International Business Machines Corporation

Lenovo (singapore) Pte. Ltd.

Luigi Brochard

Rajendra D Panda

Robert H Bell, Jr

Donald R DeSota

Francois Thomas

Venkat Rajeev Indukuru

Sameh Sherif Sharkawi

A method, system, and computer program product for processing an application in a high performance computing (HPC) data center are described. The method includes analyzing and sorting a plurality of nodes in a cluster of the HPC data center into a plurality of frequency bins, each of the plurality of nodes being sorted into more than one of the plurality of frequency bins based on performance. The method also includes analyzing and sorting the application into an application bin among a plurality of application bins based on a frequency scaling characteristic of the application. The method further includes selecting a first set of nodes among the plurality of nodes to process the application, the first set of nodes being sorted into a first frequency bin among the plurality of frequency bins corresponding with the application bin of the application.

Performance-aware job scheduling under power constraints

A performance projection system includes a test IHS and a currently existing IHS. The performance projection system includes surrogate programs and user application software. The test IHS employs a memory that includes a virtual future IHS, currently existing IHS, surrogate programs, and user application software for determination of runtime and HW counter performance data. The user application software and surrogate programs execute on the currently existing MS to provide designers with runtime data and HW counter or microarchitecture dependent data. Designers execute surrogate programs on the future IHS to provide runtime and HW counter data. Designers normalize and weight the runtime and HW counter data to provide a representative surrogate program for comparison to user application software performance on the future IHS. Using a scaling factor, designers may generate a projection of runtime performance for the user application software executing on the future IHS.

Workload performance projection for future information handling systems using microarchitecture dependent data

A job scheduler can select a processor core operating frequency for a node in a cluster to perform a job based on energy usage and performance data. After a job request is received, an energy aware job scheduler accesses data that specifies energy usage and job performance metrics that correspond to the requested job and a plurality of processor core operating frequencies. A first of the plurality of processor core operating frequencies is selected that satisfies an energy usage criterion for performing the job based, at least in part, on the data that specifies energy usage and job performance metrics that correspond to the job. The job is assigned to be performed by a node in the cluster at the selected first of the plurality of processor core operating frequencies.

Energy-aware job scheduling for cluster environments

A performance projection system includes a test IHS and multiple currently existing IHSs. The performance projection system includes user application software and surrogate programs that execute on currently existing IHSs. The performance projection system measures user application software and surrogate program performance during execution on currently existing IHSs. The performance projection systems measures runtime program performance during execution of surrogate programs on a future semiconductor die IC design model or virtualized future system. Designers normalize and compare surrogate program runtime performance data with user application software performance data. Designers un-normalize the normalized runtime performance data to generate a projection of runtime performance on the future system.

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Paris, France

Luigi Brochard