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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Low latency, high bandwidth data communications between compute nodes in a parallel computer

Methods, systems, and products are disclosed for data transfers between nodes in a parallel computer that include: receiving, by an origin DMA on an origin node, a buffer identifier for a buffer containing data for transfer to a target node; sending, by the origin DMA to the target node, a RTS message; transferring, by the origin DMA, a data portion to the target node using a memory FIFO operation that specifies one end of the buffer from which to begin transferring the data; receiving, by the origin DMA, an acknowledgement of the RTS message from the target node; and transferring, by the origin DMA in response to receiving the acknowledgement, any remaining data portion to the target node using a direct put operation that specifies the other end of the buffer from which to begin transferring the data, including initiating the direct put operation without invoking an origin processing core.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Low latency, high bandwidth data communications between compute nodes in a parallel computer

Methods, systems, and products are disclosed for data transfers between nodes in a parallel computer that include: receiving, by an origin DMA on an origin node, a buffer identifier for a buffer containing data for transfer to a target node; sending, by the origin DMA to the target node, a RTS message; transferring, by the origin DMA, a data portion to the target node using a memory FIFO operation that specifies one end of the buffer from which to begin transferring the data; receiving, by the origin DMA, an acknowledgement of the RTS message from the target node; and transferring, by the origin DMA in response to receiving the acknowledgement, any remaining data portion to the target node using a direct put operation that specifies the other end of the buffer from which to begin transferring the data, including initiating the direct put operation without invoking an origin processing core.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Low latency, high bandwidth data communications between compute nodes in a parallel computer

Methods, systems, and products are disclosed for data transfers between nodes in a parallel computer that include: receiving, by an origin DMA on an origin node, a buffer identifier for a buffer containing data for transfer to a target node; sending, by the origin DMA to the target node, a RTS message; transferring, by the origin DMA, a data portion to the target node using a memory FIFO operation that specifies one end of the buffer from which to begin transferring the data; receiving, by the origin DMA, an acknowledgement of the RTS message from the target node; and transferring, by the origin DMA in response to receiving the acknowledgement, any remaining data portion to the target node using a direct put operation that specifies the other end of the buffer from which to begin transferring the data, including initiating the direct put operation without invoking an origin processing core.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Self-pacing direct memory access data transfer operations for compute nodes in a parallel computer

Methods, apparatus, and products are disclosed for self-pacing DMA data transfer operations for nodes in a parallel computer that include: transferring, by an origin DMA on an origin node, a RTS message to a target node, the RTS message specifying an message on the origin node for transfer to the target node; receiving, in an origin injection FIFO for the origin DMA from a target DMA on the target node in response to transferring the RTS message, a target RGET descriptor followed by a DMA transfer operation descriptor, the DMA descriptor for transmitting a message portion to the target node, the target RGET descriptor specifying an origin RGET descriptor on the origin node that specifies an additional DMA descriptor for transmitting an additional message portion to the target node; processing, by the origin DMA, the target RGET descriptor; and processing, by the origin DMA, the DMA transfer operation descriptor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Accurate and Scalable O(N) Algorithm for First-Principles Molecular-Dynamics Computations on Large Parallel Computers

We present the first truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems with finite band gaps of sizes that were previously impossible with this degree of accuracy. By avoiding global communications, we provide a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wave functions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 101 952 atoms on 23 328 processors, with a wall-clock time of the order of 1 min per molecular dynamics time step and numerical error on the forces of less than 7x10 -4 Ha/Bohr.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Data communications in a parallel active messaging interface of a parallel computer

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a data communications instruction, the instruction characterized by an instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance with the instruction type, the transfer data from the origin endpoint to the target endpoint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Data communications in a parallel active messaging interface of a parallel computer

Data communications in a parallel active messaging interface ('PAMI') or a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution of a compute node, including specification of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications instruction, the instruction characterized by instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance witht the instruction type, the transfer data from the origin endpoin to the target endpoint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Synchronizing compute node time bases in a parallel computer

Synchronizing time bases in a parallel computer that includes compute nodes organized for data communications in a tree network, where one compute node is designated as a root, and, for each compute node: calculating data transmission latency from the root to the compute node; configuring a thread as a pulse waiter; initializing a wakeup unit; and performing a local barrier operation; upon each node completing the local barrier operation, entering, by all compute nodes, a global barrier operation; upon all nodes entering the global barrier operation, sending, to all the compute nodes, a pulse signal; and for each compute node upon receiving the pulse signal: waking, by the wakeup unit, the pulse waiter; setting a time base for the compute node equal to the data transmission latency between the root node and the compute node; and exiting the global barrier operation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Synchronizing compute node time bases in a parallel computer

