| Patent application number | Description | Published |
|---|
| 20080209179 | Low-Impact Performance Sampling Within a Massively Parallel Computer - An apparatus, program product and method sample at different times nodes that are performing similar work. Performance data associated with first and second node subsets performing the similar work are sampled at different times, e.g., in a round-robin fashion, and in accordance with a given sampling rate. The performance data is analyzed. Nodes whose performance suffers as a result of a sampling operation may be identified and removed from a subsequent operation. | 08-28-2008 |
| 20080263386 | DYNAMICALLY REROUTING NODE TRAFFIC ON A MASSIVELY PARALLEL COMPUTER SYSTEM USING HINT BITS - A method and apparatus for dynamically rerouting node processes on the compute nodes of a massively parallel computer system using hint bits to route around failed nodes or congested networks without restarting applications executing on the system. When a node has a failure or there are indications that it may fail, the application software on the system is suspended while the data on the failed node is moved to a backup node. The torus network traffic is routed around the failed node and traffic for the failed node is rerouted to the backup node. The application can then resume operation without restarting from the beginning. | 10-23-2008 |
| 20080263387 | FAULT RECOVERY ON A PARALLEL COMPUTER SYSTEM WITH A TORUS NETWORK - An apparatus and method for overcoming a torus network failure in a parallel computer system. A mesh routing mechanism in the service node of the computer system configures the nodes from a torus to a mesh network when a failure occurs in the torus network. The mesh routing mechanism takes advantage of cutoff registers in each node to route node to node data transfers around the faulty node or network connection. | 10-23-2008 |
| 20090043728 | Query Optimization in a Parallel Computer System to Reduce Network Traffic - An apparatus and method for a database query optimizer to optimize a query that uses multiple networks. The query optimizer optimizes a query to reduce network traffic on a network or node that is overloaded or above an established parameter in a node/network attribute table. The query optimization to reduce network traffic may result in a sub-optimal query in other respects such as execution time. The result is a query optimizer that rewrites or optimizes a query to execute on multiple nodes or networks to reduce traffic on a network or node according to the loading characteristics and assigned attributes of a node or network. | 02-12-2009 |
| 20090043745 | Query Execution and Optimization with Autonomic Error Recovery from Network Failures in a Parallel Computer System with Multiple Networks - An apparatus and method for a database query execution monitor determines if an network error or low performance condition exists and then where possible modifies the query. The query execution monitor then determines an alternate query execution plan to continue execution of the query. The query optimizer can re-optimize the query to use a different network or node. Thus, the query execution monitor allows autonomic error recovery for network failures using an alternate query execution. The alternate query execution could also be determined at the initial optimization time and then this alternate plan used to execute a query in the case of a particular network failure. | 02-12-2009 |
| 20090043750 | Query Optimization in a Parallel Computer System with Multiple Networks - An apparatus and method for a database query optimizer to optimize a query that uses multiple networks. The database query optimizer optimizes a query that uses multiple networks to satisfy the query by splitting the query execution to use multiple networks. Thus, the query optimizer rewrites or optimizes a query to execute on multiple nodes or networks to more efficiently execute the query and reduce network traffic on a network. The query optimizer uses plan cache statistics to determine whether to use multiple networks to optimize the query. | 02-12-2009 |
| 20090043873 | Methods and Apparatus for Restoring a Node State - In one aspect of the invention, a method is provided. The method may include: (1) storing a snapshot of a system state of a node; (2) executing a job on the node; and (3) restoring the node to the system state using the stored snapshot of the system state. | 02-12-2009 |
| 20090043910 | Query Execution and Optimization Utilizing a Combining Network in a Parallel Computer System - An apparatus and method for a database query optimizer utilizes a combining network to optimize a portion of a query in a parallel computer system with multiple nodes. The efficiency of the parallel computer system is increased by offloading collective operations on node data to the global combining network. The global combining network performs collective operations such as minimum, maximum, sum, and logical functions such as OR and XOR. | 02-12-2009 |
