2015
Authors
Rodrigues, A; Silva, C; Borges, P; Silva, S; Dutra, I;
Publication
2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY)
Abstract
Statistical data analysis methods are well known for their difficulty in handling large number of instances or large number of parameters. This is most noticeable in the presence of "big data", i.e., of data that are heterogeneous, and come from several sources, which makes their volume increase very rapidly. In this paper, we study popular and well-known statistical functions generally applied to data analysis, and assess their performance using our own implementation (DataIP) 1, MatLab and R. We show that DataIP outperforms MatLab and R by several orders of magnitude and that the design and implementation of these functions need to be rethought to adapt to today's data challenges.
2015
Authors
Rodrigues, AV; Jorge, A; Dutra, I;
Publication
30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, VOLS I AND II
Abstract
We describe GPU implementations of the matrix recommender algorithms CCD++ and ALS. We compare the processing time and predictive ability of the GPU implementations with existing multi- core versions of the same algorithms. Results on the GPU are better than the results of the multi- core versions (maximum speedup of 14.8).
2015
Authors
Rodrigues, AV; Jorge, A; Dutra, I;
Publication
CoRR
Abstract
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