This executive briefing is a preliminary report of a larger study on demand-side barriers and drivers of cloud computing adoption for HPC. A more comprehensive report and analysis will be published later in 2016. From June to August 2016, the CloudLightning project surveyed over 170 HPC discrete end users worldwide in the academic, commercial and government sectors on their HPC use, perceived drivers and barriers to using cloud computing, and uses of cloud computing for HPC.
Cloud computing is growing and replacing many data centers for High Performance Computing (HPC) applications. However, the movement towards using a cloud infrastructure is not without challenges. This whitepaper discusses many of the challenges in moving from an on-premise HPC solution to using an HPC Cloud Solution.
Clusters that are purchased for specific applications tend not to be flexible as workloads change. What is needed is an infrastructure that can expand or contract as the workload changes. IBM, a recognized leader in High Performance Computing is applying its expertise in both HPC and Cloud computing to bring together the technologies to create the HPC Cloud.
CloudyCluster allows you to quickly set up and configure a cluster on Amazon Web Services (AWS) to handle the most demanding HPC and Big Data tasks. You don’t need access to a data center and you don’t have to be an expert in the ins and outs of running computationally intensive workloads in a cloud environment.
In this video from the Dell booth at SC14, Rich Brueckner from insideHPC moderates a panel discussion on Cloud HPC. Panelists include: Muhammad Atif (NCI), Larry Smarr (UC San Diego), Roger Rintala (Intelligent Light), Boyd Wilson (Clemson University & Omnibond).
Most IaaS (infrastructure as a service) vendors such as Rackspace, Amazon and Savvis use various virtualization technologies to manage the underlying hardware they build their offerings on. Unfortunately the virtualization technologies used vary from vendor to vendor and are sometimes kept secret. Therefore, the question about virtual machines versus physical machines for high performance computing (HPC) applications is germane to any discussion of HPC in the cloud.
In such a demanding and dynamic HPC environment, Cloud Computing technologies, whether deployed as a private cloud or in conjunction with a public cloud, represent a powerful approach to managing technical computing resources. Now, learn how breaking down internal compute silos, by masking underlying HPC complexity to the scientist-clinician researcher user community, and by providing transparency and control to IT managers, cloud computing strategies and tools help organizations of all sizes effectively manage their HPC assets and growing compute workloads that consume them.
As more applications and computing resources move to the cloud, enterprises will become more dependent on cloud vendors, whether the issue is access, hosting, management, or any number of other services. Even in today’s IT environment, cloud consumers want to avoid vendor lock-in—having only one cloud provider. They want to know that they will have visibility into data and systems across multiple platforms and providers.
This article is the third in an editorial series that explores the benefits the HPC community can achieve by adopting HPC virtualization and secure private cloud technologies. Virtualization has been proven to be a viable architectural approach that addresses the many challenges mentioned in last week’s article. This week and next we look at the benefits of creating a virtualized infrastructure.
Make sure you use Cloud services that are designed for HPC applications including high-bandwidth, low-latency networking, exclusive node use, and high performance compute/storage capabilities for your application set. Develop a very flexible and quick Cloud provisioning scheme that mirrors your local systems as much as possible, and is integrated with the existing workload manager. An ideal solution is where your existing cluster can be seamlessly extended into the Cloud and managed/monitored in the same way as local clusters. Read more from the insideHPC Guide to Managing HPC Clusters.