Integrating online compression to accelerate large-scale data analytics applications. In: Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing (IPDPS) (2013)
Schendel, E.R., Pendse, S.V., Jenkins, J., Boyuka, D.A., II, Gong, Z., Lakshminarasimhan, S., Liu, Q., Kolla, H., Chen, J., Klasky, S.,Ross, R., Samatova, N.F.: Isobar hybrid compression-i/o interleaving for large-scale parallel i/o optimization, In: Proceedings of International Symposium on High-Performance Parallel and Distributed Computing (2012)
Jenkins, J., Schendel, E.R., Lakshminarasimhan, S., Boyuka, D.S., II, Rogers, T., Ethier, S., Ross, R., Klasky, S., Samatova, N.F.: Byte-precision level of detail processing for variable precision analytics. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC) (2012)
Burrows, M., Jerian, C., Lampson, B., Mann, T.: On-line data compression in a log-structured file system. In: Proceedings of the Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) (1992)
Joshua, P.: MacDonald. File system support for delta compression. Technical report, University of California, Berkley (2000)
Olson, M.A., Bostic, K., Seltzer M.: db. In: Proceedings of the Annual Conference on USENIX Annual Technical Conference (1999)
Edel, N.K., Tuteja, D., Miller, E.L., Brandt S.A.: Mramfs: a compressing file system for non-volatile ram. In: Proceedings of the the IEEE Computer Society’s 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MASCOTS) (2004)
Muthitacharoen, A., Chen, B., Mazières, D.: A low-bandwidth network file system. In: Proceedings of the Eighteenth ACM Symposium on Operating Systems Principles (SOSP) (2001)
Park, K.S., Ihm, S., Bowman, M., Pai, V.S.: Supporting practical content-addressable caching with czip compression. In: 2007 USENIX Annual Technical Conference (2007)
Meister, D., Brinkmann, A., SĂĽĂź, T.: File recipe compression in data deduplication systems. In: Proceedings of the 11th USENIX Conference on File and Storage Technologies (FAST) (2013)
Lakshminarasimhan, S., Boyuka, D.A., Pendse, S.V., Zou, X., Jenkins, J., Vishwanath, V., Papka, M.E., Samatova, N.F.: Scalable in situ scientific data encoding for analytical query processing. In: Proceedings of the 22nd International Symposium on High-performance Parallel and Distributed Computing (HPDC) (2013)
Gong, Z., Lakshminarasimhan, S., Jenkins, J., Kolla, H., Ethier, S., Chen, J., Ross, R., Klasky, S., Samatova, N.F.: Multi-level layout optimization for efficient spatio-temporal queries on isabela-compressed data. In: Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium (IPDPS) (2012)
Shnaiderman, L., Shmueli, O.: A parallel twig join algorithm for XML processing using a GPGPU. In: International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures (2012)
Wang, H., Potluri, S., Bureddy, D., Rosales, C., Panda, D.K.: Gpu-aware mpi on rdma-enabled clusters: design, implementation and evaluation. IEEE Trans. Parallel Distrib. Syst. 25(10) (2014)
Bordawekar, R., Bondhugula, U., Rao. R.: Believe it or not!: mult-core cpus can match gpu performance for a flop-intensive application! In: Proceedings of the 19th International Conference on Parallel Architectures and Compilation Techniques, PACT ’10, (2010)
Farooqui, N., Schwan, K., Yalamanchili, S.: Efficient instrumentation of gpgpu applications using information flow analysis and symbolic execution. In: Proceedings of Workshop on General Purpose Processing Using GPUs, GPGPU-7 (2014)
Muniswamy-Reddy, K.-K.: Foundations for provenance-aware systems (2010)
Foster, I.T., Vckler, J.S., Wilde, M., Zhao, Y.: The virtual data grid: a new model and architecture for data-intensive collaboration. In: CIDR’03 (2003)
Provenance aware service oriented architecture. http://twiki.pasoa.ecs.soton.ac.uk/bin/view/PASOA/WebHome. Accessed 6 July 2015
Parker-Wood, A., Long, D.D.E., Miller, E.L., Seltzer, M., Tunkelang, D.: Making sense of file systems through provenance and rich metadata. Technical Report UCSC-SSRC-12-01, University of California, Santa Cruz, March 2012
Muniswamy-Reddy, K.-K., Holland, D.A., Braun, U., Seltzer, M.: Provenance-aware storage systems. In: Proceedings of the annual conference on USENIX ’06 Annual Technical Conference (2006)
Muniswamy-Reddy, K.-K., Macko, P., Seltzer, M.: Making a cloud provenance-aware. In: 1st Workshop on the Theory and Practice of Provenance (2009)
Muniswamy-Reddy, K.-K., Braun, U., Holland, D.A., Macko, P., Maclean, D., Margo, D., Seltzer, M., Smogor, R.: Layering in provenance systems. In: Proceedings of the 2009 USENIX Annual Technical Conference (2009)
Gehani, A., Tariq, D.: SPADE: support for provenance auditing in distributed environments. In: Proceedings of the 13th International Middleware Conference (2012)
