Abstract: Methods, systems, and products are disclosed for executing a distributed JAVA application on a plurality of compute nodes. The JAVA application includes a plurality of jobs distributed among the plurality of compute nodes. The plurality of compute nodes are connected together for data communications through a data communication network. Each of the plurality of compute nodes has installed upon it a JAVA Virtual Machine (‘JVM’) capable of supporting at least one job of the JAVA application. Executing a distributed JAVA application on a plurality of compute nodes includes: tracking, by an application manager, JVM environment variables for the JVMs installed on the plurality of compute nodes; and configuring, by the application manager, the plurality of jobs for execution on the plurality of compute nodes in dependence upon the JVM environment variables for the JVMs installed on the plurality of compute nodes.

Abstract: Embodiments of the invention provide techniques for scheduling jobs on a multi-node computing system based on the predicted environmental impact of executing the jobs. In one embodiment, a plurality of job plans may be generated for processing a requested job on the multi-node computing system. The environmental impacts resulting from executing each job plan may be estimated by matching the job plans to stored data based on standardized executions of job plans. Further, environmental impacts may be estimated by matching the job plans to stored data based on actual environmental measurements obtained during prior executions of the job plan on the multi-node computer system. The job may be executed using a job plan selected based on predicted environmental impacts and time performance.

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, systems, and products are disclosed for executing an application on a parallel computer having a plurality of nodes. Executing an application on a parallel computer includes: booting up a first subset of a plurality of nodes in a serial processing mode; booting up a second subset of the plurality of nodes in a parallel processing mode; profiling, prior to application execution, an application to identify serial segments of the application, parallel segments of the application, and application data utilized by each of the serial segments and the parallel segments; and executing the application on the plurality of nodes, including migrating, in dependence upon the profile for the application upon encountering the parallel segments during execution, only specific portions of the application and the application data from the nodes booted up in the serial processing mode to the nodes booted up in the parallel processing mode.

Abstract: Methods, systems, and products are disclosed for executing a distributed Java application on a plurality of compute nodes. The Java application includes a plurality of jobs distributed among the plurality of compute nodes. The plurality of compute nodes are connected together for data communications through a data communication network. Each of the plurality of compute nodes has installed upon it a Java Virtual Machine (‘JVM’) capable of supporting at least one job of the Java application. Executing a distributed Java application on a plurality of compute nodes includes: tracking, by an application manager, a just-in-time (‘JIT’) compilation history for the JVMs installed on the plurality of compute nodes; and configuring, by the application manager, the plurality of jobs for execution on the plurality of compute nodes in dependence upon the JIT compilation history for the JVMs installed on the plurality of compute nodes.

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: A process is disclosed for identifying and recovering from resource leaks on compute nodes of a parallel computing system. A resource monitor stores information about system resources available on a compute node in a clean state. After the compute node runs a job, the resource monitor compares the current resource availability to the clean state. If a resource leak is found, the resource monitor contacts a global resource manger to remove the resource leak.

Abstract: Methods, apparatus, and products are disclosed for reducing power consumption during execution of an application on a plurality of compute nodes that include: powering up, during compute node initialization, only a portion of computer memory of the compute node, including configuring an operating system for the compute node in the powered up portion of computer memory; receiving, by the operating system, an instruction to load an application for execution; allocating, by the operating system, additional portions of computer memory to the application for use during execution; powering up the additional portions of computer memory allocated for use by the application during execution; and loading, by the operating system, the application into the powered up additional portions of computer memory.

Abstract: Methods, apparatus, and products are disclosed for executing an application on a parallel computer that include: executing, by a current compute node, a current task of the application, including producing results; determining, by the current compute node in dependence upon current network characteristics and application characteristics, whether to transfer the results to a next compute node for further processing by a next task on the next compute node or to execute the next task for further processing of the results on the current compute node; transferring, by the current compute node, the results to the next compute node for further processing by the next task on the next compute node if the determination specifies transferring the results to the next node; and executing, by the current compute node, the next task for further processing of the results if the determination specifies executing the next task on the current compute node.

Abstract: Methods, apparatus, and products are disclosed for thread selection during context switching on a plurality of compute nodes that includes: executing, by a compute node, an application using a plurality of threads of execution, including executing one or more of the threads of execution; selecting, by the compute node from a plurality of available threads of execution for the application, a next thread of execution in dependence upon power characteristics for each of the available threads; determining, by the compute node, whether criteria for a thread context switch are satisfied; and performing, by the compute node, the thread context switch if the criteria for a thread context switch are satisfied, including executing the next thread of execution.

Abstract: Methods, apparatus, and products are disclosed for balancing a data processing load among a plurality of compute nodes in a parallel computer that include: partitioning application data for processing on the plurality of compute nodes into data chunks; receiving, by each compute node, at least one of the data chunks for processing; estimating, by each compute node, processing time involved in processing the data chunks received by that compute node for processing; and redistributing, by at least one of the compute nodes to at least one of the other compute nodes, a portion of the data chunks received by that compute node in dependence upon the processing time estimated by that compute node.

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: Systems, methods and articles of manufacture are disclosed for injecting parameter conditions to reduce a size of a data set to be processed. A data set may be received to be processed by an analytic routine. The data set may include results from executing a first query. Further, input may be received from a user, the input specifying a parameter specific to the analytic routine to be performed on the data set. At least one condition associated with the specified parameter may be identified. A second query may be generated from the first query and the identified condition. The second query may be executed to generate a reduced data set. The analytic routine may be performed on the reduced data set to generate an output to the user.

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: 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: 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: 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: Methods, systems, and products are disclosed for executing a distributed Java application on a plurality of compute nodes. The Java application includes a plurality of jobs distributed among the plurality of compute nodes. The plurality of compute nodes are connected together for data communications through a data communication network. Each of the plurality of compute nodes has installed upon it a Java Virtual Machine (‘JVM’) capable of supporting at least one job of the Java application. Executing a distributed Java application on a plurality of compute nodes includes: tracking, by an application manager, a just-in-time (‘JIT’) compilation history for the JVMs installed on the plurality of compute nodes; and configuring, by the application manager, the plurality of jobs for execution on the plurality of compute nodes in dependence upon the JIT compilation history for the JVMs installed on the plurality of compute nodes.

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: A process is disclosed for identifying and recovering from resource leaks on compute nodes of a parallel computing system. A resource monitor stores information about system resources available on a compute node in a clean state. After the compute node runs a job, the resource monitor compares the current resource availability to the clean state. If a resource leak is found, the resource monitor contacts a global resource manger to remove the resource leak.