Running applications on a hybrid cluster

A.V. Bogdanov, I.G. Gankevich, V.Yu. Gayduchok, N.V. Yuzhanin

Результат исследований: Научные публикации в периодических изданияхстатья


A hybrid cluster implies the use of computational devices with radically different architectures. Usually, these are conventional CPU architecture (e.g. x86_64) and GPU architecture (e. g. NVIDIA CUDA). Creating and exploiting such a cluster requires some experience: in order to harness all computational power of the described system and get substantial speedup for computational tasks many factors should be taken into account. These factors consist of hardware characteristics (e.g. network infrastructure, a type of data storage, GPU architecture) as well as software stack (e.g. MPI implementation, GPGPU libraries). So, in order to run scientific applications GPU capabilities, software features, task size and other factors should be considered. This report discusses opportunities and problems of hybrid computations. Some statistics from tests programs and applications runs will be demonstrated. The main focus of interest is open source applications (e. g. OpenFOAM) that support GPGPU (with some parts rewritte
Язык оригиналане определен
Страницы (с-по)475-483
Номер выпуска3
СостояниеОпубликовано - 2015