{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:15:17Z","timestamp":1761808517321,"version":"3.37.3"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T00:00:00Z","timestamp":1653004800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T00:00:00Z","timestamp":1653004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2020YFB1600201"],"award-info":[{"award-number":["2020YFB1600201"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62090024","61876173"],"award-info":[{"award-number":["62090024","61876173"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"YESS hip program","award":["YESS2016qnrc001"],"award-info":[{"award-number":["YESS2016qnrc001"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["CCF Trans. HPC"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1007\/s42514-022-00103-1","type":"journal-article","created":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T08:04:05Z","timestamp":1653033845000},"page":"302-320","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Cognitive SSD+: a deep learning engine for energy-efficient unstructured data retrieval"],"prefix":"10.1007","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8407-2594","authenticated-orcid":false,"given":"Shengwen","family":"Liang","sequence":"first","affiliation":[]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Huawei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xiaowei","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,20]]},"reference":[{"issue":"11","key":"103_CR1","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1145\/291006.291026","volume":"33","author":"A Acharya","year":"1998","unstructured":"Acharya, A., Uysal, M., Saltz, J.: Active disks: programming model, algorithms and evaluation. SIGPLAN Not 33(11), 81\u201391 (1998). https:\/\/doi.org\/10.1145\/291006.291026","journal-title":"SIGPLAN Not"},{"key":"103_CR2","doi-asserted-by":"publisher","unstructured":"Andersen, D.G., Franklin, J., Kaminsky, M., et\u00a0al.: Fawn: A fast array of wimpy nodes. In: Proceedings of the ACM SIGOPS 22Nd Symposium on Operating Systems Principles. ACM, New York, NY, USA, SOSP \u201909, pp 1\u201314,(2009) https:\/\/doi.org\/10.1145\/1629575.1629577,","DOI":"10.1145\/1629575.1629577"},{"key":"103_CR3","doi-asserted-by":"publisher","unstructured":"Balasubramonian, R., Chang, J., Manning, T., et al.: Near-data processing: Insights from a micro-46 workshop. IEEE Micro 34(4), 36\u201342 (2014)https:\/\/doi.org\/10.1109\/MM.2014.55, https:\/\/ieeexplore.ieee.org\/document\/6871738","DOI":"10.1109\/MM.2014.55"},{"key":"103_CR4","doi-asserted-by":"publisher","unstructured":"Boboila, S., Kim, Y., Vazhkudai, S.S., et\u00a0al.: Active flash: Out-of-core data analytics on flash storage. In: 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST), pp 1\u201312, (2012) https:\/\/doi.org\/10.1109\/MSST.2012.6232366, https:\/\/ieeexplore.ieee.org\/document\/6232366","DOI":"10.1109\/MSST.2012.6232366"},{"key":"103_CR5","doi-asserted-by":"publisher","unstructured":"Caulfield, A.M., De, A., Coburn, J., et\u00a0al.: Moneta: A high-performance storage array architecture for next-generation, non-volatile memories. In: Proceedings of the 2010 43rd Annual IEEE\/ACM International Symposium on Microarchitecture. IEEE Computer Society, Washington, DC, USA, MICRO \u201943, pp 385\u2013395, (2010) https:\/\/doi.org\/10.1109\/MICRO.2010.33,","DOI":"10.1109\/MICRO.2010.33"},{"key":"103_CR6","doi-asserted-by":"publisher","unstructured":"Chen, T., Du, Z., Sun, N., et\u00a0al.: Diannao: A small-footprint high-throughput accelerator for ubiquitous machine-learning. In: Proceedings of the 19th International Conference on Architectural Support for Programming Languages and Operating Systems. ACM, New York, NY, USA, ASPLOS \u201914, pp 269\u2013284, (2014) https:\/\/doi.org\/10.1145\/2541940.2541967,","DOI":"10.1145\/2541940.2541967"},{"key":"103_CR7","doi-asserted-by":"publisher","unstructured":"Chen, Y.H., Emer, J., Sze, V.: Eyeriss: