{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T03:55:48Z","timestamp":1743047748119,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030495558"},{"type":"electronic","value":"9783030495565"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-49556-5_11","type":"book-chapter","created":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T23:05:06Z","timestamp":1591657506000},"page":"110-115","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["The Implementation and Optimization of Matrix Decomposition Based Collaborative Filtering Task on X86 Platform"],"prefix":"10.1007","author":[{"given":"Tianshu","family":"Hao","sequence":"first","affiliation":[]},{"given":"Ziping","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,6,9]]},"reference":[{"key":"11_CR1","unstructured":"Recommender system. \nhttps:\/\/en.wikipedia.org\/wiki\/Recommender_system\n\n. Accessed 14 Oct 2019"},{"issue":"8","key":"11_CR2","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TPAMI.2016.2605085","volume":"39","author":"B Yang","year":"2016","unstructured":"Yang, B., Lei, Y., Liu, J., Li, W.: Social collaborative filtering by trust. IEEE Trans. Pattern Anal. Mach. Intell. 39(8), 1633\u20131647 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Das, A.S., Datar. M., Garg, A., Rajaram, S.: Google news personalization: scalable online collaborative filtering. In: Proceedings of the 16th International Conference on World Wide Web, 8 May 2007, pp. 271\u2013280. ACM (2017)","DOI":"10.1145\/1242572.1242610"},{"issue":"1","key":"11_CR4","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/MIC.2003.1167344","volume":"1","author":"G Linden","year":"2003","unstructured":"Linden, G., Smith, B., York, J.: Amazon. com recommendations: item-to-item collaborative filtering. IEEE Internet Comput. 1(1), 76\u201380 (2003)","journal-title":"IEEE Internet Comput."},{"key":"11_CR5","unstructured":"Netflix. \nhttp:\/\/www.netflix.com\n\n. Accessed 14 Oct 2019"},{"key":"11_CR6","unstructured":"Reddit. \nhttps:\/\/www.reddit.com\n\n. Accessed 14 Oct 2019"},{"key":"11_CR7","unstructured":"Youtube. \nhttps:\/\/www.youtube.com\/\n\n. Accessed 14 Oct 2019"},{"key":"11_CR8","unstructured":"MovieLens. \nhttps:\/\/grouplens.org\/datasets\/movielens\/"},{"issue":"4","key":"11_CR9","first-page":"19","volume":"5","author":"FM Harper","year":"2016","unstructured":"Harper, F.M., Konstan, J.A.: The movielens datasets: history and context. ACM Trans. Interact. Intell. Syst. (TIIS) 5(4), 19 (2016)","journal-title":"ACM Trans. Interact. Intell. Syst. (TIIS)"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"ALS description in apache flink. \nhttps:\/\/ci.apache.org\/projects\/flink\/flink-docs-release-1.2\/dev\/libs\/ml\/als.html\n\n. Accessed 25 Oct 2019","DOI":"10.1007\/978-3-319-63962-8_303-1"},{"key":"11_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1007\/978-3-540-68880-8_32","volume-title":"Algorithmic Aspects in Information and Management","author":"Y Zhou","year":"2008","unstructured":"Zhou, Y., Wilkinson, D., Schreiber, R., Pan, R.: Large-scale parallel collaborative filtering for the netflix prize. In: Fleischer, R., Xu, J. (eds.) AAIM 2008. LNCS, vol. 5034, pp. 337\u2013348. Springer, Heidelberg (2008). \nhttps:\/\/doi.org\/10.1007\/978-3-540-68880-8_32"},{"key":"11_CR12","unstructured":"BLAS. \nhttps:\/\/en.wikipedia.org\/wiki\/Basic_Linear_Algebra_Subprograms\n\n. Accessed 25 Oct 2019"},{"key":"11_CR13","unstructured":"Xianyi, Z., Qian, W., Saar, W.: OpenBLAS: An optimized BLAS library. Agosto, Accedido (2016)"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Hu, Y., Koren, Y., Volinsky, C.: Collaborative filtering for implicit feedback datasets. In: 2008 Eighth IEEE International Conference on Data Mining, 15 December 2008, pp. 263\u2013272. IEEE (2008)","DOI":"10.1109\/ICDM.2008.22"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Li, Z., et al.: AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 17 November 2019, p. 25. ACM (2019)","DOI":"10.1145\/3295500.3356138"},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Wang, Q., Zhang, X., Zhang, Y., Yi, Q.: AUGEM: automatically generate high performance dense linear algebra kernels on x86 CPUs. In: SC 2013: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 17 November 2013, pp. 1\u201312. IEEE (2013)","DOI":"10.1145\/2503210.2503219"},{"key":"11_CR17","unstructured":"Gao, W., et al.: AIBench: an industry standard internet service AI benchmark suite. arXiv preprint \narXiv:1908.08998\n\n, 13 August 2019"},{"key":"11_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-32813-9_1","volume-title":"Benchmarking, Measuring, and Optimizing","author":"W Gao","year":"2019","unstructured":"Gao, W., et al.: AIBench: towards scalable and comprehensive datacenter AI benchmarking. In: Zheng, C., Zhan, J. (eds.) Bench 2018. LNCS, vol. 11459, pp. 3\u20139. