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Developing a Plan for Cloud Based GPU Processing


For some applications, cloud based clusters may be limited due to communication and/or storage latency and speeds. With GPUs, however, these issue are not present because application running on cloud GPUs perform exactly the same as those in your local cluster — unless the application span multiple nodes and are sensitive to MPI speeds. For those GPU applications that can work well in the cloud environment, a remote cloud may be an attractive option for both production and feasibility studies.

IBM Storage With OpenStack

IBM Cloud Service

While there is much discussion and products in the market regarding cloud computing and the ability to spin up a virtual machines quickly and efficiently, the fact remains that without planning for cloud based storage, the data will get lost. Simply put, without storage, there is no data.

IBM Cloud Services vs Amazon EC2


High Performance Computing (HPC) in the cloud has become a hot topic with new offerings targeted at this market. The demands of technical computing professional to use the cloud for HPC workloads are different than that of a general enterprise software requirement. Performance is key, which requires a different infrastructure at the cloud providers premises.

Planning for the Convergence of HPC and Big Data

HPC BIGDATA Convergence

As an open source tool designed to navigate large amounts of data, Hadoop continues to find new uses in HPC. Managing a Hadoop cluster is different than managing an HPC cluster, however. It requires mastering some new concepts, but the hardware is basically the same and many Hadoop clusters now include GPUs to facilitate deep learning.

High Performance Cluster Computing Survey

IBM Cloud Service

Moving from a desktop oriented computing environment to a cluster based environment has it challenges for some organizations. However, a number of companies are aware of the benefits and are progressing in the move to a cluster based technical computing system.

IBM Platform Computing Solutions for Life Sciences

Download the IBM Platform Computing Life Sciences White Paper

Massive amounts of computing power and data are needed for effective and efficient processing for many areas that are considered in the Life Science domain. From drug design to genomic sequencing and risk analysis , many workflows require that the tools and processes be in place so that entire organizations are more effective.

Best Practices for Maximizing GPU Resources in HPC Clusters

logos nivida bright computing

HPC developers want to write code and create new applications. The advanced nature of HPC often requires that this process be associated with specific hardware and software environment present on a given HPC resource. Developers want to extract the maximum performance from HPC hardware and at the same time not get mired down in the complexities of software tool chains and dependencies.

Five Reasons To Deploy Cisco UCS Infrastructure


Cisco UCS solutions allow for a faster and more optimized deployment of a computing infrastructure. This solution brief details how the Cisco UCS infrastructure can help your organization become more productive more quickly and can achieve business results without having to be concerned with fitting together various pieces of disparate hardware and software.

Strategies for Managing High Performance GPU Clusters

Managing GPU Clusters Thumb

When discussing GPU accelerators, the focus is often on the price-to-performance benefits to the end user. The true cost of managing and using GPUs goes far beyond the hardware price, however. Understanding and managing these costs helps provide more efficient and productive systems.

Cray XC Series Networking


Creating a large server farm with fast CPUs doesn’t map well to applications that require storage connectivity, as most do, or socket to socket communication within the overall system. Thus, a flexible and high speed networking solution is critical to the overall performance of the computing system.