Ca, Inc.

Hyperformix, Inc.

Hyperformit, Inc.

Kenneth Zink

Douglas Neuse

Paul David Peterson

Christopher Brian Walton

Laurence E Clay

Theodore Lehr

Neal Tibrewala

Allan Drew Clarke

Paul T Barnett

Timothy E Wise

Richard Gimarc

Daniel M Braddock

Annette Palmer

Tom Zauli

David Leigh DuPré´

Rajinikala Ramachandran

Carolyn West

Steven M Oberlin

James Reynolds

Amy Carolyn Spellmann

James Renyolds

Amy Carolyn Spellman

Methods of analyzing and capacity planning for multi-core, multi-chip, multi-threaded computer system environments by analyzing the scalability of a fourth layer complexity, the processor boards, and incorporating this factor into the calculation of the expected throughput of a system constructed with multiple processor boards. In particular, the method may comprise identifying a system for which system performance prediction is desired, specifying a simulation model, and determining configuration parameters for the system, the system with at least one processor board, at least one chip per board, at least one core per chip, and at least one thread per core. The method may further comprise obtaining scalability factors based on the configuration data for the system, executing a simulation process for the simulation model for a deterministic simulation time, calculating a throughput of the system as a prediction of the performance of the system, and storing the results in a storage device.

Capacity planning for systems with multiprocessor boards

A method includes receiving a request for access to an instance of a computing resource, the request having a performance standard associated therewith, requesting the instance of the computing resource from a computing resource provider, evaluating a performance of the instance of the computing resource provided by the computing resource provider to determine if the performance of the instance of the computing resource complies with the performance standard associated with the request, and providing access to the instance of the computing resource provided by the computing resource provider responsive to a determination that the performance of the instance of the computing resource complies with the performance standard associated with the request. Related systems and computer program products are also disclosed.

Methods, systems, and computer program products for user side optimization of acquisition of virtualized resources

A method for expressing a hierarchy of scalabilities in complex systems, including a discrete event simulation and an analytic model, for analysis and prediction of the performance of multi-chip, multi-core, multi-threaded computer processors is provided. Further provided is a capacity planning tool for migrating data center systems from a source configuration which may include source systems with multithreaded, multicore, multichip central processing units to a destination configuration which may include destination systems with multithreaded, multicore and multichip central processing units, wherein the destination systems may be different than the source systems. Apparatus and methods are taught for the assembling of and utilization of linear and exponential scalability factors in the capacity planning tool when a plurality of active processor threads populate processors with multiple chips, multiple cores per chip and multiple threads per core.

System and method for capacity planning for systems with multithreaded multicore multiprocessor resources

A system and method for automatically reconfiguring a computing environment comprises a consumption analysis server, a placement server, a deployment server in communication with a set of virtual machine monitors and a data warehouse in communication with a set of data collection agents, and a database. The consumption analysis server operates on measured resource utilization data in the data warehouse to yield a set of resource consumptions, available capacities and host and virtual machine configurations from the computing environment. The deployment server continuously monitors an event triggering condition and when the triggering condition is met, the placement server assigns a set of target virtual machines to a target set of hosts in a new placement and the deployment server implements the new placement through communication with the set of virtual machine monitors. The placement server right-sizes the virtual machines and the target set of hosts.

System and method for continuous optimization of computing systems with automated assignment of virtual machines and physical machines to hosts

A system and method for reconfiguring a computing environment comprising a consumption analysis server, a placement server and a data warehouse in communication with a set of data collection agents and a database. The consumption analysis server operates on measured resource utilization data to yield a set of resource consumptions in regularized time blocks, collects host and virtual machine configurations from the computing environment and determines available capacity for a set of target hosts. The placement server assigns a set of target virtual machines to the target set of hosts in a new placement that is right-sized according to a set of right-sizing constraints and rules. In one mode of operation the new placement is nearly optimal. In another mode of operation, the new placement is 'good enough' to achieve a threshold score based on an objective function of capacity headroom. The new placement is implemented in the computing environment.

System and method for automated assignment of virtual machines and physical machines to hosts with right-sizing

A system and method for reconfiguring a computing environment comprising a consumption analysis server, a placement server, an infrastructure management client and a data warehouse in communication with a set of data collection agents and a database. The consumption analysis server operates on measured resource utilization data to yield a set of resource consumptions in regularized time blocks, collects host and virtual machine configurations from the computing environment and determines available capacity for a set of target hosts. The placement server assigns a set of target virtual machines to the target set of hosts in a new placement. In one mode of operation the new placement is nearly optimal. In another mode of operation, the new placement is 'good enough' to achieve a threshold score based on an objective function of resource capacity headroom. The new placement is implemented in the computing environment.

System and method for automated assignment of virtual machines and physical machines to hosts

A method of semi-automatic data collection, data analysis and model generation for performance analysis of computer networks and software is provided. The invention provides a graphical user interface which indicates the overall data flow in the performance analysis process and guides the user through the proper sequence of steps in that process. Underneath the graphical user interface, the invention provides software tools which include novel data pipeline for transformation of network traces, resource data and application data into organized hash tables, and further into spreadsheets for introduction into computer network simulation programs. The invention also provides novel algorithms for recognizing transaction and parentage between transactions from low level network trace data. The invention further provides novel methods of visualization of trace data and transaction and parentage associations.

Method of semi-automatic data collection, data analysis, and model generation for the performance analysis of enterprise applications

Growing community of inventors

Austin, TX, United States of America

Kenneth Zink