| 20090067334 | MECHANISM FOR PROCESS MIGRATION ON A MASSIVELY PARALLEL COMPUTER - Embodiments off the invention provide a mechanism for process migration on a massively parallel computer system. In particular, embodiments of the invention may be used to update process state data for a migrated compute node, such as MPI (or other communication library) state data, across a full collection of compute nodes present in a given parallel system executing a parallel task. Migrating a process form one compute node to another may be useful to address a variety of sub-optimal operating conditions. For example, one or more processes may be migrated to cure network congestion resulting from a poorly mapped task or when a compute node is predicted to experience a hardware failure. | 03-12-2009 |
| 20090083276 | INSERTING DATA INTO AN IN-MEMORY DISTRIBUTED NODAL DATABASE - A method and apparatus loads data to an in-memory database across multiple nodes in a parallel computing system. A database loader uses SQL flags, historical information gained from monitoring prior query execution times and patterns, and node and network configuration to determine how to effectively cluster data attributes across multiple nodes. The database loader may also allow a system administrator to force placement of database structures in particular nodes. | 03-26-2009 |
| 20090112953 | ENHANCED GARBAGE COLLECTION IN A MULTI-NODE ENVIRONMENT - Embodiments of the invention enhance a garbage collection process running on a parallel system or distributed computing environment. Using a garbage collector in such an environment allows a more in-depth analysis to be performed than is possible on other systems. This is because the number of compute nodes present in many parallel systems, and the connections between them, allows the overhead of doing advanced analysis to be spread across the nodes and the results of that analysis to be shared among the nodes. | 04-30-2009 |
| 20090113438 | OPTIMIZATION OF JOB DISTRIBUTION ON A MULTI-NODE COMPUTER SYSTEM - A method and apparatus optimizes job and data distribution on a multi-node computing system. A job scheduler distributes jobs and data to compute nodes according to priority and other resource attributes to ensure the most critical work is done on the nodes that are quickest to access and with less possibility of node communication failure. In a tree network configuration, the job scheduler distributes critical jobs and data to compute nodes that are located closest to the I/O nodes. Other resource attributes include network utilization, constant data state, and class routing. | 04-30-2009 |
| 20090125611 | SHARING LOADED JAVA CLASSES AMONG A PLURALITY OF NODES - Methods, apparatus, and products are disclosed for sharing loaded Java classes among a plurality of nodes connected together for data communications using a data communication network, the plurality of nodes including an execution node and other nodes, that include: executing, by the execution node, a Java application, including identifying a Java class utilized for the Java application; determining, by the execution node, whether the Java class is already loaded on at least one of the other nodes; retrieving, by the execution node, the loaded Java class from the other nodes if the Java class is already loaded on at least one of the other nodes; and executing, by the execution node, the Java application using the loaded Java class retrieved from the other nodes. | 05-14-2009 |
| 20090125616 | OPTIMIZED PEER-TO-PEER FILE TRANSFERS ON A MULTI-NODE COMPUTER SYSTEM - A method and apparatus performs peer-to-peer file transfers on a High Performance Computing (HPC) cluster such as a Beowulf cluster. A peer-to-peer file tracker (PPFT) allows operating system, application and data files to be moved from a pre-loaded node to another node of the HPC cluster. A peer-to-peer (PTP) client is loaded into the nodes to facilitate PTP file transfers to reduce loading on networks, network switches and file servers to reduce the time needed to load the nodes with these files to increase overall efficiency of the multi-node computing system. The selection of the nodes participating in file transfers can be based on network topology, network utilization, job status and predicted network/computer utilization. This selection can be dynamic, changing during the file transfers as resource conditions change. The policies used to choose resources can be configured by an administrator. | 05-14-2009 |
| 20090125883 | NODE SELECTION FOR EXECUTING A JAVA APPLICATION AMONG A PLURALITY OF NODES - Methods, apparatus, and products are disclosed for node selection for executing a Java application among a plurality of nodes connected together for data communications using a data communication network, the plurality of nodes also connected to a service node, that include: tracking, by the service node, loaded Java classes currently loaded on each of the plurality of nodes; receiving, in the service node, an instruction to execute a Java application using the plurality of nodes; identifying, by the service node, Java classes utilized in executing the Java application; selecting, by the service node, one of the plurality of nodes for executing the Java application in dependence upon the loaded Java classes and the Java classes utilized in executing the Java application; and configuring, by the service node, the Java application for execution on the selected node. | 05-14-2009 |
