Özdal, Muhammet MustafaYeşil, ŞerifKim, T.Ayupov, A.Burns, S.Öztürk, Özcan2018-04-122018-04-122015-11http://hdl.handle.net/11693/37735Date of Conference: 2-6 Nov. 2015Conference name: IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2015Intelligent data analysis has become more important in the last decade especially because of the significant increase in the size and availability of data. In this paper, we focus on the common execution models and characteristics of iterative graph analytics applications. We show that the features that improve work efficiency can lead to significant overheads on existing systems. We identify the opportunities for custom hardware implementation, and outline the desired architectural features for energy efficient computation of graph analytics applications. © 2015 IEEE.EnglishThroughputHardwareConvergenceMeasurementBenchmark testingColorComputational modelingData analysisGraph theoryConference Paper10.1109/ICCAD.2015.7372635