Multi-GPUs appear as an attractive platform to speed up data-parallel GPGPU computation. The idea of split-and-merge execution has been introduced to accelerate the parallelism of multiple GPUs even further. However, it has not been explored before how to exploit such an idea for real-time multi-GPU systems properly. This paper presents an open-source real-time multi-GPU scheduling framework, c...

Graphics processors (GPUs) have recently emerged as a powerful co-processor for general-purpose computation. Compared with commodity CPUs, GPUs have an order of magnitude higher computation power as well as memory bandwidth. Moreover, new-generation GPUs allow writes to random memory locations, provide efficient inter-processor communication through on-chip local memory, and support a general-p...

Many embedded systems process huge amount of data that comes from the interaction with the environment. The Graphics Processing Unit (GPU) is a modern embedded solution that tackles the efficiency challenge when processing a lot of data. GPU may improve even more the system performance by allowing multiple activities to be executed in a parallel manner. In a complex component-based application,...

Spatial operations such as spatial join combine two objects on spatial predicates. It is different from relational join because objects have multi dimensions and spatial join consumes large execution time. Recently, many researches tried to find methods to improve the execution time. Parallel spatial join is one method to improve the execution time. Comparison between objects can be done in par...

The finite element method (FEM) with model reduction is widely used to simulate deformable objects. Improving the performance and rendering quality of deformable objects simulated using FEM with model reduction has been a critical problem for several years. As computer technologies rapidly evolve, GPUs have seen significant improvement. It is clear that modern graphics processing units (GPUs) p...