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November 14-17, all open Expo hours
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Researchers and businesses alike have complex computational workloads such as tightly coupled parallel processes or demanding network-bound applications, from genome sequencing to financial modeling. Regardless of the application, one major issue affects them both: procuring and provisioning machines. In typical cluster environments, there is a long queue to access machines, and purchasing dedicated, purpose-built hardware takes time and considerable upfront investment.
With Amazon Web Services, businesses and researchers can easily fulfill their high performance computational requirements with the added benefit of ad-hoc provisioning and pay-as-you-go pricing. The AWS cloud computing platform allows organizations to:
Amazon EC2 provides resizable compute capacity in the cloud with the flexibility to choose from a number of different instance types to meet your computing needs. Each instance provides a predictable amount of dedicated compute capacity and is charged per instance-hour consumed. There are no up-front fees or long-term commitments.
The Amazon EC2 Cluster Compute instance types are specifically designed to combine high compute performance with high performance network capability to meet the needs of HPC applications. Unique to Cluster Compute instances is the ability to group them into clusters of instances for use with HPC applications. This is particularly valuable for those applications that rely on protocols like Message Passing Interface (MPI) for tightly coupled inter-node communication. Cluster instances provide low latency, full bisection 10 Gbps bandwidth between instances, they also provide specific processor architecture in their definition to allow developers to tune their applications and achieve optimal performance.
Cluster Compute Eight Extra Large specifications:
Cluster Compute Quadruple Extra Large specifications:
The Amazon EC2 Cluster GPU instance type adds to the capabilities of the Cluster Compute instance by including two Nvidia Tesla GPUs per instance for very high computing capability using the CUDA or OpenCL programming models.
Cluster GPU Quadruple Extra Large specifications:
Cluster Compute and Cluster GPU instances are available today for Linux operating system use in the US – N. Virginia Region. If you wish to run more than 8 Cluster GPU instances, please complete the Amazon EC2 instance request form. There is no similar limit specific to Cluster Compute instances.
Cluster Compute and Cluster GPU instances require booting from an EBS-backed Amazon Machine Image (AMI) using Hardware Virtual Machine (HVM) virtualization. Information on how to create an HVM AMI and how to launch instances as a cluster can be found in the concepts sections of the Amazon EC2 Developer Guide and User Guide.
“Cluster Compute Instances give MATLAB users the opportunity to test and run their high performance computing problems for data-intensive applications in the cloud at a price and performance level that allows us to continually innovate and meet customer needs.”
– Silvina Grad-Freilich, Senior Manager Parallel-Computing, MathWorks
“For years we’ve helped customers build and manage the world’s most complex large-scale computing clusters, and now with Cluster Compute Instances, customers can leverage Adaptive Computing’s familiar automation software tools to manage HPC resources on Amazon’s leading cloud infrastructure.”
– Michael Jackson, COO and President, Adaptive Computing
“The high-performance networking of Cluster Compute Instances for Amazon EC2 fills an important need among scientific computing professionals, making the on-demand and scalable cloud environment more viable for technical computing”
– David Patterson, co-inventor of RAID, RISC, and several other computer innovations