Heterogeneous Data Center Architectures: Software and Hardware Integration and Orchestration Aspects

Authored by: A. Scionti , F. Lubrano , O. Terzo , S. Mazumdar

Heterogeneous Computing Architectures

Print publication date:  September  2019
Online publication date:  September  2019

Print ISBN: 9780367023447
eBook ISBN: 9780429399602
Adobe ISBN:


 Download Chapter



Machine learning (ML) and deep learning (DL) algorithms are emerging as the new driving force for the computer architecture evolution. With an ever large adoption of ML/DL techniques in Cloud and high-performance computing (HPC) domains, several new architectures (spanning from chips to entire distributed systems) have been pushed on the market to better support applications based on ML/DL algorithms. While HPC and Cloud remained for long time distinguished domains with their own challenges, an ever large number of new applications is pushing for their rapid convergence. In this context, many accelerators (GP-GPUs, FPGAs) and customised ASICs (e.g., Google TPUs, Intel Neural Network Processor – NNP) with dedicated functionalities have been proposed, further enlarging the data center heterogeneity landscape. Supporting such large (at scale) heterogeneity demands for an adequate software environment (orchestration tool) able to maximise flexibility, productivity and extract maximum performance from the underlying hardware. To this end, first, a comprehensive vision on current state-of-the-art hardware and software heterogeneity, covering the whole spectrum of a modern Cloud/HPC system architecture is given. Then, ECRAE is presented, i.e., an orchestration solution devised to explicitly deal with heterogeneous devices deployed at scale.

Search for more...
Back to top

Use of cookies on this website

We are using cookies to provide statistics that help us give you the best experience of our site. You can find out more in our Privacy Policy. By continuing to use the site you are agreeing to our use of cookies.