{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:26:49Z","timestamp":1743060409902,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030352240"},{"type":"electronic","value":"9783030352257"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-35225-7_17","type":"book-chapter","created":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T13:04:56Z","timestamp":1574168696000},"page":"262-277","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Fast Dynamic Graph Algorithms"],"prefix":"10.1007","author":[{"given":"Gaurav","family":"Malhotra","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hitish","family":"Chappidi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rupesh","family":"Nasre","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,11,15]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Wang, Y., Davidson, A., Pan, Y., Wu, Y., Riffel, A., Owens, J.D.: Gunrock: a high-performance graph processing library on the GPU. In: PPoPP (2015)","DOI":"10.1145\/2688500.2688538"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Gharaibeh, A., Costa, L.B., Santos-Neto, E., Ripeanu, M.: A yoke of oxen and a thousand chickens for heavy lifting graph processing. In: PACT (2012)","DOI":"10.1145\/2370816.2370866"},{"key":"17_CR3","doi-asserted-by":"crossref","unstructured":"Hong, S., Kim, S.K., Oguntebi, T., Olukotun, K.: Accelerating CUDA graph algorithms at maximum warp. In: PPoPP, pp. 267\u2013276 (2011)","DOI":"10.1145\/2038037.1941590"},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Merrill, D.G., Garland, M., Grimshaw, A.S.: Scalable GPU graph traversal. In: PPoPP (2012)","DOI":"10.1145\/2145816.2145832"},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Nasre, R., Burtscher, M., Pingali, K.: Data-driven versus topology-driven irregular computations on GPUs. In: IPDPS, pp. 463\u2013474 (2013)","DOI":"10.1109\/IPDPS.2013.28"},{"key":"17_CR6","unstructured":"Leskovec, J., Sosi\u010d, R.: SNAP: a general purpose network analysis and graph mining library in C++, June 2014. http:\/\/snap.stanford.edu\/snap"},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Pingali, K., et al.: The tao of parallelism in algorithms. In: PLDI, pp. 12\u201325 (2011)","DOI":"10.1145\/1993498.1993501"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Vineet, V., Harish, P., Patidar, S., Narayanan, P.J.: Fast minimum spanning tree for large graphs on the GPU. In: HPG, pp. 167\u2013171 (2009)","DOI":"10.1145\/1572769.1572796"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Burtscher, M., Nasre, R., Pingali, K.: A quantitative study of irregular programs on GPUs. In: IISWC, pp. 141\u2013151 (2012)","DOI":"10.1109\/IISWC.2012.6402918"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Hant, W., et al.: Chronos: a graph engine for temporal graph analysis. In: ECCS, p. 1 (2014)","DOI":"10.1145\/2592798.2592799"},{"issue":"11","key":"17_CR11","doi-asserted-by":"crossref","first-page":"726","DOI":"10.14778\/3402707.3402713","volume":"4","author":"C Ren","year":"2011","unstructured":"Ren, C., Lo, E., Kao, B., Zhu, X., Cheng, R.: On querying historical evolving graph sequences. Proc. VLDB Endow. 4(11), 726\u2013737 (2011)","journal-title":"Proc. VLDB Endow."},{"key":"17_CR12","unstructured":"Kan, A., Chan, J., Bailey, J., Leckie, C.: A query based approach for mining evolving graphs. In: Proceedings of the Eighth Australasian Data Mining Conference, vol. 101, pp. 139\u2013150. Australian Computer Society Inc. (2009)"},{"key":"17_CR13","unstructured":"Yoo, A., Chow, E., Henderson, K., McLendon, W., Hendrickson, B., Catalyurek, U.: A scalable distributed parallel breadth-first search algorithm on BlueGene\/L. In: SC, p. 25 (2005)"},{"key":"17_CR14","unstructured":"Bader, D.A., Madduri, K.: Designing multithreaded algorithms for breadth-first search and st-connectivity on the Cray MTA-2. In: ICPP, pp. 523\u2013530 (2006)"},{"issue":"6","key":"17_CR15","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1145\/1273442.1250759","volume":"42","author":"M Kulkarni","year":"2007","unstructured":"Kulkarni, M., Pingali, K., Walter, B., Ramanarayanan, G., Bala, K., Chew, L.P.: Optimistic parallelism requires abstractions. SIGPLAN Not. (PLDI) 42(6), 211\u2013222 (2007)","journal-title":"SIGPLAN Not. (PLDI)"},{"key":"17_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/978-3-540-77220-0_21","volume-title":"High Performance Computing \u2013 HiPC 2007","author":"P Harish","year":"2007","unstructured":"Harish, P., Narayanan, P.J.: Accelerating large graph algorithms on the GPU using CUDA. In: Aluru, S., Parashar, M., Badrinath, R., Prasanna, V.K. (eds.) HiPC 2007. LNCS, vol. 4873, pp. 197\u2013208. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-77220-0_21"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Luo, L., Wong, M., Hwu, W.-M.: An effective GPU implementation of breadth-first search. In: DAC, pp. 52\u201355 (2010)","DOI":"10.1145\/1837274.1837289"},{"key":"17_CR18","doi-asserted-by":"crossref","unstructured":"Hong, S., Oguntebi, T., Olukotun, K.: Efficient parallel graph exploration on multi-core CPU and GPU. In: PACT. PACT 2011 (2011)","DOI":"10.1109\/PACT.2011.14"},{"issue":"9","key":"17_CR19","doi-asserted-by":"publisher","first-page":"950","DOI":"10.14778\/2777598.2777604","volume":"8","author":"M Han","year":"2015","unstructured":"Han, M., Daudjee, K.: Giraph unchained: barrierless asynchronous parallel execution in pregel-like graph processing systems. Proc. VLDB Endow. 8(9), 950\u2013961 (2015)","journal-title":"Proc. VLDB Endow."},{"key":"17_CR20","unstructured":"Nobari, S., Cao, T.-T., Karras, P., Bressan, S.: Scalable parallel minimum spanning forest computation. In: Proceedings of the 17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. PPoPP 2012, pp. 205\u2013214. ACM, New York (2012). http:\/\/doi.acm.org\/10.1145\/2145816.2145842"},{"key":"17_CR21","unstructured":"Huang, S., Fu, A.W.-C., Liu, R.: Minimum spanning trees in temporal graphs. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data. SIGMOD 2015, pp. 419\u2013430. ACM, New York (2015). http:\/\/doi.acm.org\/10.1145\/2723372.2723717"},{"key":"17_CR22","doi-asserted-by":"crossref","unstructured":"Ashari, A., Sedaghati, N., Eisenlohr, J., Parthasarathy, S., Sadayappan, P.: Fast sparse matrix-vector multiplication on GPUs for graph applications. In: SC, pp. 781\u2013792 (2014)","DOI":"10.1109\/SC.2014.69"},{"key":"17_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/978-3-319-41321-1_4","volume-title":"High Performance Computing","author":"J King","year":"2016","unstructured":"King, J., Gilray, T., Kirby, R.M., Might, M.: Dynamic sparse-matrix allocation on GPUs. In: Kunkel, J.M., Balaji, P., Dongarra, J. (eds.) ISC High Performance 2016. LNCS, vol. 9697, pp. 61\u201380. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-41321-1_4"},{"key":"17_CR24","doi-asserted-by":"crossref","unstructured":"Green, O., Bader, D.A.: cuSTINGER: supporting dynamic graph algorithms for GPUs. In: 2016 IEEE High Performance Extreme Computing Conference (HPEC), pp. 1\u20136, September 2016","DOI":"10.1109\/HPEC.2016.7761622"},{"key":"17_CR25","doi-asserted-by":"crossref","unstructured":"Nasre, R., Burtscher, M., Pingali, K.: Morph algorithms on GPUs. In: PPoPP, pp. 147\u2013156 (2013)","DOI":"10.1145\/2517327.2442531"},{"key":"17_CR26","unstructured":"Cheramangalath, U., Nasre, R., Srikant, Y.N.: Falcon: a graph manipulation language for heterogeneous systems. ACM Trans. Archit. Code Optim. 12(4), 54:1\u201354:27 (2015). http:\/\/doi.acm.org\/10.1145\/2842618"}],"container-title":["Lecture Notes in Computer Science","Languages and Compilers for Parallel Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-35225-7_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,4]],"date-time":"2021-02-04T01:57:30Z","timestamp":1612403850000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-35225-7_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030352240","9783030352257"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-35225-7_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"15 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"LCPC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Languages and Compilers for Parallel Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"College Station, TX","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"lcpc2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/parasol.tamu.edu\/lcpc2017\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Hotcrp.com","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"54% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}