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

This paper introduces a platform to support serverless computing for scalable event-driven
data processing that features a multi-level elasticity approach combined with virtualization of …

Graphics processing units (GPUs) are being adopted in many computing facilities given their
extraordinary computing power, which makes it possible to accelerate many general …

In modern virtual computing environment, the 2D/3D rendering performance and parallel
computing potential of GPU (graphics processing unit) must be fully exploited for multiple …

This paper introduces gMig, an open-source and practical GPU live migration solution for full
virtualization. By taking advantage of the dirty pattern of GPU workloads, gMig presents the …

The increasing demand for machine learning computation contributes to the convergence of
high-performance computing and cloud computing, in which the virtualization of Graphics …

Graphics processing units (GPUs) are currently used in data centers to reduce the execution
time of compute‐intensive applications. However, the use of GPUs presents several side …

This paper introduces gMig, an open-source and practical vGPU live migration solution for
full virtualization. Taking the advantage of the dirty pattern of GPU workloads, gMig presents …

The cloud model allows the access to a vast amount of computational resources, alleviating
the need for acquisition and maintenance costs on a pay-per-use basis. However, other …

Nowadays, many data centers use virtual machines (VMs) in order to achieve a more
efficient use of hardware resources. The use of VMs provides a reduction in equipment and …