Zhou, W., Sherr, M., Tao, T., Li, X., Thau Loo, B., Mao, Y.: Efficient querying and maintenance of network provenance at internet-scale. In: Proceedings of the 2010 International Conference on Management of Data, pp. 615–626 (2010)
Abraham, J., Brazier, P., Chebotko, A., Navarro, J., Piazza, A.: Distributed storage and querying techniques for a semantic web of scientific workflow provenance. In: 2010 IEEE International Conference on Services Computing (SCC), pp. 178–185. IEEE (2010)
Malik, T., Gehani, A., Tariq, D., Zaffar, F.: Sketching distributed data provenance. In: Data Provenance and Data Management in eScience, pp. 85–107 (2013)
Heinis, T., Alonso, G.: Efficient lineage tracking for scientific workflows. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1007–1018 (2008)
Extensible Markup Language (XML): http://www.w3.org/xml/. Accessed 13 Dec 2014
JSON: http://www.json.org/. Accessed 8 Dec 2014
Binary JSON: http://bsonspec.org/. Accessed 13 Dec 2014
Apache Thrift: https://thrift.apache.org/. Accessed 8 Dec 2014
Apache Avro: http://avro.apache.org/. Accessed 13 Dec 2014
Apache Etch: https://etch.apache.org/. Accessed 13 Dec 2014
BERT: http://bert-rpc.org/. Accessed 13 Dec 2014
Message Pack: http://msgpack.org/. Accessed 13 Dec 2014
Hessian: http://hessian.caucho.com/. Accessed 13 Dec 2014
ICE: http://doc.zeroc.com/display/ice34/home. Accessed 13 Dec 2014
CBOR: http://cbor.io/. Accessed 13 Dec 2014
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. In: Proceedings of USENIX Symposium on Opearting Systems Design & Implementation (2004)
Apache Hadoop: http://hadoop.apache.org/. Accessed 5 Sept 2014
Zaharia, M., Chowdhury, M., Franklin, M.J., Shenker, S., Stoica, I.: Spark: cluster computing with working sets. In: Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing (2010)
MPICH: http://www.mpich.org/. Accessed 10 Dec 2014
Open MPI: http://www.open-mpi.org/. Accessed 10 Dec 2014
OpenMP: http://openmp.org/wp/. Accessed 9 Dec 2014
PPL: http://msdn.microsoft.com/en-us/library/dd492418.aspx. Accessed 13 Dec 2014
Jeon, M., He, Y., Elnikety, S., Cox, A.L., Rixner, S.: Adaptive parallelism for web search. In: Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys ’13 (2013)
Jeon, M., Kim, S., Hwang, S., He, Y., Elnikety, S., Cox, A.L., Rixner, S.: Predictive parallelization: taming tail latencies in web search. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR ’14 (2014)
Lee, J., Winslett, M., Ma, X., Yu, S.: Enhancing data migration performance via parallel data compression. In: Proceedings of the 16th International Parallel and Distributed Processing Symposium, IPDPS ’02 (2002)
Klasky, S., Ethier, S., Lin, Z., Martins, K., McCune, D., Samtaney, R.: Grid-based parallel data streaming implemented for the gyrokinetic toroidal code. In: Proceedings of the 2003 ACM/IEEE Conference on Supercomputing, SC ’03 (2003)
Warneke, D., Kao, O.: Nephele: efficient parallel data processing in the cloud. In: Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS ’09 (2009)
Yu, Y., Isard, M., Fetterly, D., Budiu, M., Erlingsson, U., Gunda, P.K., Currey, J.: Dryadlinq: a system for general-purpose distributed data-parallel computing using a high-level language. In: Proceedings of the 8th USENIX Conference on Operating Systems Design and Implementation, OSDI’08 (2008)
Ronnie, C., Bob, J., Per-Ake, L., Bill, R., Darren, S., Simon, W., Jingren, Z.: Scope: easy and efficient parallel processing of massive data sets. Proc. VLDB Endow. 1(2), 1265–1276 (2008)
Ahrens, J., Brislawn, K., Martin, K., Geveci, B., Charles Law, C., Papka, M.: Large-scale data visualization using parallel data streaming. In: Computer Graphics and Applications. IEEE, 21(4), July 2001
Allen, M.D., Sridharan, S., Sohi, G.S.: Serialization sets: a dynamic dependence-based parallel execution model. In: Proceedings of the 14th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP ’09 (2009)
Voss, M., Eigenmann, R.: Reducing parallel overheads through dynamic serialization. In: Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing, IPPS ’99/SPDP ’99 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this chapter
Cite this chapter
Zhao, D., Mahakode, A., Lakshminarasaiah, S., Raicu, I. (2016). High-Performance Storage Support for Scientific Big Data Applications on the Cloud. In: Pop, F., Kołodziej, J., Di Martino, B. (eds) Resource Management for Big Data Platforms. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-44881-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-44881-7_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44880-0
Online ISBN: 978-3-319-44881-7
eBook Packages: Computer ScienceComputer Science (R0)