The integration of graphics processing units (GPUs) on high-end compute nodes has
established a new accelerator-based heterogeneous computing model, which now …

Cloud Computing is an emerging computing paradigm. It shares massively scalable, elastic
resources (eg, data, calculations, and services) transparently among the users over a …

We propose Graviton, an architecture for supporting trusted execution environments on
GPUs. Graviton enables applications to offload security-and performance-sensitive kernels …

Deep Neural Networks (DNNs) have reinvigorated real-world applications that rely on
learning patterns of data and are permeating into different industries and markets. Cloud …

To amortize cost, cloud vendors providing DNN acceleration as a service to end-users
employ consolidation and virtualization to share the underlying resources among multiple …

Studies show that non-graphics programs can be less optimized for the GPU hardware,
leading to significant resource under-utilization. Sharing the GPU among multiple programs …

Modern warehouse-scale computers (WSCs) are being outfitted with accelerators to provide
the significant compute required by emerging intelligent personal assistant (IPA) workloads …

The demand for multitasking on graphics processing units (GPUs) is constantly increasing
as they have become one of the default components on modern computer systems along …

GPUs have become ubiquitous in the cloud due to the dramatic performance gains they
enable in domains such as machine learning and computer vision. However, offloading …

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