{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T12:09:48Z","timestamp":1725970188786},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319776095"},{"type":"electronic","value":"9783319776101"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","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":[[2018]]},"DOI":"10.1007\/978-3-319-77610-1_22","type":"book-chapter","created":{"date-parts":[[2018,3,7]],"date-time":"2018-03-07T02:32:50Z","timestamp":1520389970000},"page":"297-310","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Do Iterative Solvers Benefit from Approximate Computing? An Evaluation Study Considering Orthogonal Approximation Methods"],"prefix":"10.1007","author":[{"given":"Michael","family":"Bromberger","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markus","family":"Hoffmann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robin","family":"Rehrmann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,3,8]]},"reference":[{"key":"22_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1007\/978-3-662-48096-0_50","volume-title":"Euro-Par 2015: Parallel Processing","author":"H Anzt","year":"2015","unstructured":"Anzt, H., Chow, E., Dongarra, J.: Iterative sparse triangular solves for preconditioning. In: Tr\u00e4ff, J.L., Hunold, S., Versaci, F. (eds.) Euro-Par 2015. LNCS, vol. 9233, pp. 650\u2013661. Springer, Heidelberg (2015). https:\/\/doi.org\/10.1007\/978-3-662-48096-0_50"},{"key":"22_CR2","doi-asserted-by":"crossref","unstructured":"Anzt, H., Dongarra, J., Quintana-Ort\u00ed, E.S.: Adaptive precision solvers for sparse linear systems. In: Proceedings of the 3rd International Workshop on Energy Efficient Supercomputing, p. 2. ACM (2015)","DOI":"10.1145\/2834800.2834802"},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"Baek, W., Chilimbi, T.: Green: a framework for supporting energy-conscious programming using controlled approximation. In: ACM SIGPLAN Conference on Programming Language Design and Implementation (2010)","DOI":"10.1145\/1806596.1806620"},{"key":"22_CR4","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1137\/1037008","volume":"37","author":"R Bagnara","year":"1995","unstructured":"Bagnara, R.: A unified proof for the convergence of Jacobi and Gauss Seidel methods. SIAM Rev. 37, 93\u201397 (1995)","journal-title":"SIAM Rev."},{"key":"22_CR5","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1006\/jcph.2002.7176","volume":"182","author":"M Benzi","year":"2002","unstructured":"Benzi, M.: Preconditioning techniques for large linear systems: a survey. J. Comput. Phys. 182, 418\u2013477 (2002)","journal-title":"J. Comput. Phys."},{"key":"22_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/978-3-319-30695-7_18","volume-title":"Architecture of Computing Systems \u2013 ARCS 2016","author":"M Bromberger","year":"2016","unstructured":"Bromberger, M., Heuveline, V., Karl, W.: Reducing energy consumption of data transfers using runtime data type conversion. In: Hannig, F., Cardoso, J.M.P., Pionteck, T., Fey, D., Schr\u00f6der-Preikschat, W., Teich, J. (eds.) ARCS 2016. LNCS, vol. 9637, pp. 239\u2013250. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-30695-7_18"},{"key":"22_CR7","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/0024-3795(69)90028-7","volume":"2","author":"D Chazan","year":"1969","unstructured":"Chazan, D., Miranker, W.: Chaotic relaxation. Linear Algebra Appl. 2, 199\u2013222 (1969)","journal-title":"Linear Algebra Appl."},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Chippa, V., Chakradhar, S., Roy, K., Raghunathan, A.: Analysis and characterization of inherent application resilience for approximate computing. In: Proceedings of the 50th Annual Design Automation Conference, DAC 2013, pp. 113:1\u2013113:9. ACM, New York (2013)","DOI":"10.1145\/2463209.2488873"},{"key":"22_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88706-5","volume-title":"Partial Differential Equations with Numerical Methods","author":"S Larsson","year":"2003","unstructured":"Larsson, S., Thomee, V.: Partial Differential Equations with Numerical Methods. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-3-540-88706-5"},{"issue":"4","key":"22_CR10","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1145\/2248487.1950391","volume":"47","author":"S Liu","year":"2012","unstructured":"Liu, S., Pattabiraman, K., Moscibroda, T., Zorn, B.G.: Flikker: saving DRAM refresh-power through critical data partitioning. ACM SIGPLAN Not. 47(4), 213\u2013224 (2012)","journal-title":"ACM SIGPLAN Not."