By Antonio Balzanella, Rosanna Verde (auth.), Joanna Kołodziej, Beniamino Di Martino, Domenico Talia, Kaiqi Xiong (eds.)
This quantity set LNCS 8285 and 8286 constitutes the lawsuits of the thirteenth overseas convention on Algorithms and Architectures for Parallel Processing, ICA3PP 2013, held in Vietri sul Mare, Italy in December 2013. the 1st quantity comprises 10 uncommon and 31 standard papers chosen from ninety submissions and overlaying themes comparable to great facts, multi-core programming and software program instruments, disbursed scheduling and cargo balancing, high-performance medical computing, parallel algorithms, parallel architectures, scalable and allotted databases, dependability in disbursed and parallel platforms, instant and cellular computing. the second one quantity includes 4 sections together with 35 papers from one symposium and 3 workshops held together with ICA3PP 2013 major convention. those are thirteen papers from the 2013 foreign Symposium on Advances of dispensed and Parallel Computing (ADPC 2013), five papers of the overseas Workshop on great information Computing (BDC 2013), 10 papers of the overseas Workshop on relied on info in great info (TIBiDa 2013) in addition to 7 papers belonging to Workshop on Cloud-assisted clever Cyber-Physical platforms (C-Smart CPS 2013).
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Additional info for Algorithms and Architectures for Parallel Processing: 13th International Conference, ICA3PP 2013, Vietri sul Mare, Italy, December 18-20, 2013, Proceedings, Part I
So, based on these results, we expect that using an eﬃcient capture analysis Lightweight Identiﬁcation of Captured Memory 21 technique has a great inﬂuence on the overall performance of the STMBench7 with Deuce. In our work, we propose to make the runtime capture analysis algorithm faster by using the following approach: We label objects with unique identiﬁers of their creating transaction, and then check if the accessing transaction corresponds to that label, in which case we avoid the barriers.
We performed extensive experimental tests for a wide variety of benchmarks (Section 5), including real-world–sized benchmarks that are known for being specially challenging for STMs. The goal of these tests was not only to evaluate the performance of our proposal, but, more importantly, to assess the usefulness of the runtime capture analysis, thus completing the analysis of  about how many of the memory accesses are to captured locations. Besides the STAMP , we also analyze the STMBench7 , and the JWormBench , which were not included in .
Studies in Classiﬁcation, Data Analysis, and Knowledge Organization, pp. 299–317. Springer, Berlin (2004) 10. : La methode des Nuees dynamiques. Revue de Statistique Appliquee 19(2), 19–34 (1971) 11. : Symbolic Data Analysis and the SODAS Software. Wiley (2008) 12. : Probabilistic counting. In: SFCS 1983: Proceedings of the 24th Annual Symposium on Foundations of Computer Science, pp. 76–82. IEEE Computer Society, Washington, DC (1983) 13. : Discretization from Data Streams: applications to Histograms and Data Mining.