Abstract: Configuring compute nodes in a parallel computer using remote direct memory access (‘RDMA’), the parallel computer comprising a plurality of compute nodes coupled for data communications via one or more data communications networks, including: initiating, by a source compute node of the parallel computer, an RDMA broadcast operation to broadcast binary configuration information to one or more target compute nodes in the parallel computer; preparing, by each target compute node, the target compute node for receipt of the binary configuration information from the source compute node; transmitting, by each target compute node, a ready message to the target compute node, the ready message indicating that the target compute node is ready to receive the binary configuration information from the source compute node; and performing, by the source compute node, an RDMA broadcast operation to write the binary configuration information into memory of each target compute node.

Abstract: Configuring compute nodes in a parallel computer using remote direct memory access (‘RDMA’), the parallel computer comprising a plurality of compute nodes coupled for data communications via one or more data communications networks, including: initiating, by a source compute node of the parallel computer, an RDMA broadcast operation to broadcast binary configuration information to one or more target compute nodes in the parallel computer; preparing, by each target compute node, the target compute node for receipt of the binary configuration information from the source compute node; transmitting, by each target compute node, a ready message to the target compute node, the ready message indicating that the target compute node is ready to receive the binary configuration information from the source compute node; and performing, by the source compute node, an RDMA broadcast operation to write the binary configuration information into memory of each target compute node.

Abstract: Configuring compute nodes in a parallel computer using remote direct memory access (‘RDMA’), the parallel computer comprising a plurality of compute nodes coupled for data communications via one or more data communications networks, including: initiating, by a source compute node of the parallel computer, an RDMA broadcast operation to broadcast binary configuration information to one or more target compute nodes in the parallel computer; preparing, by each target compute node, the target compute node for receipt of the binary configuration information from the source compute node; transmitting, by each target compute node, a ready message to the target compute node, the ready message indicating that the target compute node is ready to receive the binary configuration information from the source compute node; and performing, by the source compute node, an RDMA broadcast operation to write the binary configuration information into memory of each target compute node.

Abstract: Configuring compute nodes in a parallel computer using remote direct memory access (‘RDMA’), the parallel computer comprising a plurality of compute nodes coupled for data communications via one or more data communications networks, including: initiating, by a source compute node of the parallel computer, an RDMA broadcast operation to broadcast binary configuration information to one or more target compute nodes in the parallel computer; preparing, by each target compute node, the target compute node for receipt of the binary configuration information from the source compute node; transmitting, by each target compute node, a ready message to the target compute node, the ready message indicating that the target compute node is ready to receive the binary configuration information from the source compute node; and performing, by the source compute node, an RDMA broadcast operation to write the binary configuration information into memory of each target compute node.

Abstract: Configuring compute nodes in a parallel computer using remote direct memory access (‘RDMA’), the parallel computer comprising a plurality of compute nodes coupled for data communications via one or more data communications networks, including: initiating, by a source compute node of the parallel computer, an RDMA broadcast operation to broadcast binary configuration information to one or more target compute nodes in the parallel computer; preparing, by each target compute node, the target compute node for receipt of the binary configuration information from the source compute node; transmitting, by each target compute node, a ready message to the target compute node, the ready message indicating that the target compute node is ready to receive the binary configuration information from the source compute node; and performing, by the source compute node, an RDMA broadcast operation to write the binary configuration information into memory of each target compute node.

Abstract: Configuring compute nodes in a parallel computer using remote direct memory access (‘RDMA’), the parallel computer comprising a plurality of compute nodes coupled for data communications via one or more data communications networks, including: initiating, by a source compute node of the parallel computer, an RDMA broadcast operation to broadcast binary configuration information to one or more target compute nodes in the parallel computer; preparing, by each target compute node, the target compute node for receipt of the binary configuration information from the source compute node; transmitting, by each target compute node, a ready message to the target compute node, the ready message indicating that the target compute node is ready to receive the binary configuration information from the source compute node; and performing, by the source compute node, an RDMA broadcast operation to write the binary configuration information into memory of each target compute node.

Abstract: Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

Abstract: Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

Abstract: Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

Abstract: Collectively loading an application in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: identifying, by a parallel computer control system, a subset of compute nodes in the parallel computer to execute a job; selecting, by the parallel computer control system, one of the subset of compute nodes in the parallel computer as a job leader compute node; retrieving, by the job leader compute node from computer memory, an application for executing the job; and broadcasting, by the job leader to the subset of compute nodes in the parallel computer, the application for executing the job.