| 20090132541 | MANAGING DATABASE RESOURCES USED FOR OPTIMIZING QUERY EXECUTION ON A PARALLEL COMPUTER SYSTEM - Embodiments of the invention may be used to increase query processing parallelism of an in-memory database stored on a parallel computing system. A group of compute nodes each store a portion of data as part of the in-memory database. Further, a pool of compute nodes may be reserved to create copies of data from the compute nodes of the in-memory database as part of query processing. When a query is received for execution, the query may be evaluated to determine whether portions of in-memory should be duplicated to allow multiple elements of the query (e.g., multiple query predicates) to be evaluated in parallel. | 05-21-2009 |
| 20090132609 | REAL TIME DATA REPLICATION FOR QUERY EXECUTION IN A MASSIVELY PARALLEL COMPUTER - Embodiments of the invention may be used to increase query processing parallelism of an in-memory database stored on a parallel computing system. A group of compute nodes each store a portion of data as part of the in-memory database. Further, a pool of compute nodes may be reserved to create copies of data from the compute nodes of the in-memory database as part of query processing. When a query is received for execution, the query may be evaluated to determine whether portions of in-memory should be duplicated to allow multiple elements of the query (e.g., multiple query predicates) to be evaluated in parallel. | 05-21-2009 |
| 20090158276 | DYNAMIC DISTRIBUTION OF NODES ON A MULTI-NODE COMPUTER SYSTEM - A method and apparatus dynamically distribute I/O nodes on a multi-node computing system. An I/O configuration mechanism located in the service node of a multi-node computer system controls the distribution of the I/O nodes. The I/O configuration mechanism uses job information located in a job record to initially configure the I/O node distribution. The I/O configuration mechanism further monitors the I/O performance of the executing job to then dynamically adjusts the I/O node distribution based on the I/O performance of the executing job. | 06-18-2009 |
| 20090240930 | Executing An Application On A Parallel Computer - Methods, systems, and products are disclosed for executing an application on a parallel computer including a plurality of nodes connected together through a data communications network. Each node has a plurality of processors capable of operating independently for serial processing and capable of operating symmetrically for parallel processing. The application has parallel segments for parallel processing and serial segments for serial processing. Embodiments of the invention include: booting up a first subset of the plurality of nodes in a serial processing mode; booting up a second subset of the plurality of nodes in a parallel processing mode; and executing the application on the plurality of nodes, including: migrating the application to the nodes booted up in the parallel processing mode upon encountering the parallel segments during execution, and migrating the application to the nodes booted up in the serial processing mode upon encountering the serial segments during execution. | 09-24-2009 |
| 20090265305 | Partial Indexes for Multi-Node Database - Embodiments of the invention enable a database spread over multiple nodes to allow each node to have different indexes over the data in tables, depending on how each node would benefit (or not benefit) from having the index(es). When a database table is spread across the nodes of a multi-node or distributed system, each node may maintain only the portion of the index relevant to that node, if doing so would improve the performance of query processing operations on that node. Further, the database may periodically redistributed across the compute nodes based on index performance. Doing so allows the database system to intelligently trade off between consuming space for the index on a node and the usefulness of having an index on that node. | 10-22-2009 |
| 20090265306 | Index Maintenance in a Multi-Node Database - Embodiments of the invention enable a database spread over multiple nodes to allow each node to have different indexes over the data in tables, depending on how each node would benefit (or not benefit) from having the index(es). When a database table is spread across the nodes of a multi-node or distributed system, each node may maintain only the portion of the index relevant to that node, if doing so would improve the performance of query processing operations on that node. Further, the database may periodically redistributed across the compute nodes based on index performance. Doing so allows the database system to intelligently trade off between consuming space for the index on a node and the usefulness of having an index on that node. | 10-22-2009 |
| 20090271588 | Migrating Program Objects in a Multi-Node Computer System - Embodiments of the invention enable application programs running across multiple compute nodes of a highly-parallel system to selectively migrate objects from one node to another. For example, when an object becomes too large, a node containing the object may migrate the object to another node, thereby freeing memory space. Whether a large object is migrated can be dependent on how frequently the object is used by the application. Because the memory used by such an object is freed for other uses by the application, overall application performance may be improved. On large parallel systems with thousands of compute nodes, even relatively small improvements in application performance an individual compute node may be magnified many times, resulting in dramatic improvements in overall application performance. | 10-29-2009 |
