Addressing Reviewers’ remarks Sample Clauses

Addressing Reviewers’ remarks. The major remark for WP 3 from the reviewers’ comments is the way in which the hardware- mapped algorithms are compared against software implementations in terms of performance. They have remarked that hardware implementation has to be compared against optimum software implementations and this has to be done for the proper datasets. Especially for the datasets from social networks the reviewers have recommended diversity, and not to restrict data sets just from Twitter. Below we describe in more details the reviewers’ remarks, while Table 2 clarifies the actions performed to address main reviewer’s remarks. Reviewers' remark 1: ―When comparing hardware and software implementations make sure that the software baselines used for comparison are state of the art implementations (in terms of efficiency). However, it is likely the case that other algorithms become more appropriate –and efficient- solutions for prediction. We therefore encourage TSI to keep close track of this issue and implement the most promising methods for the task(s) at hand.” In order to address the reviewers’ remarks on D3.2, the WP3 QualiMaster partners have been in closer cooperation with WP5 to select the proper optimum implementations to compare against. For the SVM implementation, the D3.2 presented results are against the well know LibSVM implementation, which is used as a library for several platforms, including Matlab. The Count Min structure integrated with Exponential Histograms (ECM Sketch) was compared against the official software implementation. For Transfer Entropy we compare our own hardware and software implementations against the software presented in [23] which involves the same algorithmic implementation as well as similar time series datasets. Regarding our Mutual Information implementation there is no optimized software implementation for financial or social network data but only for image processing and so we compared the hardware implementations against WP5 implementations. For the Hayashi Yoshida algorithm there was no official distribution or optimized implementation to our knowledge, therefore we compare hardware performance against WP5 distributed software implementation. Reviewers' remark 2: “Evaluations should use larger collections of data. Try to move to evaluation designs with larger collections of data” In cooperation with WP5 the data sets were selected to be representative for the algorithms and the cases that QualiMaster aims to cover. We used both synt...
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Addressing Reviewers’ remarks. The reviewer’s remarks from the 2nd year annual review were focusing on the hardware performance measurements, proposing comparisons against multithread software implementation and use of larger data sets. WP3 partners use the official distribution of software to compare with, and if possible do it with the distributor as in the ECM sketch algorithm. For the Hayashi Yoshida algorithm, comparisons are made with the corresponding multithreaded solution when mapped to distributed platform using the Storm framework. Official distribution of the Mutual Information algorithm is coded in the R-Project, which has inherently low performance. Transfer Entropy as was presented in [4] was implemented in C which proved not to be optimized. For that reason WP3 partners had to rewrite themselves the software in the C programming language, which proved to be 19 times faster than R-Project and 2.5 times faster than the original software for the Transfer Entropy. For this reason, our home-developed highly optimized software was used for performance comparisons. Data sets that are used are real life data from stock exchange markets and were provided by Spring.

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