The goal of this paper is to give an introduction to analysis of images acquired by a digital
camera with visible illumination and to review its applications as a Process Analytical …

As machine learning (ML) techniques are applied to a widening range of applications, high
throughput ML inference serving has become critical for online services. Such ML inference …

Neural personalized recommendation is the cornerstone of a wide collection of cloud
services and products, constituting significant compute demand of cloud infrastructure. Thus …

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 …

Personalized recommendations are the backbone machine learning (ML) algorithm that
powers several important application domains (eg, ads, e-commerce, etc) serviced from …

A cost-effective multi-tenant neural network execution is becoming one of the most important
design goals for modern neural network accelerators. For example, as emerging AI services …

Emerging AI-enabled applications such as augmented and virtual reality (AR/VR) leverage
multiple deep neural network (DNN) models for various sub-tasks such as object detection …

In many industry scale applications, large and resource consuming machine learning
models reside in powerful cloud servers. At the same time, large amounts of input data are …

The rapid development of deep learning algorithms, as well as innovative hardware
advancements, encourages multi-DNN workloads such as augmented reality applications …

While user-facing services experience diurnal load patterns, co-locating services improve
hardware utilization. Prior work on co-locating services on GPUs run queries sequentially …