Google Inc.

Microsoft Technology Licensing, LLC

Ashish Raniwala

Craig D Chambers

Frances J Perry

Robert R Henry

Robert Bradshaw

Stephen Robert Adams

Nathan Weizenbaum

Jordan Tigani

Ezra Cooper

Stephen R Adams

Ricardo Gouvêa Bianchini

Christian L Belady

Husam Atallah Alissa

Ioannis Manousakis

Winston Allen Saunders

Marcus Felipe Fontoura

David Thomas Gauthier

Brian A Janous

Osvaldo Patricio Morales

Alok Gautam Kumbhare

Mark Alan Monroe

Inigo Goiri Presa

Deepak Menon

Nithish Mahalingam

Kyle Edward Woolcock

Lalu Vannankandy Kunnath

Brijesh Warrier

Ehsan Nasr Azadani

Sean Patrick Abbott

Kevin C Zatloukal

Majid Jalili

Theo Vassilakis

Rodrigo Lemos De Assis

Upshur Bagwell Quinby, V

Pulkit Ambikanandan Misra

A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Parallel processing of data

A power controller allocates input power to a datacenter between computing power for computing services, backup power, and overhead power for overhead systems. The power controller reallocates the overhead power and/or the backup power to the computing power. This may increase the overall utilization of the datacenter by allowing additional processing power of the servers to be used.

Allocating power between overhead, backup, and computing power services

The present disclosure relates to systems, methods, and computer readable media for optimizing resource allocation on a computing zone based on bursting data and in accordance with an allocation policy. For example, systems disclosed herein may implement a lifetime-aware allocation of computing resources to facilitate computational bursting on respective server nodes to prioritize different aspects of performance on the server nodes of a cloud computing system. The systems described herein provide a number of benefits, including, by way of example, facilitating an allocation policy that enables more densely packing virtual machines on respective server nodes, boosting individual virtual machine performance, and reducing a buffer of empty nodes that need to be maintained on one or more node clusters. This may include more densely packing virtual machines on respective server nodes.

Managing computational bursting on server nodes

One example method includes identifying synchronous code including instructions specifying a computing operation to be performed on a set of data; transforming the synchronous code into a pipeline application including one or more pipeline objects; identifying a first input data set on which to execute the pipeline application; executing the pipeline application on a first input data set to produce a first output data set; after executing the pipeline application on the first input data set, identifying a second input data set on which to execute the pipeline application; determining a set of differences between the first input data set and second input data set; and executing the pipeline application on the set of differences to produce a second output data set.

Incremental parallel processing of data

An untrusted application is received at a data center including one or more processing modules and providing a native processing environment. The untrusted application includes a data parallel pipeline. Secured processing environments are used to execute the untrusted application.

Parallel processing of data for an untrusted application

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Bellevue, WA, United States of America

Ashish Raniwala