Deep learning (DL) has demonstrated its remarkable success in a wide variety of fields. The
development of a DL model is a time-consuming and resource-intensive procedure. Hence …

Deep learning (DL) shows its prosperity in a wide variety of fields. The development of a DL
model is a time-consuming and resource-intensive procedure. Hence, dedicated GPU …

Deep Learning (DL) models have achieved superior performance. Meanwhile, computing
hardware like NVIDIA GPUs also demonstrated strong computing scaling trends with 2x …

The development of cloud computing delivery models inspires the emergence of cloud-
native computing. Cloud-native computing, as the most influential development principle for …

Data analysts predict that the GPU as a service (GPUaaS) market will grow to support 3D
models, animated video processing, gaming, and deep learning model training. The main …

Transformer has dominated the field of natural language processing because of its strong
capability in learning from sequential input data. In recent years, various computing and …

Many applications such as autonomous driving and augmented reality, require the
concurrent running of multiple deep neural networks (DNN) that poses different levels of real …

Resource provisioning plays a pivotal role in determining the right amount of infrastructure
resource to run applications and reduce the monetary cost. A significant portion of …

Over the last years, the ever-growing number of Machine Learning (ML) and Artificial
Intelligence (AI) applications deployed in the Cloud has led to high demands on the …

Deep Learning (DL) models have achieved superior performance in many application
domains, including vision, language, medical, commercial ads, entertainment, etc. With the …