| 20090271595 | Configuring An Application For Execution On A Parallel Computer - Methods, systems, and products are disclosed for configuring an application for execution on a parallel computer that include: 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 deployment on the parallel computer, the application to identify the serial segments and the parallel segments of the application; and deploying the application for execution on the parallel computer in dependence upon the profile of the application and proximity within the data communications network of the nodes in the first subset relative to the nodes in the second subset. | 10-29-2009 |
| 20090271596 | Executing An Application On A Parallel Computer - 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. | 10-29-2009 |
| 20090271784 | Executing A Distributed Java Application On A Plurality Of Compute Nodes - 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. | 10-29-2009 |
| 20090271799 | Executing A Distributed Java Application On A Plurality Of Compute Nodes - 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. | 10-29-2009 |
| 20090271807 | Selectively Generating Program Objects on Remote Node of a Multi-Node Computer System - Embodiments of the invention enable application programs running across multiple compute nodes of a highly-parallel system to selectively migrate objects from one node to another. For example, when an object becomes too large, a node containing the object may migrate the object to another node, thereby freeing memory space. Whether a large object is migrated can be dependent on how frequently the object is used by the application. Because the memory used by such an object is freed for other uses by the application, overall application performance may be improved. On large parallel systems with thousands of compute nodes, even relatively small improvements in application performance an individual compute node may be magnified many times, resulting in dramatic improvements in overall application performance. | 10-29-2009 |
| 20090300752 | UTILIZING VIRTUAL PRIVATE NETWORKS TO PROVIDE OBJECT LEVEL SECURITY ON A MULTI-NODE COMPUTER SYSTEM - The disclosure herein provides data security on a parallel computer system using virtual private networks connecting the nodes of the system. A mechanism sets up access control data in the nodes that describes a number of security classes. Each security class is associated with a virtual network. Each user on the system is associated with one of the security classes. Each database object to be protected is given an attribute of a security class. Database objects are loaded into the system nodes that match the security class of the database object. When a query executes on the system, the query is sent to a particular class or set of classes such that the query is only seen by those nodes that are authorized by the equivalent security class. In this way, the network is used to isolate data from users that do not have proper authorization to access the data. | 12-03-2009 |
| 20090307287 | Database Journaling in a Multi-Node Environment - A database spread over multiple nodes allows each node to store a journal recording changes made to the database and also allows a journaling component to manage the memory space available for journaling. Two threshold size values may be specified for the journal. The first threshold value specifies a journal size at which to being pruning the journal on a given node. A journal pruning algorithm may be used to identify journal entries that may be removed. For example, once a given transaction completes (i.e., commits) the journal entries related to that transaction may be pruned from the journal. The second threshold value specifies the maximum size of the journal. After reaching this size, journal entries may be written to disk instead of the in-memory journal. | 12-10-2009 |
| 20090307290 | Database Journaling in a Multi-Node Environment - A database spread over multiple nodes allows each node to store a journal recording changes made to the database and also allows a journaling component to manage the memory space available for journaling. Two threshold size values may be specified for the journal. The first threshold value specifies a journal size at which to being pruning the journal on a given node. A journal pruning algorithm may be used to identify journal entries that may be removed. For example, once a given transaction completes (i.e., commits) the journal entries related to that transaction may be pruned from the journal. The second threshold value specifies the maximum size of the journal. After reaching this size, journal entries may be written to disk instead of the in-memory journal. | 12-10-2009 |
| 20090307466 | Resource Sharing Techniques in a Parallel Processing Computing System - A method, apparatus, and program product share a resource in a computing system that includes a plurality of computing cores. A request from a second execution context (“EC”) to lock the resource currently locked by a first EC on a first core causes replication of the second EC as a third EC on a third core. The first and third ECs are executed substantially concurrently. When the first EC modifies the resource, the third EC is restarted after the resource has been modified. Alternately, a first EC is configured in a first core and shadowed as a second EC in a second core. In response to a blocked lock request, the first EC is halted and the second EC continues. After granting a lock, it is determined whether a conflict has occurred and the first and second EC are particularly synchronized to each other in response to that determination. | 12-10-2009 |
