It’s a different kind of computing world out there. The demand for more compute performance for applications used by engineering, risk modeling, or life sciences is relentless. So, how are you keeping up with modern HPC demands? Meet Apollo – creating next-gen HPC and super-computing.
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.
Learn how a system built on Cisco UCS using Bright Cluster Manager is a complete HPC Ethernet solution that frees the IT manager, administrator, and users to focus on HPC results instead of managing a complex collection of hardware and software.
Tighter budgets and a stricter regulatory climate are dictating the need for smaller product envelopes and new material choices. Engineers are tasked with these demands against a backdrop of fewer resources and shrinking time-to-market cycles. Now, you’ll learn how advanced simulation software can dramatically shorten the design phase by allowing engineers to virtually optimize and validate new ideas earlier in the process, minimizing the expense of building physical prototypes and streamlining real-world testing.
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.
Engineers are being asked to do more in less time to meet ever-tightening time-to-market schedules. To do so, they need to accelerate design by making use of advanced engineering software. However, such software requires computing processing power not available in a typical engineering workstation. Learn how a cluster can deliver aggregated computing power from its many processors with many cores to meet the processing demands of more complex engineering software, and therefore deliver results faster than individual workstations.
IBM Platform Computing products can save an organizations money by reducing a variety of direct costs associated with grid and cluster computing. Your organization can slow the rate of infrastructure growth and reduce the costs of management, support, personnel and training—while also avoiding hidden or unexpected costs.
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.
Life sciences, finance, government and numerous other organizations are relying on their HPC clusters for their daily operations. But how can you powerfully scale this type of environment? Learn how cloud services offer you dynamic control over both workloads and resources.
If you work with big data in the cloud or deal with structured and unstructured data for analytics, you need software defined storage. Software defined storage uses standard compute, network, and storage hardware; the storage functions are all done in software.