Synchronizing time bases in a parallel computer that includes compute nodes organized for data communications in a tree network, where one compute node is designated as a root, and, for each compute node: calculating data transmission latency from the root to the compute node; configuring a thread as a pulse waiter; initializing a wakeup unit; and performing a local barrier operation; upon each node completing the local barrier operation, entering, by all compute nodes, a global barrier operation; upon all nodes entering the global barrier operation, sending, to all the compute nodes, a pulse signal; and for each compute node upon receiving the pulse signal: waking, by the wakeup unit, the pulse waiter; setting a time base for the compute node equal to the data transmission latency between the root node and the compute node; and exiting the global barrier operation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Identifying logical planes formed of compute nodes of a subcommunicator in a parallel computer

In a parallel computer, a plurality of logical planes formed of compute nodes of a subcommunicator may be identified by: for each compute node of the subcommunicator and for a number of dimensions beginning with a first dimension: establishing, by a plane building node, in a positive direction of the first dimension, all logical planes that include the plane building node and compute nodes of the subcommunicator in a positive direction of a second dimension, where the second dimension is orthogonal to the first dimension; and establishing, by the plane building node, in a negative direction of the first dimension, all logical planes that include the plane building node and compute nodes of the subcommunicator in the positive direction of the second dimension.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Identifying logical planes formed of compute nodes of a subcommunicator in a parallel computer

In a parallel computer, a plurality of logical planes formed of compute nodes of a subcommunicator may be identified by: for each compute node of the subcommunicator and for a number of dimensions beginning with a first dimension: establishing, by a plane building node, in a positive direction of the first dimension, all logical planes that include the plane building node and compute nodes of the subcommunicator in a positive direction of a second dimension, where the second dimension is orthogonal to the first dimension; and establishing, by the plane building node, in a negative direction of the first dimension, all logical planes that include the plane building node and compute nodes of the subcommunicator in the positive direction of the second dimension.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Identifying a largest logical plane from a plurality of logical planes formed of compute nodes of a subcommunicator in a parallel computer

In a parallel computer, a largest logical plane from a plurality of logical planes formed of compute nodes of a subcommunicator may be identified by: identifying, by each compute node of the subcommunicator, all logical planes that include the compute node; calculating, by each compute node for each identified logical plane that includes the compute node, an area of the identified logical plane; initiating, by a root node of the subcommunicator, a gather operation; receiving, by the root node from each compute node of the subcommunicator, each node's calculated areas as contribution data to the gather operation; and identifying, by the root node in dependence upon the received calculated areas, a logical plane of the subcommunicator having the greatest area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Broadcasting collective operation contributions throughout a parallel computer

Methods, systems, and products are disclosed for broadcasting collective operation contributions throughout a parallel computer. The parallel computer includes a plurality of compute nodes connected together through a data communications network. Each compute node has a plurality of processors for use in collective parallel operations on the parallel computer. Broadcasting collective operation contributions throughout a parallel computer according to embodiments of the present invention includes: transmitting, by each processor on each compute node, that processor's collective operation contribution to the other processors on that compute node using intra-node communications; and transmitting on a designated network link, by each processor on each compute node according to a serial processor transmission sequence, that processor's collective operation contribution to the other processors on the other compute nodes using inter-node communications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Scalable Graph Analytics and HPC Operational Enhancement: Parallel Computing and ML/DL Innovations

Parallel computing plays a pivotal role in the efficient processing of large-scale graphs. Complex network analysis stands as a capti- vating research frontier, holding promise across diverse scientific domains such as sociology, biology, online media, and recommenda- tion systems. In this era, Machine Learning (ML) and Deep Learning (DL) have emerged as indispensable tools, underpinning remarkable technological achievements. Within this dynamic landscape, my research revolves around advancing parallel algorithms tailored for large-scale graph operations. To achieve this, I harness the power of cutting-edge technologies including OpenMP, MPI, HIP, and CUDA, on the High-Performance Computing (HPC) platforms to unlock optimal performance. I also apply ML/DL techniques to HPC operational data, to streamline the monitoring and maintenance of supercomputers, alleviating the complexities associated with their upkeep and enhancing user support. My research echoes the syn- ergy between parallel computing, large-scale graph analysis, and ML/DL, improving computational efficiency and user experience.

Sattar, Naw Safrin↗
DOE OSTI2013

Data communications in a parallel active messaging interface of a parallel computer

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Endpoint-based parallel data processing with non-blocking collective instructions in a parallel active messaging interface of a parallel computer

Endpoint-based parallel data processing with non-blocking collective instructions in a PAMI of a parallel computer is disclosed. The PAMI is composed of data communications endpoints, each including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task. The compute nodes are coupled for data communications through the PAMI. The parallel application establishes a data communications geometry specifying a set of endpoints that are used in collective operations of the PAMI by associating with the geometry a list of collective algorithms valid for use with the endpoints of the geometry; registering in each endpoint in the geometry a dispatch callback function for a collective operation; and executing without blocking, through a single one of the endpoints in the geometry, an instruction for the collective operation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

Endpoint-based parallel data processing in a parallel active messaging interface ('PAMI') of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective opeartion through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

Endpoint-based parallel data processing in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective operation through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

97 MATHEMATICS AND COMPUTING↗