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-32813-9_1"},{"key":"11_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/978-3-030-32813-9_3","volume-title":"Benchmarking, Measuring, and Optimizing","author":"T Hao","year":"2019","unstructured":"Hao, T., et al.: Edge AIBench: towards comprehensive end-to-end edge computing benchmarking. In: Zheng, C., Zhan, J. (eds.) Bench 2018. LNCS, vol. 11459, pp. 23\u201330. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-32813-9_3"},{"key":"11_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1007\/978-3-030-32813-9_2","volume-title":"Benchmarking, Measuring, and Optimizing","author":"Z Jiang","year":"2019","unstructured":"Jiang, Z., et al.: HPC AI500: a benchmark suite for HPC AI systems. In: Zheng, C., Zhan, J. (eds.) Bench 2018. LNCS, vol. 11459, pp. 10\u201322. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-32813-9_2"},{"key":"11_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/978-3-030-32813-9_4","volume-title":"Benchmarking, Measuring, and Optimizing","author":"C Luo","year":"2019","unstructured":"Luo, C., et al.: AIoT bench: towards comprehensive benchmarking mobile and embedded device intelligence. In: Zheng, C., Zhan, J. (eds.) Bench 2018. LNCS, vol. 11459, pp. 31\u201335. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-32813-9_4"},{"key":"11_CR22","first-page":"116","volume-title":"Bench 2019, LNCS","author":"M Chen","year":"2019","unstructured":"Chen, M., Chen, T., Chen, Q.: An efficient implementation of the ALS-WR algorithm on x86 CPUs. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 116\u2013122. Springer, Cham (2019)"},{"key":"11_CR23","first-page":"101","volume-title":"Bench 2019, LNCS","author":"W Deng","year":"2019","unstructured":"Deng, W., Wang, P., Wang, J., Li, C., Guo, M.: PSL: exploiting parallelism, sparsity and locality to accelerate matrix factorization on X86 platforms. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 101\u2013109. Springer, Cham (2019)"},{"key":"11_CR24","first-page":"141","volume-title":"Bench 2019, LNCS","author":"X Xiong","year":"2019","unstructured":"Xiong, X., Wen, X., Huang, C.: Improving RGB-D face recognition via transfer learning from a pretrained 2D network. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 141\u2013148. Springer, Cham (2019)"},{"key":"11_CR25","first-page":"149","volume-title":"Bench 2019, LNCS","author":"T Gong","year":"2019","unstructured":"Gong, T., Niu, H.: An implementation of ResNet on the classification of RGB-D images. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 149\u2013155. Springer, Cham (2019)"},{"key":"11_CR26","first-page":"57","volume-title":"Bench 2019, LNCS","author":"J Li","year":"2019","unstructured":"Li, J., Jiang, Z.: Performance analysis of cambricon MLU100. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 57\u201366. Springer, Cham (2019)"},{"key":"11_CR27","first-page":"51","volume-title":"Bench 2019, LNCS","author":"G Li","year":"2019","unstructured":"Li, G., Wang, X., Ma, X., Liu, L., Feng, X.: XDN: towards efficient inference of residual neural networks on cambricon chips. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 51\u201356. Springer, Cham (2019)"},{"key":"11_CR28","first-page":"85","volume-title":"Bench 2019, LNCS","author":"P Hou","year":"2019","unstructured":"Hou, P., Yu, J., Miao, Y., Tai, Y., Wu, Y., Zhao, C.: RVTensor: a light-weight neural network inference framework based on the RISC-V architecture. In: Gao, W., et al. (eds.) Bench 2019, LNCS, vol. 12093, pp. 85\u201390. Springer, Cham (2019)"}],"container-title":["Lecture Notes in Computer Science","Benchmarking, Measuring, and Optimizing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-49556-5_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T23:06:38Z","timestamp":1591657598000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-49556-5_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030495558","9783030495565"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-49556-5_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"9 June 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Bench","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Benchmarking, Measuring and Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Denver, CO","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bench2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.benchcouncil.org\/bench19\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"79","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":"20","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":"11","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":"25% - 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":"10","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)"}}]}}