RT info:eu-repo/semantics/preprint
T1 Open SYCL on heterogeneous GPU systems: A case of study
A1 Carratalá-Sáez, Rocío
A1 Torres de la Sierra, Yuri
A1 Llanos Ferraris, Diego Rafael
A1 González Escribano, Arturo
A2 ArXiv
K1 Informática
K1 Open SYCL, CUDA, HIP, Finite Time Lyapunov Exponent, Performance evauation, Development effort
K1 1203 Ciencia de Los Ordenadores
K1 3304 Tecnología de Los Ordenadores
AB Computational platforms for high-performance scientic applications are becoming more heterogenous, including hardware accelerators such as multiple GPUs. Applications in a wide variety of scientic elds require an efcient and careful managementof the computational resources of this type of hardware to obtain the best possible performance. However, there are currentlydifferent GPU vendors, architectures and families that can be found in heterogeneous clusters or machines. Programming with thevendor provided languages or frameworks, and optimizing for specic devices, may become cumbersome and compromise portability to other systems. To overcome this problem, several proposals for high-level heterogeneous programming have appeared, trying to reduce the development eort and increase functional and performance portability, specically when using GPU hardware accelerators. This paper evaluates the SYCL programming model, using the Open SYCL compiler, from two different perspectives: The performance it offers when dealing with single or multiple GPU devices from the same or different vendors, and the development effort required to implement the code. We use as case of study the Finite Time Lyapunov Exponent calculation over two real-world scenarios and compare the performance and the development eort of its Open SYCL-based version against the equivalent versions that use CUDA or HIP. Based on the experimental results, we observe that the use of SYCL does not lead to a remarkable overhead in terms of the GPU kernels execution time. In general terms, the Open SYCL development eort for the host code is lower than that observed with CUDA or HIP. Moreover, the SYCL version can take advantage of both CUDA and AMD GPU devices simultaneously much easier than directly using the vendor-specic programming solutions.
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/83868
UL https://uvadoc.uva.es/handle/10324/83868
LA eng
NO Open SYCL on heterogeneous GPU systems: A case of study, Rocío Carratalá-Sáez and Francisco J. andújar and Yuri Torres and Arturo Gonzalez-Escribano and Diego R. Llanos, ArXiv preprint 2310.06947, 2023.
NO Producción Científica
NO Departamento de Informática, Universidad de Valladolid
DS UVaDOC
RD 29-mar-2026