| 20090313452 | MANAGEMENT OF PERSISTENT MEMORY IN A MULTI-NODE COMPUTER SYSTEM - A method and apparatus creates and manages persistent memory (PM) in a multi-node computing system. A PM Manager in the service node creates and manages pools of nodes with various sizes of PM. A node manager uses the pools of nodes to load applications to the nodes according to the size of the available PM. The PM Manager can dynamically adjust the size of the PM according to the needs of the applications based on historical use or as determined by a system administrator. The PM Manager works with an operating system kernel on the nodes to provide persistent memory for application data and system metadata. The PM Manager uses the persistent memory to load applications to preserve data from one application to the next. Also, the data preserved in persistent memory may be system metadata such as file system data that will be available to subsequent applications. | 12-17-2009 |
| 20090313636 | Executing An Application On A Parallel Computer - 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. | 12-17-2009 |
| 20090319621 | Message Flow Control in a Multi-Node Computer System - Embodiments of the invention provide for controlling message flow across a parallel computer system having multiple compute nodes by selectively grouping compute nodes of such a system into node pools and assigning message flow control policies to nodes in the node pools. The message flow control policies specify logging and/or tracing activities to be performed by instances of applications running on nodes assigned to the node pools. As the application is executed, logging and/or tracing messages are generated on the compute nodes according to message flow control policies assigned to the nodes. Optionally, the message flow is analyzed, the message flow control policies are adjusted, and duplicate messages are eliminated. | 12-24-2009 |
| 20090319662 | Process Migration Based on Exception Handling in a Multi-Node Environment - A process on a highly distributed parallel computing system is disclosed. When a first compute node in a first pool is ready to hand-off a task to second pool for further processing, the first compute node may first determine whether a node is available in the second pool. If no node is available from the second pool, then the first compute node may begin performing a primary task assigned to the second pool of nodes, up to the point where a service available exclusively to the nodes of the second pool is required. In the interim, however, one of the nodes of the second pool may become available. Alternatively, an application program running on a compute node may be configured with an exception handling routine that catches exceptions and migrates the application to a compute node where a necessary service is available, as such exceptions occur. | 12-24-2009 |
| 20090320003 | Sharing Compiler Optimizations in a Multi-Node System - Embodiments of the invention enable application programs running across multiple compute nodes of a highly-parallel system to compile source code into native instructions, and subsequently share the optimizations used to compile the source code with other nodes. For example, determining what optimizations to use may consume significant processing power and memory on a node. In cases where multiple nodes exhibit similar characteristics, it is possible that these nodes may use the same set of optimizations when compiling similar pieces of code. Therefore, when one node compiles source code into native instructions, it may share the optimizations used with other similar nodes, thereby removing the burden for the other nodes to figure out which optimizations to use. Thus, while one node may suffer a performance hit for determining the necessary optimizations, other nodes may be saved from this burden by simply using the optimizations provided to them. | 12-24-2009 |
| 20090320008 | Sharing Compiler Optimizations in a Multi-Node System - Embodiments of the invention enable application programs running across multiple compute nodes of a highly-parallel system to compile source code into native instructions, and subsequently share the optimizations used to compile the source code with other nodes. For example, determining what optimizations to use may consume significant processing power and memory on a node. In cases where multiple nodes exhibit similar characteristics, it is possible that these nodes may use the same set of optimizations when compiling similar pieces of code. Therefore, when one node compiles source code into native instructions, it may share the optimizations used with other similar nodes, thereby removing the burden for the other nodes to figure out which optimizations to use. Thus, while one node may suffer a performance hit for determining the necessary optimizations, other nodes may be saved from this burden by simply using the optimizations provided to them. | 12-24-2009 |