},{"key":"22_CR11","first-page":"62:1","volume":"48","author":"S Mittal","year":"2016","unstructured":"Mittal, S.: A survey of techniques for approximate computing. ACM Comput. Surv. (CSUR) 48, 62:1\u201362:33 (2016)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"2","key":"22_CR12","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1109\/TVLSI.2016.2586379","volume":"25","author":"A Raha","year":"2017","unstructured":"Raha, A., Venkataramani, S., Raghunathan, V., Raghunathan, A.: Energy-efficient reduce-and-rank using input-adaptive approximations. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 25(2), 462\u2013475 (2017)","journal-title":"IEEE Trans. Very Large Scale Integr. (VLSI) Syst."},{"key":"22_CR13","doi-asserted-by":"crossref","unstructured":"Renganarayana, L., Srinivasan, V., Nair, R., Prener, D.: Programming with relaxed synchronization. In: Proceedings of the 2012 ACM Workshop on Relaxing Synchronization for Multicore and Manycore Scalability, pp. 41\u201350. ACM (2012)","DOI":"10.1145\/2414729.2414737"},{"key":"22_CR14","volume-title":"Iterative Methods for Sparse Linear Systems","author":"Y Saad","year":"1996","unstructured":"Saad, Y.: Iterative Methods for Sparse Linear Systems. PWS, Boston (1996)"},{"key":"22_CR15","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1145\/2654822.2541948","volume":"42","author":"M Samadi","year":"2014","unstructured":"Samadi, M., Jamshidi, D.A., Lee, J., Mahlke, S.: Paraprox: pattern-based approximation for data parallel applications. ACM SIGARCH Comput. Archit. News 42, 35\u201350 (2014)","journal-title":"ACM SIGARCH Comput. Archit. News"},{"key":"22_CR16","doi-asserted-by":"crossref","unstructured":"Samadi, M., Lee, J., Jamshidi, D.A., Hormati, A., Mahlke, S.: SAGE: self-tuning approximation for graphics engines. In: Proceedings of the 46th Annual IEEE\/ACM International Symposium on Microarchitecture, pp. 13\u201324. ACM (2013)","DOI":"10.1145\/2540708.2540711"},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Schaffner, M., Gurkaynak, F.K., Smolic, A., Kaeslin, H., Benini, L.: An approximate computing technique for reducing the complexity of a direct-solver for sparse linear systems in real-time video processing. In: 2014 51st ACM\/EDAC\/IEEE Design Automation Conference (DAC), pp. 1\u20136. IEEE (2014)","DOI":"10.1145\/2593069.2593082"},{"key":"22_CR18","doi-asserted-by":"crossref","unstructured":"Sch\u00f6ll, A., Braun, C., Wunderlich, H.J.: Applying efficient fault tolerance to enable the preconditioned conjugate gradient solver on approximate computing hardware. In: 2016 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), pp. 21\u201326. IEEE (2016)","DOI":"10.1109\/DFT.2016.7684063"},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Sch\u00f6ll, A., Braun, C., Wunderlich, H.J.: Energy-efficient and error-resilient iterative solvers for approximate computing. In: Proceedings of the 23rd IEEE International Symposium on On-Line Testing and Robust System Design (IOLTS 2017), pp. 237\u2013239 (2017)","DOI":"10.1109\/IOLTS.2017.8046244"},{"key":"22_CR20","unstructured":"Shewchuk, J.R.: An Introduction to the Conjugate Gradient Method Without the Agonizing Pain. School of Computer Science, Carnegie Mellon University, Pittsburgh, August 1994"},{"key":"22_CR21","doi-asserted-by":"crossref","unstructured":"Sidiroglou-Douskos, S., Misailovic, S., Hoffmann, H., Rinard, M.: Managing performance vs. accuracy trade-offs with loop perforation. In: Proceedings of the 19th ACM SIGSOFT Symposium and the 13th European Conference on Foundations of Software Engineering, ESEC\/FSE 2011, pp. 124\u2013134. ACM, New York (2011)","DOI":"10.1145\/2025113.2025133"},{"key":"22_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Tian, Y., Wang, T., Yuan, F., Xu, Q.: Approxeigen: an approximate computing technique for large-scale eigen-decomposition. In: Proceedings of the IEEE\/ACM International Conference on Computer-Aided Design, pp. 824\u2013830. IEEE Press (2015)","DOI":"10.1109\/ICCAD.2015.7372656"},{"key":"22_CR23","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Yuan, F., Ye, R., Xu, Q.: Approxit: an approximate computing framework for iterative methods. In: Proceedings of the 51st Annual Design Automation Conference, pp. 1\u20136. ACM (2014)","DOI":"10.1145\/2593069.2593092"}],"container-title":["Lecture Notes in Computer Science","Architecture of Computing Systems \u2013 ARCS 2018"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-77610-1_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T21:55:17Z","timestamp":1603922117000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-77610-1_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319776095","9783319776101"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-77610-1_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}