• Genomics Research Workloads that enable researchers to evaluate larger and larger sets of population and genomic data , to accelerate time to market for new treatments and diagnostic routines .
• Financial Risk Modeling Empowers financial organizations to quickly assess risk , empower efficient decision making and ensure compliance with industry regulations .
• Rendering Rapidly scale resources to support the production of special effects for movie production , and empower designers to model products in new and interactive ways .
Azure has invested to ensure specific technologies are available for supporting HPC workloads . These technologies are focused on rapid deployment , high performance and scalability .
Some key capabilities include :
• Hybrid HPC Pack Many HPC users start with hybrid models , then grow to native cloud deployments for all HPC resources . The Hybrid HPC pack from Azure allows a head node to be configured on-premise and then distribute jobs to Azure compute nodes . This model can be used for large workloads to scale very quickly , as well as to minimize cost so that fewer nodes have to be purchased for on-premise use .
• RDMA and MPI Remote Direct Memory Access ( RDMA ) allows very high speed communications between nodes by using lighter weight protocols . Coupling RDMA with the Message Passing Interface ( MPI ) included with the Microsoft HPC Pack enables highly efficient communications between nodes at low latency .
• Azure Resource Manager Resource Manager allows the creation of templates that span multiple Azure services to automate deployment , configuration and monitoring . Resource Manager is a key component of any HPC deployment on Azure that ensures consistency in deployed instances , and monitors for any failed resources that require re-provisioning .
• Future GPU instances Graphics Processing Units ( GPU ) provide very large core count processors for execution of certain workloads in parallel . Many workloads can benefit from GPU acceleration . To assist these workloads , Microsoft has announced the future availability of GPU instances on Azure .
Microsoft has a large set of industry software vendors that sell commercial applications , tested and supported for running on Windows based hosts . These applications are commonly levered in Azure to allow customers to rapidly scale their capacity needs as user demand changes . Azure provides a scalable platform for the execution of HPC workloads , with additional capabilities to ensure automated management and high performance .
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