International Business Machines Corporation

Globalfoundries Inc.

Michael A Blocksome

Charles J Archer

Brian E Smith

Joseph D Ratterman

Jeffrey John Parker

James E Carey

Philip James Sanders

Douglas R Miller

Amith R Mamidala

Sameer Kumar

Amanda Peters

Philip Heidelberger

Todd Alan Inglett

Dong Chen

Thomas M Gooding

Bob Richard Cernohous

Albert Sidelnik

Mark Edwin Giampapa

Mark Gregory Megerian

Gabor J Dozsa

Michael K Gschwind

Valentina Salapura

Paul William Coteus

Alan G Gara

Adam James Muff

Todd Edward Takken

Martin Ohmacht

Bruce Martin Fleischer

Alexandre E Eichenberger

Robert William Wisniewski

John A Gunnels

Gary Ross Ricard

Burkhard Steinmacher-Burow

Kathryn Mary O'Brien

Matthias Augustin Blumrich

Sameh W Asaad

Shawn Anthony Hall

Thomas Winters Fox

John Kevin O'Brien

Chen-Yong Cher

Barry Marshall Trager

Peng Wu

Charles David Wait

Daniel A Faraj

James Anthony Marcella

George L Chiu

Krishnan Sugavanam

Gerard Vincent Kopcsay

Patrick Joseph McCarthy

Robert Matthew Senger

David Gerald Herbeck

Noel A Eisley

David L Satterfield

Craig Brian Stunkel

Rudolf Adriaan Haring

Yutaka Sugawara

Kristan D Davis

Jose R Brunheroto

Michael B Mundy

Matthew Roger Ellavsky

Robert E Walkup

James Lee Van Oosten

Samuel J Miller

Ruth Janine Poole

Ralph E Bellofatto

Peter Boyle

Brant L Knudson

Todd Eric Johnson

Norman Christ

Kahn C Evans

William Maupin Stockdell

Alfred Thomas Watson, Iii

Jeremy E Berg

Melissa Aron

Jeff Parker

Hanhong Xue

Amanda Randles

Hanghong Xue

Data communications may be carried out in a distributed computing environment that includes a plurality of computers coupled for data communications through communications adapters and an active messaging interface ('AMI'). In distributed computing environment, data communications may include: receiving in the AMI from an application an eager SEND instruction that describes the location and size of send data in an application SEND buffer; copying by the AMI the send data from the application SEND buffer to a temporary AMI buffer; advising the application of completion of the SEND instruction before sending the SEND data to the receiver; and after advising the application of completion of the SEND instruction, sending the SEND data by the sender to the receiver.

Data communications in a distributed computing environment

In a distributed computing environment that includes hosts that execute a VMM, where each VMM supports execution of one or more VMs, administering VMs may include: assigning, by a VMM manager, the VMMs of the distributed computing environment to a logical tree topology, including assigning one of the VMMs as a root VMM of the tree topology; and executing, amongst the VMMs of the tree topology, a broadcast operation, including: pausing, by the root VMM, execution of one or more VMs supported by the root VMM; sending, by the root VMM, to other VMMs in the tree topology, a message indicating a pending transfer of the paused VMs; and transferring the paused VMs from the root VMM to the other VMMs.

Administering virtual machines in a distributed computing environment

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time and supports DMA functionality allowing for parallel processing message-passing.

Multi-petascale highly efficient parallel supercomputer

The present invention provides a system and method for extracting elements from distributed arrays on a parallel processing system. The system includes a module that populates a result array with globally largest elements from input arrays, a module that generates a partition element, a module that counts the number of local elements greater than the partition element, and a module that determines the globally largest elements. The method for extracting elements from distributed arrays on a parallel processing system includes populating a result array with globally largest elements from input arrays, generating a partition element, counting the number of local elements greater than the partition and determining the globally largest elements.

Parallel, low-latency method for high-performance speculative globally-large element extraction from distributed, sorted arrays

In a distributed computing environment that includes hosts that execute a VMM, with each VMM supporting execution of one or more VMs, administering VMs may include: assigning, by a VMM manager, the VMMs of the distributed computing environment to a logical tree topology, including assigning one of the VMMs as a root VMM of the tree topology; and executing, amongst the VMMs of the tree topology, a scatter operation, including: pausing, by the root VMM one or more executing VMs; storing, by the root VMM in a buffer, a plurality of VMs to scatter amongst the other VMMs of the tree topology; and sending, by the root VMM, to each of the other VMMs of the tree topology a different one of the VMs stored in the buffer.

Methods, apparatuses, and computer program products for adaptive clock throttling for event processing are provided. Embodiments include an event processing system receiving a plurality of events from one or more components of the distributed processing system. Embodiments also include the event processing system determining that an arrival attribute of the plurality of events exceeds an arrival threshold. Embodiments also include the event processing system, adjusting, in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, a clock speed of at least one of the event processing system and a component of the distributed processing system.

Adaptive clock throttling for event processing

In a distributed computing environment that includes which each execute a VMM, where each VMM supports execution of one or more VMs, administering the VMs may include: assigning, by a VMM manager, the VMMs of the distributed computing environment to a logical tree topology, including assigning one of the VMMs as a root VMM of the tree topology; and executing, amongst the VMMs of the tree topology, a gather operation, including: sending, by the root VMM, to other VMMs in the tree topology, a request to retrieve one or more VMs supported by the other VMMs; pausing, by the other VMMs, each VM requested to be retrieved; and providing, by the other VMMs to the root VMM, the VMs requested to be retrieved.

Administering VMs in a distributed computing environment that includes hosts that execute a VMM, with each VMM supporting execution of one or more VMs, includes: assigning the VMMs to a logical tree topology with one as a root; and executing, by the VMMs of the tree topology, a reduce operation, including: sending, by the root VMM to each of other VMMs of the tree topology, a request for an instance of a particular VM; pausing, by each of the other VMMs, the requested instance of the particular VM; providing, by each of the other VMMs to the root VMM in response to the root VMM's request, the requested instance of the particular VM; and identifying, by the root VMM, differences among the requested instances of the particular VM including, performing a bitwise XOR operation amongst the instances of the particular VM.

Distributed hardware device simulation, including: identifying a plurality of hardware components of the hardware device; providing software components simulating the functionality of each hardware component, wherein the software components are installed on compute nodes of a distributed processing system; receiving, in at least one of the software components, one or more messages representing an input to the hardware component; simulating the operation of the hardware component with the software component, thereby generating an output of the software component representing the output of the hardware component; and sending, from the software component to at least one other software component, one or more messages representing the output of the hardware component.

Distributed hardware device simulation

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Rochester, MN, United States of America

Michael A Blocksome