{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T22:43:11Z","timestamp":1780440191371,"version":"3.54.1"},"reference-count":14,"publisher":"Association for Computing Machinery (ACM)","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,8]]},"abstract":"<jats:p>The past years saw the emergence of highly heterogeneous server architectures that feature multiple accelerators in addition to the main processor. Efficiently exploiting these systems for data processing is a challenging research problem that comprises many facets, including how to find an optimal operator placement strategy, how to estimate runtime costs across different hardware architectures, and how to manage the code and maintenance blowup caused by having to support multiple architectures.<\/jats:p>\n          <jats:p>In prior work, we already discussed solutions to some of these problems: First, we showed that specifying operators in a hardware-oblivious way can prevent code blowup while still maintaining competitive performance when supporting multiple architectures. Second, we presented learning cost functions and several heuristics to efficiently place operators across all available devices.<\/jats:p>\n          <jats:p>In this demonstration, we provide further insights into this line of work by presenting our combined system Ocelot\/HyPE. Our system integrates a hardware-oblivious data processing engine with a learning query optimizer for placement decisions, resulting in a highly adaptive DBMS that is specifically tailored towards heterogeneous hardware environments.<\/jats:p>","DOI":"10.14778\/2733004.2733042","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T15:37:52Z","timestamp":1431445072000},"page":"1609-1612","source":"Crossref","is-referenced-by-count":20,"title":["Ocelot\/HyPE"],"prefix":"10.14778","volume":"7","author":[{"given":"Sebastian","family":"Bre\u00df","sequence":"first","affiliation":[{"name":"TU Dortmund University and University of Magdeburg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bastian","family":"K\u00f6cher","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Berlin"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Max","family":"Heimel","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Berlin"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Volker","family":"Markl","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Berlin"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Saecker","sequence":"additional","affiliation":[{"name":"Parstream GmbH"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gunter","family":"Saake","sequence":"additional","affiliation":[{"name":"University of Magdeburg"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2014,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1409360.1409380"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1941487.1941507"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536274.2536325"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2013.05.004"},{"key":"e_1_2_1_5_1","first-page":"288","volume-title":"ADBIS","author":"Bre\u00df S.","year":"2013","unstructured":"S. Bre\u00df , N. Siegmund , L. Bellatreche , and G. Saake . An operator-stream-based scheduling engine for effective GPU coprocessing . In ADBIS , pages 288 -- 301 . Springer , 2013 . S. Bre\u00df, N. Siegmund, L. Bellatreche, and G. Saake. An operator-stream-based scheduling engine for effective GPU coprocessing. In ADBIS, pages 288--301. Springer, 2013."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1620585.1620588"},{"key":"e_1_2_1_7_1","first-page":"616","volume-title":"EDBT","author":"Heimel M.","year":"2014","unstructured":"M. Heimel , F. Haase , M. Meinke , S. Bre\u00df , M. Saecker , and V. Markl . Demonstrating self-learning algorithm adaptivity in a hardware-oblivious database engine . In EDBT , pages 616 -- 619 , 2014 . M. Heimel, F. Haase, M. Meinke, S. Bre\u00df, M. Saecker, and V. Markl. Demonstrating self-learning algorithm adaptivity in a hardware-oblivious database engine. In EDBT, pages 616--619, 2014."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536360.2536370"},{"issue":"1","key":"e_1_2_1_9_1","first-page":"40","article-title":"MonetDB: Two decades of research in column-oriented database architectures","volume":"35","author":"Idreos S.","year":"2012","unstructured":"S. Idreos MonetDB: Two decades of research in column-oriented database architectures . IEEE Data Eng. Bull. , 35 ( 1 ): 40 -- 45 , 2012 . S. Idreos et al. MonetDB: Two decades of research in column-oriented database architectures. IEEE Data Eng. Bull., 35(1):40--45, 2012.","journal-title":"IEEE Data Eng. Bull."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2594526"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687730"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2479871.2479927"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536206.2536210"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536274.2536319"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2733004.2733042","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:42:48Z","timestamp":1672220568000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2733004.2733042"}},"subtitle":["optimized data processing on heterogeneous hardware"],"short-title":[],"issued":{"date-parts":[[2014,8]]},"references-count":14,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2014,8]]}},"alternative-id":["10.14778\/2733004.2733042"],"URL":"https:\/\/doi.org\/10.14778\/2733004.2733042","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2014,8]]}}}