RT Conference Proceedings
T1 Efficient OpenCL-based concurrent tasks offloading on accelerators
A1 Lázaro-Muñoz, Antonio J.
A1 González-Linares, José María
A1 Gómez-Luna, Juan
A1 Guil-Mata, Nicolás
K1 Computación heterogénea
AB Current heterogeneous platforms with CPUs and accelerators have the ability to launch several independent tasks simultaneously, in order to exploit concurrency among them. These tasks typically consist of data transfer commands and kernel computation commands. In this paper we develop a runtime approach to optimize the concurrency between data transfers and kernel computation commands in a multithreaded scenario where each CPU thread offloads tasks to the accelerator. It deploys a heuristic based on a temporal execution model for concurrent tasks. It is able to establish a near-optimal task execution order that significantly reduces the total execution time, including data transfers. Our approach has been evaluated employing five different benchmarks composed of dominant kernel and dominant transfer real tasks. In these experiments our heuristic achieves speedups up to 1.5x in AMD R9 and NVIDIA K20c accelerators and 1.3x in an Intel Xeon Phi (KNC) device.
PB Procedia Computer Science
YR 2017
FD 2017
LK http://hdl.handle.net/10630/13908
UL http://hdl.handle.net/10630/13908
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026