Benchmarking Cloud-HPC Hardware for R&D and Engineering Applications

An IT and HPC Leader’s Guide to Optimizing Their Most Critical Compute-Driven Operations


R&D and engineering teams developing new, more advanced products
are demanding more high-performance computing (HPC) resources to
power their computation-intensive applications. At the same time,
there has been an explosion of specialized HPC hardware in the cloud,
pushing many organizations to explore new ways to deploy new
technologies and techniques for great R&D efficiency and innovation.
While many organizations have a cloud strategy and may have a
preferred cloud service provider (CSP), IT and HPC practitioners face a
new landscape of challenges and opportunities caused by:

– Explosion of specialized HPC hardware options in the cloud

– Broader and more computationally-intensive applications

– Lack of business visibility and control over HPC efficiency

These conditions make it increasingly complex and important for
organizations to optimize their HPC operations to capitalize on their
talent and investments in hardware and software.
In this guide you will learn: How to use a data-driven framework to
capture more value from the latest cloud-HPC technologies. By
benchmarking commonly used computer aided engineering (CAE)
applications you can identify which hardware and software
configurations are best suited for your specific business goals.

In this guide you will learn: How to use a data-driven framework to
capture more value from the latest cloud-HPC technologies. By
benchmarking commonly used computer aided engineering (CAE)
applications you can identify which hardware and software
configurations are best suited for your specific business goals.