A spatial architecture for energy-efficient dataflow for convolutional neural networks. In: Proceedings of the 43rd International Symposium on Computer Architecture. IEEE Press, Piscataway, NJ, USA, ISCA \u201916, pp 367\u2013379, (2016) https:\/\/doi.org\/10.1109\/ISCA.2016.40,","DOI":"10.1109\/ISCA.2016.40"},{"key":"103_CR8","doi-asserted-by":"publisher","unstructured":"Cheong, W., Yoon, C., Woo, S., et\u00a0al.: A flash memory controller for 15s ultra-low-latency ssd using high-speed 3d nand flash with 3s read time. In: 2018 IEEE International Solid - State Circuits Conference - (ISSCC), pp 338\u2013340, (2018) https:\/\/doi.org\/10.1109\/ISSCC.2018.8310322","DOI":"10.1109\/ISSCC.2018.8310322"},{"key":"103_CR9","doi-asserted-by":"publisher","unstructured":"Cho, S., Park, C., Oh, H., et\u00a0al.: Active disk meets flash: A case for intelligent ssds. In: Proceedings of the 27th International ACM Conference on International Conference on Supercomputing. ACM, New York, NY, USA, ICS \u201913, pp 91\u2013102,(2013) https:\/\/doi.org\/10.1145\/2464996.2465003,","DOI":"10.1145\/2464996.2465003"},{"key":"103_CR10","unstructured":"Choe, H., Lee, S., Park, S., et\u00a0al.: Near-data processing for machine learning. CoRR abs\/1610.02273. (2016) arXiv:1610.02273"},{"key":"103_CR11","doi-asserted-by":"publisher","unstructured":"De, A., Gokhale, M., Gupta, R., et\u00a0al.: Minerva: Accelerating data analysis in next-generation ssds. In: Proceedings of the 2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines. IEEE Computer Society, Washington, DC, USA, FCCM \u201913, pp 9\u201316,(2013) https:\/\/doi.org\/10.1109\/FCCM.2013.46,","DOI":"10.1109\/FCCM.2013.46"},{"key":"103_CR12","doi-asserted-by":"publisher","unstructured":"Do, J., Kee, Y.S., Patel, J.M., et\u00a0al.: Query processing on smart ssds: Opportunities and challenges. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. ACM, New York, NY, USA, SIGMOD \u201913, pp 1221\u20131230, (2013) https:\/\/doi.org\/10.1145\/2463676.2465295,","DOI":"10.1145\/2463676.2465295"},{"key":"103_CR13","doi-asserted-by":"publisher","unstructured":"Friedman, J., Baskett, F., Shustek, L.: An algorithm for finding nearest neighbors. IEEE Transactions on Computers C-24(10):1000\u20131006. (1975) https:\/\/doi.org\/10.1109\/T-C.1975.224110","DOI":"10.1109\/T-C.1975.224110"},{"key":"103_CR14","unstructured":"Fu, C., Cai, D.: EFANNA : An extremely fast approximate nearest neighbor search algorithm based on knn graph. CoRR abs\/1609.07228 (2016a) , arXiv:1609.07228"},{"key":"103_CR15","unstructured":"Fu, C., Cai, D.: Efanna: An extremely fast approximate nearest neighbor search algorithm based on knn graph (2016b) arXiv preprint arXiv:1609.07228"},{"key":"103_CR16","unstructured":"Fu, C., Wang, C., Cai, D.: Fast approximate nearest neighbor search with navigating spreading-out graphs. CoRR abs\/1707.00143. (2017a) arXiv:1707.00143"},{"key":"103_CR17","unstructured":"Fu, C., Wang, C., Cai, D.: Fast approximate nearest neighbor search with navigating spreading-out graphs. CoRR abs\/1707.00143. (2017b) arXiv:1707.00143"},{"issue":"12","key":"103_CR18","doi-asserted-by":"publisher","first-page":"2916","DOI":"10.1109\/TPAMI.2012.193","volume":"35","author":"Y Gong","year":"2013","unstructured":"Gong, Y., Lazebnik, S., Gordo, A., et al.: Iterative quantization: a procrustean approach to learning binary codes for large-scale image retrieval. IEEE Trans Pattern Anal Mach Intell 35(12), 2916\u20132929 (2013). https:\/\/doi.org\/10.1109\/TPAMI.2012.193","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"103_CR19","doi-asserted-by":"publisher","unstructured":"Guttman, A.: R-trees: A dynamic index structure for spatial searching. In: Proceedings of the 1984 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery, New York, NY, USA, SIGMOD \u201984, p 47\u201357, (1984) https:\/\/doi.org\/10.1145\/602259.602266,","DOI":"10.1145\/602259.602266"},{"key":"103_CR20","unstructured":"Ha, J.: crow: Crow is very fast and easy to use C++ micro web framework). (2018) https:\/\/github.com\/ipkn\/crow"},{"key":"103_CR21","doi-asserted-by":"crossref","unstructured":"Harwood, B., Drummond, T.: Fanng: Fast approximate nearest neighbour graphs. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 5713\u20135722 (2016)","DOI":"10.1109\/CVPR.2016.616"},{"key":"103_CR22","doi-asserted-by":"publisher","unstructured":"Hurson, A., Miller, L., Pakzad, S., et\u00a0al.: Parallel architectures for database systems. Advances in Computers, vol\u00a028. Elsevier, p 107 \u2013 151, (1989) https:\/\/doi.org\/10.1016\/S0065-2458(08)60047-9, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0065245808600479","DOI":"10.1016\/S0065-2458(08)60047-9"},{"key":"103_CR23","doi-asserted-by":"publisher","unstructured":"Jia, Y., Shelhamer, E., Donahue, J., et\u00a0al.: Caffe: Convolutional architecture for fast feature embedding. In: Proceedings of the 22Nd ACM International Conference on Multimedia. ACM, New York, NY, USA, MM \u201914, pp 675\u2013678, (2014) https:\/\/doi.org\/10.1145\/2647868.2654889,","DOI":"10.1145\/2647868.2654889"},{"key":"103_CR24","doi-asserted-by":"publisher","unstructured":"Jun, S.W., Liu, M., Lee, S., et\u00a0al.: Bluedbm: An appliance for big data analytics. In: Proceedings of the 42Nd Annual International Symposium on Computer Architecture. ACM, New York, NY, USA, ISCA \u201915, pp 1\u201313, (2015) https:\/\/doi.org\/10.1145\/2749469.2750412,","DOI":"10.1145\/2749469.2750412"},{"key":"103_CR25","doi-asserted-by":"publisher","unstructured":"Jun, S.W., Wright, A., Zhang, S., et\u00a0al.: Grafboost: Using accelerated flash storage for external graph analytics. In: Proceedings of the 45th Annual International Symposium on Computer Architecture. IEEE Press, Piscataway, NJ, USA, ISCA \u201918, pp 411\u2013424, (2018) https:\/\/doi.org\/10.1109\/ISCA.2018.00042,","DOI":"10.1109\/ISCA.2018.00042"},{"key":"103_CR26","doi-asserted-by":"crossref","unstructured":"Kang, Y., Kee, Y.S., Miller, E.L., et\u00a0al.: Enabling cost-effective data processing with smart ssd. 2013 IEEE 29th Symposium on Mass Storage Systems and Technologies (MSST) pp 1\u201312 (2013) ftp:\/\/ftp.cse.ucsc.edu\/pub\/darrell\/kang-msst13.pdf","DOI":"10.1109\/MSST.2013.6558444"},{"key":"103_CR27","doi-asserted-by":"publisher","unstructured":"Katayama, N., Satoh, S.: The sr-tree: An index structure for high-dimensional nearest neighbor queries. In: Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery, New York, NY, USA, SIGMOD \u201997, p 369\u2013380, (1997) https:\/\/doi.org\/10.1145\/253260.253347,","DOI":"10.1145\/253260.253347"},{"issue":"6","key":"103_CR28","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Commun ACM 60(6), 84\u201390 (2017). https:\/\/doi.org\/10.1145\/3065386","journal-title":"Commun ACM"},{"key":"103_CR29","doi-asserted-by":"publisher","unstructured":"Kwak, J., Lee, S., Park, K., et\u00a0al.: Cosmos+ openssd: Rapid prototype for flash storage systems. ACM Trans Storage 16(3) (2020) https:\/\/doi.org\/10.1145\/3385073,","DOI":"10.1145\/3385073"},{"key":"103_CR30","unstructured":"Lee, G., Shin, S., Song, W., et\u00a0al.: Asynchronous I\/O stack: A low-latency kernel I\/O stack for Ultra-Low latency SSDs. In: 2019 USENIX Annual Technical Conference (USENIX ATC 19). USENIX Association, Renton, WA, pp 603\u2013616, (2019) https:\/\/www.usenix.org\/conference\/atc19\/presentation\/lee-gyusun"},{"key":"103_CR31","unstructured":"Leilich, H.O., Stiege, G., Zeidler, H.C.: A search processor for data base management systems. In: Proceedings of the Fourth International Conference on Very Large Data Bases - Volume 4. VLDB Endowment, VLDB \u201978, pp 280\u2013287, (1978) http:\/\/dl.acm.org\/citation.cfm?id=1286643.1286682"},{"key":"103_CR32","unstructured":"Li, W., Zhang, Y., Sun, Y., et\u00a0al.: Approximate nearest neighbor search on high dimensional data - experiments, analyses, and improvement (v1.0). CoRR abs\/1610.02455. (2016a) http:\/\/arxiv.org\/abs\/1610.02455, arXiv:1610.02455"},{"key":"103_CR33","unstructured":"Li, W.J., Wang, S., Kang, W.C.: Feature learning based deep supervised hashing with pairwise labels. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. AAAI Press, IJCAI\u201916, pp 1711\u20131717, (2016b) http:\/\/dl.acm.org\/citation.cfm?id=3060832.3060860"},{"key":"103_CR34","unstructured":"Liang, S., Wang, Y., Lu, Y., et\u00a0al.: Cognitive SSD: A deep learning engine for In-Storage data retrieval. In: 2019 USENIX Annual Technical Conference (USENIX ATC 19). USENIX Association, Renton, WA, pp 395\u2013410, (2019) https:\/\/www.usenix.org\/conference\/atc19\/presentation\/liang"},{"issue":"1","key":"103_CR35","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1145\/320434.320447","volume":"1","author":"CS Lin","year":"1976","unstructured":"Lin, C.S., Smith, D.C.P., Smith, J.M.: The design of a rotating associative memory for relational database applications. ACM Trans Database Syst 1(1), 53\u201365 (1976). https:\/\/doi.org\/10.1145\/320434.320447","journal-title":"ACM Trans Database Syst"},{"key":"103_CR36","doi-asserted-by":"crossref","unstructured":"Lin, K., Yang, H., Hsiao, J., et\u00a0al.: Deep learning of binary hash codes for fast image retrieval. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp 27\u201335, (2015) http:\/\/ieeexplore.ieee.org\/document\/7301269\/","DOI":"10.1109\/CVPRW.2015.7301269"},{"key":"103_CR37","doi-asserted-by":"crossref","unstructured":"Liong, V.E., Lu, J., Wang, G., et\u00a0al.: Deep hashing for compact binary codes learning. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 2475\u20132483, (2015) http:\/\/ieeexplore.ieee.org\/document\/7298862\/","DOI":"10.1109\/CVPR.2015.7298862"},{"key":"103_CR38","doi-asserted-by":"publisher","unstructured":"Liu, G., Xu, J., Wang, C., et\u00a0al.: A performance comparison of http servers in a 10g\/40g network. In: Proceedings of the 2018 International Conference on Big Data and Computing. Association for Computing Machinery, New York, NY, USA, ICBDC \u201918, p 115\u2013118, (2018) https:\/\/doi.org\/10.1145\/3220199.3220216,","DOI":"10.1145\/3220199.3220216"},{"key":"103_CR39","doi-asserted-by":"crossref","unstructured":"Liu, H., Wang, R., Shan, S., et\u00a0al.: Deep supervised hashing for fast image retrieval. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 2064\u20132072, (2016) http:\/\/ieeexplore.ieee.org\/document\/7780596\/","DOI":"10.1109\/CVPR.2016.227"},{"key":"103_CR40","doi-asserted-by":"publisher","unstructured":"Mailthody, V.S., Qureshi, Z., Liang, W., et\u00a0al.: Deepstore: In-storage acceleration for intelligent queries. In: Proceedings of the 52nd Annual IEEE\/ACM International Symposium on Microarchitecture. Association for Computing Machinery, New York, NY, USA, MICRO \u201952, p 224\u2013238, (2019) https:\/\/doi.org\/10.1145\/3352460.3358320,","DOI":"10.1145\/3352460.3358320"},{"issue":"4","key":"103_CR41","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1109\/TPAMI.2018.2889473","volume":"42","author":"YA Malkov","year":"2018","unstructured":"Malkov, Y.A., Yashunin, D.A.: Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Trans Pattern Anal Mach Intell 42(4), 824\u2013836 (2018)","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"103_CR42","unstructured":"Muja, M., Lowe, D.G.: Fast approximate nearest neighbors with automatic algorithm configuration. VISAPP (1) 2(331-340):2 (2009)"},{"issue":"3","key":"103_CR43","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1023\/A:1011139631724","volume":"42","author":"A Oliva","year":"2001","unstructured":"Oliva, A., Torralba, A.: Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vis 42(3), 145\u2013175 (2001). https:\/\/doi.org\/10.1023\/A:1011139631724","journal-title":"Int J Comput Vis"},{"key":"103_CR44","doi-asserted-by":"crossref","unstructured":"Ouyang, J., Lin, S., Hou, Z., et\u00a0al.: Active ssd design for energy-efficiency improvement of web-scale data analysis. In: Proceedings of the 2013 International Symposium on Low Power Electronics and Design. IEEE Press, Piscataway, NJ, USA, ISLPED \u201913, pp 286\u2013291, (2013) http:\/\/dl.acm.org\/citation.cfm?id=2648668.2648739","DOI":"10.1109\/ISLPED.2013.6629310"},{"key":"103_CR45","unstructured":"Riedel, E., Gibson, G.A., Faloutsos, C.: Active storage for large-scale data mining and multimedia. In: Proceedings of the 24rd International Conference on Very Large Data Bases. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, VLDB \u201998, pp 62\u201373, (1998) http:\/\/dl.acm.org\/citation.cfm?id=645924.671345"},{"issue":"6","key":"103_CR46","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/2.928624","volume":"34","author":"E Riedel","year":"2001","unstructured":"Riedel, E., Faloutsos, C., Gibson, G.A., et al.: Active disks for large-scale data processing. Computer 34(6), 68\u201374 (2001). https:\/\/doi.org\/10.1109\/2.928624","journal-title":"Computer"},{"key":"103_CR47","doi-asserted-by":"publisher","unstructured":"Schuster, S.A., Nguyen, H.B., Ozkarahan, E.A., et\u00a0al.: Rap.2 an associative processor for databases and its applications. IEEE Trans Comput 28(6):446\u2013458 (1979) https:\/\/doi.org\/10.1109\/TC.1979.1675383,","DOI":"10.1109\/TC.1979.1675383"},{"key":"103_CR48","unstructured":"Seshadri, S., Gahagan, M., Bhaskaran, S., et\u00a0al.: Willow: A user-programmable ssd. In: Proceedings of the 11th USENIX Conference on Operating Systems Design and Implementation. USENIX Association, Berkeley, CA, USA, OSDI\u201914, pp 67\u201380, (2014) http:\/\/dl.acm.org\/citation.cfm?id=2685048.2685055"},{"key":"103_CR49","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR abs\/1409.1556. (2014) http:\/\/arxiv.org\/abs\/1409.1556, arXiv:1409.1556"},{"key":"103_CR50","doi-asserted-by":"publisher","unstructured":"Son, Y., Song, N.Y., Han, H., et\u00a0al.: A user-level file system for fast storage devices. In: Proceedings of the 2014 International Conference on Cloud and Autonomic Computing. IEEE Computer Society, Washington, DC, USA, ICCAC \u201914, pp 258\u2013264, (2014) https:\/\/doi.org\/10.1109\/ICCAC.2014.14","DOI":"10.1109\/ICCAC.2014.14"},{"key":"103_CR51","unstructured":"Tiwari, D., Vazhkudai, S.S., Kim, Y., et\u00a0al.: Reducing data movement costs using energy efficient, active computation on ssd. In: Proceedings of the 2012 USENIX conference on power-aware computing and systems. USENIX Association, Berkeley, CA, USA, HotPower\u201912, pp 4\u20134, (2012) http:\/\/dl.acm.org\/citation.cfm?id=2387869.2387873"},{"key":"103_CR52","unstructured":"Tiwari, D., Boboila, S., Vazhkudai, S.S., et\u00a0al.: Active flash: Towards energy-efficient, in-situ data analytics on extreme-scale machines. In: Proceedings of the 11th USENIX conference on file and storage technologies. USENIX association, Berkeley, CA, USA, FAST\u201913, pp 119\u2013132, (2013) http:\/\/dl.acm.org\/citation.cfm?id=2591272.2591286"},{"key":"103_CR53","doi-asserted-by":"crossref","unstructured":"Tripathy, S., Sahoo, D., Satpathy, M., et\u00a0al.: Formal modeling and verification of nand flash memory supporting advanced operations. In: 2019 IEEE 37th International Conference on Computer Design (ICCD), pp 313\u2013316, (2019) 10.1109\/ICCD46524.2019.00048","DOI":"10.1109\/ICCD46524.2019.00048"},{"key":"103_CR54","doi-asserted-by":"publisher","unstructured":"Tripathy, S., Sahoo, D., Satpathy, M., et\u00a0al.: Fuzzy fairness controller for nvme ssds. In: Proceedings of the 34th ACM International Conference on Supercomputing. Association for Computing Machinery, New York, NY, USA, ICS \u201920, (2020) https:\/\/doi.org\/10.1145\/3392717.3392766","DOI":"10.1145\/3392717.3392766"},{"issue":"3","key":"103_CR55","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1145\/3007787.3001143","volume":"44","author":"HW Tseng","year":"2016","unstructured":"Tseng, H.W., Zhao, Q., Zhou, Y., et al.: Morpheus: creating application objects efficiently