Stencil computation is one of the most important kernels in many application domains such
as image processing, solving partial differential equations, and cellular automata. Many of …

Aiming at the current problems that most physical hosts in the cloud data center are so
overloaded that it makes the whole cloud data center'load imbalanced and that existing load …

Many research works have recently experimented with GPU to accelerate packet processing
in network applications. Most works have shown that GPU brings a significant performance …

Many high-performance computing applications solving partial differential equations (PDEs)
can be attributed to the class of kernels using stencils on structured grids. Due to the …

Graphics processing units (GPUs) provide orders-of-magnitude speedup for compute-
intensive data-parallel applications. However, enterprise and cloud computing domains …

Uncertainties from sampling biases present challenges to ecologists and evolutionary
biologists in understanding species sensitivity to anthropogenic climate change. Here, we …

Scaling CNN training is necessary to keep up with growing datasets and reduce training
time. We also see an emerging need to handle datasets with very large samples, where …

Designing high-performance and scalable applications on GPU clusters requires tackling
several challenges. The key challenge is the separate host memory and device memory …

Stencil computation is an important class of algorithms used in a large variety of scientific-
simulation applications. While the code for many problems can certainly be written in a …

The importance of stencil-based algorithms in computational science has focused attention
on optimized parallel implementations for multilevel cache-based processors. Temporal …