Jpmorgan Chase Bank, N.a.

Minlin Gao

Darren Marvin

Libin Yang

Jason K S Choy

Alexey Syomichev

Aaron Bell

Thomas Williams

Nelson M Pereira

Sandeep Sarthavalli Ramesh

Lee Staples

Charles Parkin

Brian Todd

Julian Leggett

Donald Harper

Rupert Pigott

Systems and methods for hybrid burst optimized regulated workload orchestration for infrastructure as a service are disclosed. According to one embodiment, in an information processing apparatus comprising at least one computer processor, a method for providing hybrid burst optimized regulated workload orchestration for infrastructure as a service may include: (1) receiving a job request for a job comprising at least one job requirement from a job requester; (2) calculating a cost of job for the job based on the at least one job requirement; (3) identifying an IaaS provider from a plurality of IaaS providers that meets the job requirements and the cost of job, wherein the plurality of IaaS providers comprises at least one on-premises IaaS provider and the at least one off-premises IaaS provider; (4) executing an IaaS request for the identified IaaS provider; and (5) monitoring execution of the job by the identified IaaS provider.

Systems and methods for hybrid burst optimized regulated workload orchestration for infrastructure as a service

Systems and methods for managing resources in a multi-tenancy grid computing environment are provided. The methods include an auxiliary service scheduler managing the lifecycle of auxiliary services by policies to optimize the resource allocation; coordinating with an application scheduler to dispatch tasks and an auxiliary service to the same set of servers; and using a multiple layer auxiliary service map to manage and record auxiliary service status. The methods optimize dynamical resource sharing between applications with a dependency on an auxiliary service running aside on the same server.

Methods for auxiliary service scheduling for grid computing and devices thereof

Methods, non-transitory computer readable media, and workload scheduler devices that determine one of a plurality of task categories for a received task. A stored expected runtime for each of a plurality of CPUs to execute one standard computation unit (SCU) in the determined one of the plurality of task category is obtained. One of the plurality of CPUs is selected based on the stored expected runtime. The task is dispatched to the selected one of the plurality of CPUs for execution. Accordingly, with this technology, tasks associated with workloads can be more effectively dispatched and more effectively processed by a CPU pool.

Methods for feedback-based optimal workload scheduling and devices thereof

A computing environment adapted with a resource allocation policy, the resource allocation policy being configured to evenly distribute application instances to as many servers as possible.

Breadth-first resource allocation system and methods

Growing community of inventors

Livingston, NJ, United States of America

Minlin Gao