There has been a growing interest in exploiting contextual information in addition to local
features to detect and localize multiple object categories in an image. Context models can …

GPUs are being increasingly adopted as compute accelerators in many domains, spanning
environments from mobile systems to cloud computing. These systems are usually running …

Each new generation of GPUs vastly increases the resources available to GPGPU
programs. GPU programming models (like CUDA) were designed to scale to use these …

Graphics processing units (GPUs) have become a very powerful platform embracing a
concept of heterogeneous many-core computing. However, application domains of GPUs …

We present Heimdall, a mobile GPU coordination platform for emerging Augmented Reality
(AR) applications. Future AR apps impose an explored challenging workload: i) concurrent …

The computational power provided by many-core graphics processing units (GPUs) has
been exploited in many applications. The programming techniques currently employed on …

Graphics processors, or GPUs, have recently been widely used as accelerators in shared
environments such as clusters and clouds. In such shared environments, many kernels are …

Driven by the emergence of GPUs as a major player in high performance computing and the
rapidly growing popularity of cloud environments, GPU instances are now being offered by …

General-purpose computing on graphics processing units, also known as GPGPU, is a
burgeoning technique to enhance the computation of parallel programs. Applying this …

As one of the most popular accelerators, Graphics Processing Unit (GPU) has demonstrated
high computing power in several application fields. On the other hand, GPU also produces …