{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T23:21:23Z","timestamp":1725837683047},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319271361"},{"type":"electronic","value":"9783319271378"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-27137-8_15","type":"book-chapter","created":{"date-parts":[[2015,11,16]],"date-time":"2015-11-16T11:24:23Z","timestamp":1447673063000},"page":"190-202","source":"Crossref","is-referenced-by-count":1,"title":["Pre-stack Kirchhoff Time Migration on Hadoop and Spark"],"prefix":"10.1007","author":[{"given":"Chen","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heng","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gangshan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,12,16]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Shi, X., Wang, X., Zhao, C. et al.: Practical pre-stack Kirchhoff time migration of seismic processing on general purpose GPU. In: World Congress on Computer Science and Information Engineering, pp. 461\u2013465. IEEE (2009)","DOI":"10.1109\/CSIE.2009.78"},{"key":"15_CR2","unstructured":"Xue-Qi, C., Xiao-Long, J., Yuan-Zhuo, W., et al.: Summary of the big data systems and analysis techniques in Chinese. Journal of Software, vol. 25(9) (2014)"},{"key":"15_CR3","doi-asserted-by":"crossref","unstructured":"Gu, L., Li, H.: Memory or time: performance evaluation for iterative operation on hadoop and spark. In: 2013 IEEE International Conference on High Performance Computing and Communications and 2013 IEEE 10th International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), pp. 721\u2013727. IEEE (2013)","DOI":"10.1109\/HPCC.and.EUC.2013.106"},{"key":"15_CR4","unstructured":"Apache Hadoop. \n                      http:\/\/hadoop.apache.org"},{"key":"15_CR5","unstructured":"Zaharia, M., Konwinski, A., Joseph, A.D., et al.: Improving MapReduce performance in heterogeneous environments. In: OSDI, vol. 8(4), p. 7 (2008)"},{"key":"15_CR6","unstructured":"Apache Spark. \n                      http:\/\/spark.apache.org"},{"key":"15_CR7","unstructured":"Zaharia, M., Chowdhury, M., Franklin, M.J, et al.: Spark: cluster computing with working sets. In: Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing, p. 10 (2010)"},{"key":"15_CR8","unstructured":"Zaharia, M., Chowdhury, M., Das, T., et al.: Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing. In: Proceedings of the 9th USENIX Conference on Networked Systems Design and Implementation, p. 2. USENIX Association (2012)"},{"key":"15_CR9","doi-asserted-by":"crossref","unstructured":"Rizvandi, N.B., Boloori, A.J., Kamyabpour, N., et al.: MapReduce implementation of prestack Kirchhoff time migration (PKTM) on seismic data. In: 2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), pp. 86\u201391. IEEE (2011)","DOI":"10.1109\/PDCAT.2011.50"},{"issue":"2","key":"15_CR10","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.crme.2010.11.003","volume":"339","author":"GC Verdiere De","year":"2011","unstructured":"De Verdiere, G.C.: Introduction to GPGPU, a hardware and software background. C. R. Mcanique 339(2), 78\u201389 (2011)","journal-title":"C. R. Mcanique"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Panetta, J., Teixeira, T., de Souza Filho, P.R.P.: Accelerating Kirchhoff migration by CPU and GPU cooperation. In: 21st International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2009, pp. 26\u201332. IEEE (2009)","DOI":"10.1109\/SBAC-PAD.2009.29"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Gao, H., Tang, J., Wu, G.: A MapReduce computing framework based on GPU cluster. In: 2013 IEEE International Conference on High Performance Computing and Communications and 2013 IEEE 10th International Conference on Embedded Ubiquitous Computing (HPCC_EUC), pp. 1902\u20131907. IEEE (2013)","DOI":"10.1109\/HPCC.and.EUC.2013.273"},{"issue":"1","key":"15_CR13","first-page":"9","volume":"24","author":"W Gang","year":"2014","unstructured":"Gang, W., Jie, T., Gang-Shan, W.: GPU-based cluster framework in Chinese. Comput. Sci. Dev. 24(1), 9\u201313 (2014)","journal-title":"Comput. Sci. Dev."},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Lu, X., Islam, N.S., Wasi-ur-Rahman, M., et al.: High-performance design of Hadoop RPC with RDMA over InfiniBand. In: 2013 42nd International Conference on Parallel Processing (ICPP), pp. 641\u2013650. IEEE (2013)","DOI":"10.1109\/ICPP.2013.78"}],"container-title":["Lecture Notes in Computer Science","Algorithms and Architectures for Parallel Processing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-27137-8_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T15:19:58Z","timestamp":1559315998000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-27137-8_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319271361","9783319271378"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-27137-8_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]}}}