Abstract: Methods, apparatuses, and computer program products for servicing a globally broadcast interrupt signal in a multi-threaded computer comprising a plurality of processor threads. Embodiments include an interrupt controller indicating in a plurality of local interrupt status locations that a globally broadcast interrupt signal has been received by the interrupt controller. Embodiments also include a thread determining that a local interrupt status location corresponding to the thread indicates that the globally broadcast interrupt signal has been received by the interrupt controller. Embodiments also include the thread processing one or more entries in a global interrupt status bit queue based on whether global interrupt status bits associated with the globally broadcast interrupt signal are locked. Each entry in the global interrupt status bit queue corresponds to a queued global interrupt.

Abstract: Methods, apparatuses, and computer program products for servicing a globally broadcast interrupt signal in a multi-threaded computer comprising a plurality of processor threads. Embodiments include an interrupt controller indicating in a plurality of local interrupt status locations that a globally broadcast interrupt signal has been received by the interrupt controller. Embodiments also include a thread determining that a local interrupt status location corresponding to the thread indicates that the globally broadcast interrupt signal has been received by the interrupt controller. Embodiments also include the thread processing one or more entries in a global interrupt status bit queue based on whether global interrupt status bits associated with the globally broadcast interrupt signal are locked. Each entry in the global interrupt status bit queue corresponds to a queued global interrupt.

Abstract: Aggregating job exit statuses of a plurality of compute nodes executing a parallel application, including: identifying a subset of compute nodes in the parallel computer to execute the parallel application; selecting one compute node in the subset of compute nodes in the parallel computer as a job leader compute node; initiating execution of the parallel application on the subset of compute nodes; receiving an exit status from each compute node in the subset of compute nodes, where the exit status for each compute node includes information describing execution of some portion of the parallel application by the compute node; aggregating each exit status from each compute node in the subset of compute nodes; and sending an aggregated exit status for the subset of compute nodes in the parallel computer.

Abstract: Computer program product and system to limit core file generation in a massively parallel computing system comprising a plurality of compute nodes each executing at least one task, of a plurality of tasks, by: upon determining that a first task executing on a first compute node has failed, performing an atomic load and increment operation on a core file count; generating a first core file upon determining that the core file count is below a predefined threshold; and not generating the first core file upon determining that the core file count is not below the predefined threshold.

Abstract: Computer program product and system to limit core file generation in a massively parallel computing system comprising a plurality of compute nodes each executing at least one task, of a plurality of tasks, by: upon determining that a first task executing on a first compute node has failed, performing an atomic load and increment operation on a core file count; generating a first core file upon determining that the core file count is below a predefined threshold; and not generating the first core file upon determining that the core file count is not below the predefined threshold.

Abstract: Methods, apparatuses, and computer program products for servicing a globally broadcast interrupt signal in a multi-threaded computer comprising a plurality of processor threads. Embodiments include an interrupt controller indicating in a plurality of local interrupt status locations that a globally broadcast interrupt signal has been received by the interrupt controller. Embodiments also include a thread determining that a local interrupt status location corresponding to the thread indicates that the globally broadcast interrupt signal has been received by the interrupt controller. Embodiments also include the thread processing one or more entries in a global interrupt status bit queue based on whether global interrupt status bits associated with the globally broadcast interrupt signal are locked. Each entry in the global interrupt status bit queue corresponds to a queued global interrupt.

Abstract: Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

Abstract: Computer program product and system to limit core file generation in a massively parallel computing system comprising a plurality of compute nodes each executing at least one task, of a plurality of tasks, by: upon determining that a first task executing on a first compute node has failed, performing an atomic load and increment operation on a core file count; generating a first core file upon determining that the core file count is below a predefined threshold; and not generating the first core file upon determining that the core file count is not below the predefined threshold.

Abstract: Computer program product and system to limit core file generation in a massively parallel computing system comprising a plurality of compute nodes each executing at least one task, of a plurality of tasks, by: upon determining that a first task executing on a first compute node has failed, performing an atomic load and increment operation on a core file count; generating a first core file upon determining that the core file count is below a predefined threshold; and not generating the first core file upon determining that the core file count is not below the predefined threshold.

Abstract: Aggregating job exit statuses of a plurality of compute nodes executing a parallel application, including: identifying a subset of compute nodes in the parallel computer to execute the parallel application; selecting one compute node in the subset of compute nodes in the parallel computer as a job leader compute node; initiating execution of the parallel application on the subset of compute nodes; receiving an exit status from each compute node in the subset of compute nodes, where the exit status for each compute node includes information describing execution of some portion of the parallel application by the compute node; aggregating each exit status from each compute node in the subset of compute nodes; and sending an aggregated exit status for the subset of compute nodes in the parallel computer.