for heterogeneous computing. SIGARCH Comput Archit News 44(3), 53\u201365 (2016). https:\/\/doi.org\/10.1145\/3007787.3001143","journal-title":"SIGARCH Comput Archit News"},{"key":"103_CR56","unstructured":"Wang, J., Shen, H.T., Song, J., et\u00a0al.: Hashing for similarity search: a survey. arXiv:1408.2927 [cs] (2014) http:\/\/arxiv.org\/abs\/1408.2927"},{"key":"103_CR57","doi-asserted-by":"publisher","unstructured":"Wang, J., Park, D., Kee, YS., et\u00a0al.: Ssd in-storage computing for list intersection. In: Proceedings of the 12th international workshop on data management on new hardware, DaMoN \u201916, pp 4:1\u20134:7,(2016) https:\/\/doi.org\/10.1145\/2933349.2933353","DOI":"10.1145\/2933349.2933353"},{"key":"103_CR58","doi-asserted-by":"publisher","unstructured":"Wang, M., Xu, X., Yue, Q., et\u00a0al.: A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search. Proc VLDB Endow 14(11):1964\u20131978 (2021) https:\/\/doi.org\/10.14778\/3476249.3476255","DOI":"10.14778\/3476249.3476255"},{"issue":"12","key":"103_CR59","doi-asserted-by":"publisher","first-page":"3152","DOI":"10.14778\/3415478.3415541","volume":"13","author":"C Wei","year":"2020","unstructured":"Wei, C., Wu, B., Wang, S., et al.: Analyticdb-v: a hybrid analytical engine towards query fusion for structured and unstructured data. Proc VLDB Endowment 13(12), 3152\u20133165 (2020)","journal-title":"Proc VLDB Endowment"},{"key":"103_CR60","doi-asserted-by":"publisher","unstructured":"Woods, L., Istv\u00e1n, Z., Alonso, G.: Ibex: An intelligent storage engine with support for advanced sql offloading. Proc VLDB Endow 7(11):963\u2013974 (2014) https:\/\/doi.org\/10.14778\/2732967.2732972","DOI":"10.14778\/2732967.2732972"},{"issue":"2","key":"103_CR61","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1109\/TPAMI.2017.2666812","volume":"40","author":"HF Yang","year":"2018","unstructured":"Yang, H.F., Lin, K., Chen, C.S.: Supervised learning of semantics-preserving hash via deep convolutional neural networks. IEEE Trans Pattern Anal Mach Intell 40(2), 437\u2013451 (2018). https:\/\/doi.org\/10.1109\/TPAMI.2017.2666812","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"103_CR62","unstructured":"Zhang, J., Kwon, M., Gouk, D., et\u00a0al.: Flashshare: Punching through server storage stack from kernel to firmware for ultra-low latency ssds. In: Proceedings of the 12th USENIX conference on operating systems design and implementation. USENIX Association, Berkeley, CA, USA, OSDI\u201918, pp 477\u2013492,(2018) http:\/\/dl.acm.org\/citation.cfm?id=3291168.3291203"},{"key":"103_CR63","unstructured":"Zhao, F., Huang, Y., Wang, L., et\u00a0al.: Deep semantic ranking based hashing for multi-label image retrieval. CoRR abs\/1501.06272.(2015) arXiv:1501.06272"},{"key":"103_CR64","unstructured":"Zheng, L., Yang, Y., Tian, Q.: SIFT meets CNN: a decade survey of instance retrieval. CoRR abs\/1608.01807 (2016) http:\/\/arxiv.org\/abs\/1608.01807, arXiv:1608.01807"}],"container-title":["CCF Transactions on High Performance Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42514-022-00103-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42514-022-00103-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42514-022-00103-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T15:49:41Z","timestamp":1665416981000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42514-022-00103-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,20]]},"references-count":64,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["103"],"URL":"https:\/\/doi.org\/10.1007\/s42514-022-00103-1","relation":{},"ISSN":["2524-4922","2524-4930"],"issn-type":[{"type":"print","value":"2524-4922"},{"type":"electronic","value":"2524-4930"}],"subject":[],"published":{"date-parts":[[2022,5,20]]},"assertion":[{"value":"13 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 April 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 May 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}