RT Conference Proceedings
T1 Time Series Heterogeneous Co-execution on CPU+GPU
A1 Romero, José Carlos
A1 González-Navarro, María Ángeles
A1 Rodríguez-Moreno, Andrés
A1 Asenjo-Plaza, Rafael
A1 Cole, Murray
AB Time series motif (similarities) and discords discovery is one of the most important and challenging problems nowadays for time series analytics. We use an algorithm called “scrimp” that excels in collecting the relevant information of time series by reducing the computational complexity of the searching. Starting from the sequential algorithm we develop parallel alternatives based on a variety of scheduling policies that target different computing devices in a system that integrates a CPU multicore and an embedded GPU. These policies are named Dynamic -using Intel TBB- and Static -using C++11 threads- when targeting the CPU, and they are compared to a heterogeneous adaptive approach named LogFit -using Intel TBB and OpenCL- when targeting the co-execution on the CPU and GPU.
YR 2019
FD 2019-07-10
LK https://hdl.handle.net/10630/18005
UL https://hdl.handle.net/10630/18005
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 24 ene 2026