RT Journal Article T1 Assessing Intel OneAPI capabilities and cloud-performance for heterogeneous computing A1 Rodríguez Alcaraz, Silvia A1 Laso Rodríguez, Rubén A1 García Lorenzo, Óscar A1 López Vilariño, David A1 Fernández Pena, Anselmo Tomás A1 Fernández Rivera, Francisco K1 Intel OneAPI  K1 Intel DevCloud  K1 GPU  K1 FPGA  K1 Heterogeneous computing K1 Cloud computing AB This work presents a performance-oriented study of a heterogeneous application developed with Intel OneAPI to solve two well-known diffusion problems: heat diffusion and image denoising. We have explored CPU+iGPU and CPU+FPGA schemes, applying dynamic load balancing and conducting experiments on Intel DevCloud. The results demonstrate that the CPU+iGPU scheme outperforms the execution times achieved by the fastest device when the problem is sufficiently computationally demanding. We also found that the performance of the CPU+FPGA scheme is heavily affected by bandwidth limitations and specific strategies to manage memory efficiently are required. Moreover, it was demonstrated that dynamic workload balancing is crucial due to possible performance fluctuations in any of the implicated devices. In conclusion, Intel OneAPI provides a helpful tool for multi-platform development using a unique high-level language, DPC++. However, developing specific code for each platform is necessary to achieve optimal performance PB Springer SN 0920-8542 YR 2024 FD 2024 LK http://hdl.handle.net/10347/33803 UL http://hdl.handle.net/10347/33803 LA eng NO This work has received financial support from the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation ED431C 2022/16 and accreditation ED431G-2019/04) and the European Regional Development Fund (ERDF), which acknowledges the CiTIUS-Research Center in Intelligent Technologies of the University of Santiago de Compostela as a Research Center of the Galician University System. This work was also supported by the Ministry of Economy and Competitiveness, Government of Spain (Grants Nos. 28700 PID2019-104834GB-I00 and PID2022-141623NB-I00). Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature DS Minerva RD 27 abr 2026