Due to recent advances in digital technologies, and availability of credible data, an area of
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …

In this article, we survey existing academic and commercial efforts to provide Field-
Programmable Gate Array (FPGA) acceleration in datacenters and the cloud. The goal is a …

Cloud services have recently started undergoing a major shift from monolithic applications,
to graphs of hundreds or thousands of loosely-coupled microservices. Microservices …

Interactive AI-powered services require low-latency evaluation of deep neural network
(DNN) models-aka"" real-time AI"". The growing demand for computationally expensive …

Modern cloud architectures rely on each server running its own networking stack to
implement policies such as tunneling for virtual networks, security, and load balancing …

The monolithic server model where a server is the unit of deployment, operation, and failure
is meeting its limits in the face of several recent hardware and application trends. To improve …

A number of recent efforts have attempted to design accelerators for popular machine
learning algorithms, such as those involving convolutional and deep neural networks (CNNs …

Developing Field-programmable Gate Array (FPGA) architectures is challenging due to the
competing requirements of various application domains and changing manufacturing …

Deep learning models with convolutional and recurrent networks are now ubiquitous and
analyze massive amounts of audio, image, video, text and graph data, with applications in …

The NVIDIA Volta GPU microarchitecture introduces a specialized unit, called Tensor Core
that performs one matrix-multiply-and-accumulate on 4x4 matrices per clock cycle. The …