{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:25:32Z","timestamp":1743103532662,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031218668"},{"type":"electronic","value":"9783031218675"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-21867-5_6","type":"book-chapter","created":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T11:04:07Z","timestamp":1670929447000},"page":"85-99","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Effects of\u00a0Approximate Computing on\u00a0Workload Characteristics"],"prefix":"10.1007","author":[{"given":"Daniel","family":"Maier","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Schirmeister","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben","family":"Juurlink","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,14]]},"reference":[{"key":"6_CR1","doi-asserted-by":"crossref","unstructured":"Besnard, L., Pinto, P., Lasri, I., Bispo, J., Rohou, E., Cardoso, J.M.: A framework for automatic and parameterizable memoization. SoftwareX 10, 100322 (2019)","DOI":"10.1016\/j.softx.2019.100322"},{"key":"6_CR2","doi-asserted-by":"crossref","unstructured":"Brumar, I., Casas, M., Moreto, M., Valero, M., Sohi, G.S.: ATM: approximate task memoization in the runtime system. In: IPDPS. IEEE (2017)","DOI":"10.1109\/IPDPS.2017.49"},{"issue":"2","key":"6_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3388785","volume":"17","author":"S Cherubin","year":"2020","unstructured":"Cherubin, S., Cattaneo, D., Chiari, M., Agosta, G.: Dynamic precision autotuning with TAFFO. ACM TACO 17(2), 1\u201326 (2020)","journal-title":"ACM TACO"},{"issue":"1","key":"6_CR4","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1145\/3093333.3009846","volume":"52","author":"WF Chiang","year":"2017","unstructured":"Chiang, W.F., Baranowski, M., Briggs, I., Solovyev, A., Gopalakrishnan, G., Rakamari\u0107, Z.: Rigorous floating-point mixed-precision tuning. ACM SIGPLAN Not. 52(1), 300\u2013315 (2017)","journal-title":"ACM SIGPLAN Not."},{"key":"6_CR5","doi-asserted-by":"crossref","unstructured":"Chippa, V.K., Chakradhar, S.T., Roy, K., Raghunathan, A.: Analysis and characterization of inherent application resilience for approximate computing. In: DAC (2013)","DOI":"10.1145\/2463209.2488873"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Esmaeilzadeh, H., Sampson, A., Ceze, L., Burger, D.: Neural acceleration for general-purpose approximate programs. In: MICRO. IEEE (2012)","DOI":"10.1109\/MICRO.2012.48"},{"key":"6_CR7","doi-asserted-by":"crossref","unstructured":"Hoste, K., Eeckhout, L.: Comparing benchmarks using key microarchitecture-independent characteristics. In: IISWC. IEEE (2006)","DOI":"10.1109\/IISWC.2006.302732"},{"key":"6_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1007\/978-3-030-57675-2_39","volume-title":"Euro-Par 2020: Parallel Processing","author":"S Lal","year":"2020","unstructured":"Lal, S., et al.: SYCL-bench: a versatile cross-platform benchmark suite for heterogeneous computing. In: Malawski, M., Rzadca, K. (eds.) Euro-Par 2020. LNCS, vol. 12247, pp. 629\u2013644. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-57675-2_39"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Lal, S., Lucas, J., Juurlink, B.: SLC: memory access granularity aware selective lossy compression for GPUs. In: DATE. IEEE (2019)","DOI":"10.23919\/DATE.2019.8714810"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Lashgar, A., Atoofian, E., Baniasadi, A.: Loop perforation in OpenACC. In: ISPA\/IUCC\/BDCloud\/SocialCom\/SustainCom. IEEE (2018)","DOI":"10.1109\/BDCloud.2018.00036"},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Li, S., Park, S., Mahlke, S.: Sculptor: flexible approximation with selective dynamic loop perforation. In: ICS (2018)","DOI":"10.1145\/3205289.3205317"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Maier, D., Cosenza, B., Juurlink, B.: Local memory-aware kernel perforation. In: CGO (2018)","DOI":"10.1145\/3168814"},{"key":"6_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-85665-6_1","volume-title":"Euro-Par 2021: Parallel Processing","author":"D Maier","year":"2021","unstructured":"Maier, D., Cosenza, B., Juurlink, B.: ALONA: automatic loop nest approximation with reconstruction and\u00a0space pruning. In: Sousa, L., Roma, N., Tom\u00e1s, P. (eds.) Euro-Par 2021. LNCS, vol. 12820, pp. 3\u201318. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-85665-6_1"},{"issue":"10","key":"6_CR14","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1145\/2714064.2660231","volume":"49","author":"S Misailovic","year":"2014","unstructured":"Misailovic, S., Carbin, M., Achour, S., Qi, Z., Rinard, M.C.: Chisel: reliability- and accuracy-aware optimization of approximate computational kernels. ACM Sigplan Not. 49(10), 309\u2013328 (2014)","journal-title":"ACM Sigplan Not."},{"key":"6_CR15","doi-asserted-by":"crossref","unstructured":"Mitra, S., Gupta, M.K., Misailovic, S., Bagchi, S.: Phase-aware optimization in approximate computing. In: CGO. IEEE (2017)","DOI":"10.1109\/CGO.2017.7863739"},{"key":"6_CR16","doi-asserted-by":"crossref","unstructured":"Moreau, T., et al.: SNNAP: approximate computing on programmable SOCs via neural acceleration. In: HPCA. IEEE (2015)","DOI":"10.1109\/HPCA.2015.7056066"},{"issue":"6","key":"6_CR17","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1145\/1273442.1250746","volume":"42","author":"N Nethercote","year":"2007","unstructured":"Nethercote, N., Seward, J.: Valgrind: a framework for heavyweight dynamic binary instrumentation. ACM Sigplan Not. 42(6), 89\u2013100 (2007)","journal-title":"ACM Sigplan Not."},{"key":"6_CR18","doi-asserted-by":"crossref","unstructured":"Parasyris, K., et al.: HPC-MixPBench: an HPC benchmark suite for mixed-precision analysis. In: IISWC (2020)","DOI":"10.1109\/IISWC50251.2020.00012"},{"key":"6_CR19","unstructured":"Pouchet, L.N.: PolyBench\/C 3.2. http:\/\/www.cse.ohio-state.edu\/pouchet\/software\/polybench\/"},{"key":"6_CR20","doi-asserted-by":"crossref","unstructured":"Rubio-Gonz\u00e1lez, C., et al.: Precimonious: tuning assistant for floating-point precision. In: SC. IEEE (2013)","DOI":"10.1145\/2503210.2503296"},{"key":"6_CR21","doi-asserted-by":"crossref","unstructured":"Samadi, M., Jamshidi, D.A., Lee, J., Mahlke, S.: Paraprox: pattern-based approximation for data parallel applications. In: ASPLOS (2014)","DOI":"10.1145\/2541940.2541948"},{"key":"6_CR22","unstructured":"Sampson, A., et al.: Accept: a programmer-guided compiler framework for practical approximate computing. University of Washington Technical Report UW-CSE-15-01 (2015)"},{"key":"6_CR23","doi-asserted-by":"crossref","unstructured":"Shafique, M., Ahmad, W., Hafiz, R., Henkel, J.: A low latency generic accuracy configurable adder. In: DAC. IEEE (2015)","DOI":"10.1145\/2744769.2744778"},{"key":"6_CR24","doi-asserted-by":"crossref","unstructured":"Sidiroglou-Douskos, S., Misailovic, S., Hoffmann, H., Rinard, M.: Managing performance vs. ESEC\/FSE, accuracy trade-offs with loop perforation (2011)","DOI":"10.1145\/2025113.2025133"},{"issue":"4","key":"6_CR25","first-page":"60","volume":"38","author":"G Tziantzioulis","year":"2018","unstructured":"Tziantzioulis, G., Hardavellas, N., Campanoni, S.: Temporal approximate function memoization. MICRO 38(4), 60\u201370 (2018)","journal-title":"MICRO"},{"issue":"2","key":"6_CR26","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/MDAT.2016.2630270","volume":"34","author":"A Yazdanbakhsh","year":"2016","unstructured":"Yazdanbakhsh, A., Mahajan, D., Esmaeilzadeh, H., Lotfi-Kamran, P.: AxBench: a multiplatform benchmark suite for approximate computing. IEEE Des. Test 34(2), 60\u201368 (2016)","journal-title":"IEEE Des. Test"}],"container-title":["Lecture Notes in Computer Science","Architecture of Computing Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21867-5_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T11:04:42Z","timestamp":1670929482000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21867-5_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031218668","9783031218675"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21867-5_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"14 December 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ARCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Architecture of Computing Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Heilbronn","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"35","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"arcs2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/arcs-conference.org\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35","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":"18","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":"0","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":"51% - 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":"3,87","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":"3","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}