This work develops strategies for adapting a particle-in-cell code to heterogeneous computer architectures and, in particular, to an ARM-based prototype of the Mont-Blanc project using OmpSs programming model and the OpenMP and OpenCL languages.

The aim of this research it to examine the possibility of parallelizing the Frish-Hasslacher-Pomeau (FHP) model, a cellular automata algorithm for modeling fluid flow, on clusters of modern graphics processing units (GPUs). To this end an Open Computing Language (OpenCL) implementation for GPUs was written and compared with a previous, semi-automatic one based on the OpenACC compiler pragmas (S...

The introduction of the GPU (graphics processing units) has marked a revolution in the field of Parallel Computing allowing to achieve computational performance unimaginable until a few years ago. Widely adopted in the Scientific Computing Field, this hardware has proven to be extremely reliable and suitable to simulate Cellular Automata (CA) models for modeling complex systems whose evolution ...

Power constraints are forcing HPC systems to continue to increase hardware concurrency. Efficiently scaling applications on future machines will be essential for improved science and it is recognised that the “flat” MPI model will start to reach its scalability limits. The optimal approach is unknown, necessitating the use of mini-applications to rapidly evaluate new approaches. Reducing MPI ta...

The previous papers of the authors offer approach to building the ordered sequence of image pixels at lossless compression, which comprises methods of cascading fragmentation and the use of bypasses code book. For fragment sized 6*6 the code book contains 22144 various bypasses, the cost of coding to be estimated for every one of them. The search of optimal bypass is an exhaustive search type. ...

Radio propagation simulation tools are important for prediction and verification of the radio signal coverage by individual transmitters or transmitter networks such as mobile phone cellular networks. In the case of a large geographic area with a relative high resolution, the simulation can become computationally demanding, taking a considerable amount of time to accomplish. Parallel processing...

Significantly increasing intra-node parallelism is widely recognised as being a key prerequisite for reaching exascale levels of computational performance. In future exascale systems it is likely that this performance improvement will be realised by increasing the parallelism available in traditional CPU devices and using massively-parallel hardware accelerators. The MPI programming model is st...

We presented our work to design and implement a GPGPU kernel abstraction, which is suitable for developing highly efficient large scale scientific applications using stencil computations on hybrid CPU/GPU systems. By leveraging the MPI-based data parallelism implemented in Cactus, we have developed a CaKernel programming framework in the CUDA/OpenCL architecture to facilitate the development pr...

The recent rise in the popularity of Graphics Processing Units (GPUs) has been fueled by software frameworks, such as NVIDIA’s Compute Unified Device Architecture (CUDA) and Khronos Group’s OpenCL that make GPUs available for general purpose computing. However, CUDA and OpenCL are still lowlevel approaches that require users to handle details about data layout and movement across levels of memo...

Field-programmable gate arrays (FPGAs) have garnered significant interest in research on high-performance computing because their flexibility enables the building of application-specific computation pipelines and data supply systems. In addition to flexibility, toolchains for development FPGAs OpenCL been developed offered by FPGA vendors that reduce programming effort required. However, high l...