Abstract: Methods, apparatus, and products are disclosed for budget-based power consumption for application execution on a plurality of compute nodes that include: assigning an execution priority to each of one or more applications; executing, on the plurality of compute nodes, the applications according to the execution priorities assigned to the applications at an initial power level provided to the compute nodes until a predetermined power consumption threshold is reached; and applying, upon reaching the predetermined power consumption threshold, one or more power conservation actions to reduce power consumption of the plurality of compute nodes during execution of the applications.

Abstract: Embodiments of the invention provide a method for querying performance counter data on a massively parallel computing system, while minimizing the costs associated with interrupting computer processors and limited memory resources. DMA descriptors may be inserted into an injection FIFO of a remote compute node in the massively parallel computing system. Upon executing the DMA operations described by the DMA descriptors, performance counter data may be transferred from the remote compute node to a destination node.

Abstract: Methods, apparatus, and products are disclosed for scheduling applications for execution on a plurality of compute nodes of a parallel computer to manage temperature of the plurality of compute nodes during execution that include: identifying one or more applications for execution on the plurality of compute nodes; creating a plurality of physically discontiguous node partitions in dependence upon temperature characteristics for the compute nodes and a physical topology for the compute nodes, each discontiguous node partition specifying a collection of physically adjacent compute nodes; and assigning, for each application, that application to one or more of the discontiguous node partitions for execution on the compute nodes specified by the assigned discontiguous node partitions.

Abstract: Techniques are disclosed for performing a collective operation on a parallel computing system that includes multiple compute nodes and multiple networks connecting the compute nodes. Each of the networks may have different characteristics. A source node may broadcast a DMA descriptor over a first network to a target node, to initialize the collective operation. The target node may perform the collective operation over a second network and using the broadcast DMA descriptor.

Abstract: 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.

Abstract: A combined guardrail and cable safety system is disclosed. In one aspect, a safety barrier incorporating the teachings of the present disclosure may include a plurality of cable posts spaced from each other and disposed adjacent to a roadway. At least two cables may be releasably engaged with and supported by the cable posts. The cable posts and the at least two cables may cooperate with each other to prevent a vehicle from leaving the roadway. A plurality of guardrail posts may also spaced from each other and disposed adjacent to the roadway longitudinally spaced from the plurality of cable post. A box beam guardrail beam may be attached to the plurality of guardrail posts. The at least two cables may operably extend from the cable posts to engage respective cable anchor brackets attached to the box beam guardrail beam.

Abstract: Methods, apparatus, and products are disclosed for performing an all-to-all exchange on n number of data buffers using XOR swap operations. Each data buffer has n number of data elements. Performing an all-to-all exchange on n number of data buffers using XOR swap operations includes for each rank value of i and j where i is greater than j and where i is less than or equal to n: selecting data element i in data buffer j; selecting data element j in data buffer i; and exchanging contents of data element i in data buffer j with contents of data element j in data buffer i using an XOR swap operation.

Abstract: Methods, apparatus, and products are disclosed for performing an all-to-all exchange on n number of data buffers using XOR swap operations. Each data buffer has n number of data elements. Performing an all-to-all exchange on n number of data buffers using XOR swap operations includes for each rank value of i and j where i is greater than j and where i is less than or equal to n: selecting data element i in data buffer j; selecting data element j in data buffer i; and exchanging contents of data element i in data buffer j with contents of data element j in data buffer i using an XOR swap operation.

Abstract: Methods, apparatus, and products are disclosed for profiling an application for power consumption during execution on a compute node that include: receiving an application for execution on a compute node; identifying a hardware power consumption profile for the compute node, the hardware power consumption profile specifying power consumption for compute node hardware during performance of various processing operations; determining a power consumption profile for the application in dependence upon the application and the hardware power consumption profile for the compute node; and reporting the power consumption profile for the application.

Abstract: Embodiments of the invention provide a method for querying performance counter data on a massively parallel computing system, while minimizing the costs associated with interrupting computer processors and limited memory resources. DMA descriptors may be inserted into an injection FIFO of a remote compute node in the massively parallel computing system. Upon executing the DMA operations described by the DMA descriptors, performance counter data may be transferred from the remote compute node to a destination node.

Abstract: Eager send data communications in a parallel active messaging interface (PAMI) of a parallel computer, the PAMI composed of data communications endpoints that specify a client, a context, and a task, including receiving an eager send data communications instruction with transfer data disposed in a send buffer characterized by a read/write send buffer memory address in a read/write virtual address space of the origin endpoint; determining for the send buffer a read-only send buffer memory address in a read-only virtual address space, the read-only virtual address space shared by both the origin endpoint and the target endpoint, with all frames of physical memory mapped to pages of virtual memory in the read-only virtual address space; and communicating by the origin endpoint to the target endpoint an eager send message header that includes the read-only send buffer memory address.

Abstract: Methods, apparatus, and products are disclosed for profiling an application for power consumption during execution on a compute node that include: receiving an application for execution on a compute node; identifying a hardware power consumption profile for the compute node, the hardware power consumption profile specifying power consumption for compute node hardware during performance of various processing operations; determining a power consumption profile for the application in dependence upon the application and the hardware power consumption profile for the compute node; and reporting the power consumption profile for the application.

Abstract: Optimizing the deployment of a workload on a distributed processing system, the distributed processing system having a plurality of nodes, each node having a plurality of attributes, including: profiling during operations on the distributed processing system attributes of the nodes of the distributed processing system; selecting a workload for deployment on a subset of the nodes of the distributed processing system; determining specific resource requirements for the workload to be deployed; determining a required geometry of the nodes to run the workload; selecting a set of nodes having attributes that meet the specific resource requirements and arranged to meet the required geometry; deploying the workload on the selected nodes.

Abstract: 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.

Abstract: 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.

Abstract: Endpoint-based parallel data processing with non-blocking collective instructions 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 by the parallel application a data communications geometry, the geometry specifying a set of endpoints that are used in collective operations of the PAMI, including 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.

Abstract: Methods, apparatus, and products are disclosed for performing an allreduce operation using shared memory that include: receiving, by at least one of a plurality of processing cores on a compute node, an instruction to perform an allreduce operation; establishing, by the core that received the instruction, a job status object for specifying a plurality of shared memory allreduce work units, the plurality of shared memory allreduce work units together performing the allreduce operation on the compute node; determining, by an available core on the compute node, a next shared memory allreduce work unit in the job status object; and performing, by that available core on the compute node, that next shared memory allreduce work unit.

Abstract: 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.

Abstract: Methods, apparatus, and products are disclosed for reducing power consumption during execution of an application on a plurality of compute nodes that include: executing, by each compute node, an application, the application including power consumption directives corresponding to one or more portions of the application; identifying, by each compute node, the power consumption directives included within the application during execution of the portions of the application corresponding to those identified power consumption directives; and reducing power, by each compute node, to one or more components of that compute node according to the identified power consumption directives during execution of the portions of the application corresponding to those identified power consumption directives.

Abstract: Data communications 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, endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a SEND instruction, the SEND instruction specifying a transmission of transfer data from the origin endpoint to a first target endpoint; transmitting from the origin endpoint to the first target endpoint a Request-To-Send (‘RTS’) message advising the first target endpoint of the location and size of the transfer data; assigning by the first target endpoint to each of a plurality of target endpoints separate portions of the transfer data; and receiving by the plurality of target endpoints the transfer data.