| 20090320023 | Process Migration Based on Service Availability in a Multi-Node Environment - A process on a highly distributed parallel computing system is disclosed. When a first compute node in a first pool is ready to hand-off a task to second pool for further processing, the first compute node may first determine whether a node is available in the second pool. If no node is available from the second pool, then the first compute node may begin performing a primary task assigned to the second pool of nodes, up to the point where a service available exclusively to the nodes of the second pool is required. In the interim, however, one of the nodes of the second pool may become available. Alternatively, an application program running on a compute node may be configured with an exception handling routine that catches exceptions and migrates the application to a compute node where a necessary service is available, as such exceptions occur. | 12-24-2009 |
| 20100063971 | UNIVERSAL ANNOTATION CONFIGURATION AND DEPLOYMENT - Systems and articles of manufacture for managing annotations made for a variety of different type data objects manipulated (e.g., created, edited, and viewed) by a variety of different type applications are provided. Some embodiments allow users collaborating on a project to create, view, and edit annotations from within the applications used to manipulate the annotated data objects, which may facilitate and encourage the capturing and sharing of tacit knowledge through annotations. Further, annotations may be stored separate from the application data they describe, decoupling the tacit knowledge captured in the annotations from the applications used to manipulate the annotated data. | 03-11-2010 |
| 20100085870 | GLOBAL DETECTION OF RESOURCE LEAKS IN A MULTI-NODE COMPUTER SYSTEM - 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. | 04-08-2010 |
| 20100085871 | RESOURCE LEAK RECOVERY IN A MULTI-NODE COMPUTER SYSTEM - 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. | 04-08-2010 |
| 20100095100 | Checkpointing A Hybrid Architecture Computing System - A method, apparatus, and program product checkpoint an application in a parallel computing system of the type that includes a plurality of hybrid nodes. Each hybrid node includes a host element and a plurality of accelerator elements. Each host element may include at least one multithreaded processor, and each accelerator element may include at least one multi-element processor. In a first hybrid node from among the plurality of hybrid nodes, checkpointing the application includes executing at least a portion of the application in the host element and at least one accelerator element and, in response to receiving a command to checkpoint the application, checkpointing the host element separately from the at least one accelerator element. | 04-15-2010 |
| 20100095152 | Checkpointing A Hybrid Architecture Computing System - A method, apparatus, and program product checkpoint an application in a parallel computing system of the type that includes a plurality of hybrid nodes. Each hybrid node includes a host element and a plurality of accelerator elements. Each host element may include at least one multithreaded processor, and each accelerator element may include at least one multi-element processor. In a first hybrid node from among the plurality of hybrid nodes, checkpointing the application includes executing at least a portion of the application in the host element, configuring and executing at least one computation kernel in at least one accelerator element, and, in response to receiving a command to checkpoint the application, checkpointing the host element separately from the at least one accelerator element upon which the at least one computation kernel is executing. | 04-15-2010 |
| 20100122199 | Using Accelerators in a Hybrid Architecture for System Checkpointing - A hybrid node of a High Performance Computing (HPC) cluster uses accelerator nodes for checkpointing to increase overall efficiency of the multi-node computing system. The host node or processor node reads/writes checkpoint data to the accelerators. After offloading the checkpoint data to the accelerators, the host processor can continue processing while the accelerators communicate the checkpoint data with the host or wait for the next checkpoint. The accelerators may also perform dynamic compression and decompression of the checkpoint data to reduce the checkpoint size and reduce network loading. The accelerators may also communicate with other node accelerators to compare checkpoint data to reduce the amount of checkpoint data stored to the host. | 05-13-2010 |
| 20100122256 | Scheduling Work in a Multi-Node Computer System Based on Checkpoint Characteristics - Efficient application checkpointing uses checkpointing characteristics of a job to determine how to schedule jobs for execution on a multi-node computer system. A checkpoint profile in the job description includes information on the expected frequency and duration of a check point cycle for the application. The checkpoint profile may be based on a user/administrator input as well as historical information. The job scheduler will attempt to group applications (jobs) that have the same checkpoint profile, on the same nodes or group of nodes. Additionally, the job scheduler may control when new jobs start based on when the next checkpoint cycle(s) are expected. The checkpoint monitor will monitor the checkpoint cycles, updating the checkpoint profiles of running jobs. The checkpoint monitor will also keep track of an overall system checkpoint profile to determine the available checkpointing capacity before scheduling jobs on the cluster. | 05-13-2010 |
