Disney Enterprises, Inc.

Jonathan Geibel

Jeffrey M Jordan

Scott Lane Burris

Kevin Christopher Constantine

Evan Goldberg

Henry Allen Driskill

Jay Steele

Thomas Charles Greer

Curtis Zinzilieta

A system and method for leveraging grid computing for node based interactive workflows is disclosed. A server system spawns a server process that receives node graph data and input attributes from a computing device, processes the data, caches the processed data, and transmits the processed data over a network to a computing device. The computing device runs a node graph application instance comprising proxy nodes configured to initiate a request to process node graph data at the server system. The server processed node graph data is displayed on the computing device. A plurality of computing devices may collaborate on a complex node graph where the node graph data processing is distributed over a plurality of servers.

Dynamically allocated computing method and system for distributed node-based interactive workflows

A batch scheduler receives a task. Further, a processor, at the batch scheduler, generates a virtual machine corresponding to the task. In addition, the virtual machine is deployed from the batch scheduler to a compute node. The task is also dispatched from the batch scheduler to the virtual machine at the compute node.

Batch scheduler management of virtual machines

A server receives a first set of file activity data from a first file monitor. The first set of file activity data indicates activity associated with a first set of files accessed at a first compute node in communication with a network. Further, the server receives a second set of file activity data from a second file monitor. The second set of file activity data indicates activity associated with a second set of files accessed at a second compute node in communication with the network. In addition, the server aggregates the first set of file activity data and the second set of file activity data into an aggregated set of network file activity data.

File monitoring

A request from a client to perform a task is received. The client has a predetermined limit of compute resources. The task is dispatched from a batch scheduler to a compute node as a non-speculative task if a quantity of compute resources is available at the compute node to process the task, and the quantity of compute resources in addition to a total quantity of compute resources being utilized by the client is less than or equal to the predetermined limit, such that the non-speculative task is processed without being preempted by an additional task requested by an additional client. The task is dispatched, from the batch scheduler to the compute node, as a speculative task if the quantity of compute resources is available to process the task, and the quantity of compute resources in addition to the total quantity of compute resources is greater than the predetermined limit.

Batch scheduler management of speculative and non-speculative tasks based on conditions of tasks and compute resources

An interactive response monitoring tool receives an indication that an input has been received at a computing device. Further, the interactive response monitoring tool determines if a response by the computing device to the input is slower than a predetermined response threshold. In addition, the interactive response monitoring tool determines a cause of a slowdown if the predetermined response threshold has been surpassed.

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Burbank, CA, United States of America

Jonathan Geibel