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 …

Guaranteeing Quality-of-Service (QoS) of latency-sensitive applications while improving
server utilization through application co-location is important yet challenging in modern …

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

As technology scales, GPUs are forecasted to incorporate an ever-increasing amount of
computing resources to support thread-level parallelism. But even with the best effort …

Graphics Processing Units (GPUs) exploit large amounts of threadlevel parallelism to
provide high instruction throughput and to efficiently hide long-latency stalls. The resulting …

Modern GPUs are broadly adopted in many multitasking environments, including data
centers and smartphones. However, the current support for the scheduling of multiple GPU …

As graphics processing units (GPUs) are broadly adopted, running multiple applications on
a GPU at the same time is beginning to attract wide attention. Recent proposals on …

Network Function Virtualization (NFV) virtualizes software network functions to offer flexibility
in their design, management and deployment. Although GPUs have demonstrated their …

This paper introduces a new resource virtualization framework, Zorua, that decouples the
programmer-specified resource usage of a GPU application from the actual allocation in the …