| Full text | |
| Author(s): |
Culquicondor, Aldo
[1]
;
Baldassin, Alexandro
[2]
;
Castelo-Fernandez, Cesar
[3]
;
de Carvalho, Joao P. L.
[3]
;
Papa, Joao Paulo
[4]
Total Authors: 5
|
| Affiliation: | [1] Univ Catolica San Pablo, Arequipa - Peru
[2] UNESP Sao Paulo State Univ, Rio Claro - Brazil
[3] Univ Estadual Campinas, Inst Comp, Campinas - Brazil
[4] UNESP Sao Paulo State Univ, Bauru, SP - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | Neurocomputing; v. 393, p. 259-268, JUN 14 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
In this work, we propose and analyze parallel training algorithms for the Optimum-Path Forest (OPF) classifier. We start with a naive parallelization approach where, following traditional sequential training that considers the supervised OPF, a priority queue is used to store the best samples at each learning iteration. The proposed approach replaces the priority queue with an array and a linear search aiming at using a parallel-friendly data structure. We show that this approach leads to less competition among threads, thus yielding a more temporal and spatial locality. Additionally, we show how the use of vectorization in distance calculations affects the overall speedup and also provide directions on the situations one can benefit from that. The experiments are carried out on five public datasets with a different number of samples and features on architectures with distinct levels of parallelism. On average, the proposed approach provides speedups of up to 11.8 x and 26 x in a 24-core Intel and 64-core AMD processors, respectively. (C) 2019 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 14/16250-9 - On the parameter optimization in machine learning techniques: advances and paradigms |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/19403-6 - Energy-based learning models and their applications |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 17/03940-5 - Interactive Learning of Visual Dictionaries Applied to Image Classification |
| Grantee: | César Christian Castelo Fernández |
| Support Opportunities: | Scholarships in Brazil - Doctorate |