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 includes 10 special and 31 average papers chosen from ninety submissions and masking subject matters comparable to massive facts, multi-core programming and software program instruments, allotted scheduling and cargo balancing, high-performance clinical computing, parallel algorithms, parallel architectures, scalable and disbursed databases, dependability in disbursed and parallel structures, instant and cellular computing. the second one quantity contains 4 sections together with 35 papers from one symposium and 3 workshops held along side ICA3PP 2013 major convention. those are thirteen papers from the 2013 overseas Symposium on Advances of dispensed and Parallel Computing (ADPC 2013), five papers of the overseas Workshop on mammoth facts Computing (BDC 2013), 10 papers of the overseas Workshop on depended on info in titanic facts (TIBiDa 2013) in addition to 7 papers belonging to Workshop on Cloud-assisted shrewdpermanent Cyber-Physical structures (C-Smart CPS 2013).
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Extra resources 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 have chose three datasets in the evaluation process: The ﬁrst is made by 76 highly evolving time series, downloaded from Yahoo ﬁnance where the observations are the daily closing price of several random chosen stocks. Each time series is made by 4000 observations. The second is made by 179 highly evolving time series which collect daily electricity supply at several locations in Australia. Each time series is made by 3288 observations. The third is a simulated dataset consisting in n = 100 time series each having 6, 000 observations.
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. In: Proceedings of the 2006 ACM Symposium on Applied Computing, pp. 662–667 (2006) 14. : Knowledge discovery from sensor data. CRC Press (2009) 14 A. Balzanella and R. Verde 15. : Space-eﬃcient online computation of quantile summaries. SIGMOD Rec. 30(2), 58–66 (2001) 16.
Algorithms and Architectures for Parallel Processing: 13th International Conference, ICA3PP 2013, Vietri sul Mare, Italy, December 18-20, 2013, Proceedings, Part I by Antonio Balzanella, Rosanna Verde (auth.), Joanna Kołodziej, Beniamino Di Martino, Domenico Talia, Kaiqi Xiong (eds.)