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The past several years have witnessed significant performance improvements in High-Performance Computing (HPC), due to the incorporation of GPUs as co-processors. On one hand, GPU devices are growing significantly in terms of the available number of cores and the memory hierarchy; as a result, effective utilization of the available GPU resources while limiting the system power consumption has become...
Morphological operation constitutes one of a powerful and versatile image and video applications applied to a wide range of domains, from object recognition, to feature extraction and to moving objects detection in computer vision where real-time and high-performance are required. However, the throughput of morphological operation is constrained by the convolutional characteristic. In this paper,...
Graphical processing units have been gaining rising attention because of their high performance processing capabilities for many scientific and engineering applications. However, programming such highly parallel devices requires adequate programming tools. Many such programming tools have emerged and hold the promise for high levels of performance. Some of such tools may require specialized parallel...
The High Performance Computing (HPC) field is witnessing the increasing use of Graphics Processing Units (GPUs) as application accelerators, due to their massively data-parallel computing architectures and exceptional floating-point computational capabilities. The performance advantage from GPU-based acceleration is primarily derived for GPU computational kernels that operate on large amount of data,...
Modern Graphic Processing Units (GPUs) are widely used as application accelerators in the High Performance Computing (HPC) field due to their massive floating-point computational capabilities and highly data-parallel computing architecture. Contemporary high performance computers equipped with co-processors such as GPUs primarily execute parallel applications using the Single Program Multiple Data...
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