International Business Machines Corporation

Peter Bergersen Yocom

Catherine Krueger Eilert

Yuk Lung Chan

Andrew P Wack

Jeffrey Mark Nick

Jeffrey Paul Kubala

Gary M King

Dale Francis Riedy, Jr

Anthony Thomas Sofia

Jeffrey David Aman

John Alan Bivens

William J Rooney

Scott Brady Compton

Yuksel Gunal

Mariann Devine

Harry M Yudenfriend

Jeffrey Alan Frey

Hiren Ramlal Shah

John Elliott Arwe

Xiao Liang Hu

Donna N Dillenberger

Scot MacLellan

Mathew S Thoennes

Michael E Baskey

Joerg-Stephan Vogt

Danny R Sutherland

Frank Haverkamp

Joseph M Gdaniec

Thomas Fuchs

Friedemann Baitinger

Reiner Rieke

Hartmut Droege

Yong Feng

Gunnar Von Boehn

David Vincent Bostjancic

Michael Ruettger

Malcolm Scott Ware

Wei T Huang

Elpida Tzortzatos

K Paul Muller

Roy Frank Brabson

Guillermo Jesus Silva

Lap Thiet Huynh

Paul Miller Bird

Harris M Morgenstern

Daniel J Kearney

Emmanuel Yashchin

Joseph L Temple, Iii

Bernard R Pierce

Robert R Rogers

Charles E Mari

Donna N Eng Dillenberger

Scott J Hadderman

Robert Vaupel

David Andrew Booz

Roman Anthony Bobak

Richard Cwiakala

Mark Francis Hulber

Francis E Johnson

Guenter Vater

David C Manners

Matthew S Thoennes

Gregory M Dritschler

Francis Wong

Daniel A Kaberon

Greg M Dritschler

Ulrich Hild

Jim H Mulder

Joseph Iii Temple

Catherine Eilert

Examples of techniques for service level management of a workload defined environment are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include: collecting runtime workload data for a workload executing on a processing system; collecting performance data for the workload within a container; performing, by a processing device, a determination of whether the runtime workload data satisfies the goal set forth in the service level agreement; providing data from within the container in a format utilized by an application program interface; and accessing the data from within the container through the application program interface from outside of the container.

Service level management of a workload defined environment

Examples of techniques for reprogramming a field programmable device on demand are disclosed. According to aspects of the present disclosure, a computer-implemented method may include: identifying a first field programmable device as being over utilized; responsive to identifying the first field programmable device that is over utilized, identifying a second field programmable device that is underutilized; determining whether to reprogram the second field programmable device; responsive to determining to reconfigure the second field programmable device, stopping the second field programmable device from performing a workload; moving the workload to another field programmable device configured to perform the workload; and reprogramming the second field programmable device.

Reprogramming a field programmable device on-demand

A method, system, and computer program product are described for a machine selecting a selected adapter among two or more adapters that perform a same function. The method includes generating a request, at the machine, for the function, and calculating a time indicator associated with each of the two or more adapters based on a respective adapter queue time factor (QTF) associated with each of the two or more adapters, the adapter QTF associated with each of the two or more adapters being a computed value. The method also includes selecting the selected adapter and submitting one or more requests to the selected adapter of the two or more adapters to perform the function based on a comparison of the time indicator associated with each of the two or more adapters.

Adapter selection based on a queue time factor

Embodiments include a technique for predictive virtual server scheduling and optimization of dynamic consumable resources to achieve priority-based workload performance objectives is provided. Techniques include calculating a capacity requirement for each virtual server based on an administrator defined performance objective for each virtual server. Techniques also include calculating an available CPU capacity for each importance level based on the calculated capacity requirement for each virtual server, sending the calculated available CPU capacity to a scheduler; and selecting a target hypervisor based on the calculated capacity requirement of each virtual server and the calculated available CPU capacity at each importance level of each hypervisor.

Predictive virtual server scheduling and optimization of dynamic consumable resources to achieve priority-based workload performance objectives

Examples of techniques for resource sharing management of a field programmable device are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include: selecting a job belonging to one of a plurality of tenants based on resource control; dispatching a job to the field programmable device, wherein the job is received at a processing device, and wherein the job comprises dispatchable units; performing, by the field programmable device, the dispatchable units belonging to the job; and tracking, by the processing device, processing statistics related to each of the plurality of virtual processing devices based on performing the dispatchable units belong to the job.

Resource sharing management of a field programmable device

Examples of techniques for utilizing a field programmable device binary to perform a workload are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include: calling an application program interface to perform a workload; determining, by a processing device, using dynamic characteristics of the workload and a workload environment, whether the workload should be processed by a field programmable device or a software library running on the general purpose processing device; responsive to determining to process the job by the field programmable device, deploying the job to the field programmable device; and responsive to determining to process the job by a software library running on the general purpose processing device, deploying the job to the software library.

Deploying and utilizing a software library and corresponding field programmable device binary

Examples of techniques for service level management of a workload defined environment are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include: collecting runtime workload data for a workload executing within a container; performing, by a processing device, a determination of whether the runtime workload data satisfies a goal set forth in a service level agreement; responsive to determining that the runtime workload data does not satisfy the goal, providing data from within the container in a format utilized by an application program interface; and accessing the data from within the container through the application program interface from outside of the container.

Examples of techniques for managing workload distribution based on field programmable devices are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include: determining, by a processor, a first workload performance for a first general purpose processor and a first field programmable device for a first processing system; determining, by the processor, a second workload performance for a second general purpose processor and a second field programmable device for a second processing system; determining whether the first processing system is likely to outperform the second processing system for execution of a workload; and responsive to determining that the first processing system is likely to outperform the second processing system for the workload, deploying the workload to the first processing system.

Managing workload distribution among processing systems based on field programmable devices

Examples of techniques for deploying a software library and a corresponding field programmable device binary are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include: determining whether the software library and the field programmable device binary are available; determining whether to deploy the field programmable device binary to a field programmable device; determining whether to install the software library for use on a general purpose processor; responsive to determining to install the field programmable device binary to the field programmable device, deploying the field programmable device binary to the field programmable device; and responsive to determining to install the software library for use on the general purpose processor, installing the software library for use the general purpose processor.

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Lagrangeville, NY, United States of America

Peter Bergersen Yocom