| 20100180024 | REDUCING OCCURRENCES OF TWO-PHASE COMMITS IN A MULTI-NODE COMPUTING SYSTEM - Techniques are disclosed for reducing the number of two-phase commits required to perform atomic transactions in a multi-node system. By monitoring atomic operations that require two-phase commit protocols, a system may identify when it would be beneficial to consolidate data onto single (or at least fewer) compute node(s). In doing so, a less compute intensive commit protocol, such as a one-phase commit protocol may be used. Moreover, in situations where data consolidation is not available, the data may be migrated to compute nodes having a closer proximity. Thus, in such cases, network response times for two-phase commits required for an atomic operation may be reduced, thereby increasing the performance of a multi-node system. | 07-15-2010 |
| 20100205137 | Optimizing Power Consumption and Performance in a Hybrid Computer Evironment - A method for optimizing efficiency and power consumption in a hybrid computer system is disclosed. The hybrid computer system may comprise one or more front-end nodes connected to a multi-node computer system. Portions of an application may be offloaded from the front-end nodes to the multi-node computer system. By building historical profiles of the applications running on the multi-node computer system, the system can analyze the trade offs between power consumption and performance. For example, if running the application on the multi-node computer system cuts the run time by 5% but increases power consumption by 20% it may be more advantageous to simply run the entire application on the front-end. | 08-12-2010 |
| 20100205323 | Timestamp Synchronization for Queries to Database Portions in Nodes That Have Independent Clocks in a Parallel Computer System - A parallel computer system has multiple nodes that have independent clocks, where the different nodes may include different database portions that are referenced by a query. A timestamp parameter in a query is synchronized across the different nodes that are referenced by the query to assure the timestamps in the different nodes are consistent with each other notwithstanding the independent clocks used in each node. As a result, a database may be scaled to a parallel computer system with multiple nodes in a way that assures the timestamps for different nodes referenced during a query have identical values. | 08-12-2010 |
| 20100205578 | PROGRAM DEVELOPMENT TOOL CONFIGURED TO COMPILE SOURCE CODE ACCORDING TO ENERGY CONSUMPTION REQUIREMENTS - Embodiments of the invention provide techniques for presenting energy consumption information in an IDE tool. In one embodiment, the IDE tool may be configured to determine energy requirements associated with specific elements of the source code, and to present graphical indications of energy requirements along with those code elements. Such energy requirements may be determined by matching code elements to a stored data structure describing energy requirements for executing various code elements. The stored data may be based on predefined standards, and/or may be based on historical measurements of energy consumption during prior instances of executing code elements on a target computer system. Additionally, developers may specify priority for compiling portions of source code, according to desired energy requirements. | 08-12-2010 |
| 20100205591 | PRESENTING ENERGY CONSUMPTION INFORMATION IN AN INTEGRATED DEVELOPMENT ENVIRONMENT TOOL - Embodiments of the invention provide techniques for presenting energy consumption information in an IDE tool. In one embodiment, the IDE tool may be configured to determine energy requirements associated with specific elements of the source code, and to present graphical indications of energy requirements along with those code elements. Such energy requirements may be determined by matching code elements to a stored data structure describing energy requirements for executing various code elements. The stored data may be based on predefined standards, and/or may be based on historical measurements of energy consumption during prior instances of executing code elements on a target computer system. Additionally, developers may specify priority for compiling portions of source code, according to desired energy requirements. | 08-12-2010 |
| 20100205619 | ENVIRONMENT MODIFICATION IN A HYBRID NODE COMPUTING ENVIRONMENT - Embodiments of the invention provide techniques that improve resource management on a massively parallel computing system having a plurality of hybrid compute nodes. For example, a job scheduler may be provided which determines a library to link to an application based on system and user requirements. In one embodiment, the libraries may provide optimizations for job execution time, and also provide optimizations directed towards a specific processor architecture. Once the library is determined, the job scheduler may configure the environment of the application so that the application links with the optimized library during run-time. Doing so may improve overall system performance of the massively parallel computing system. | 08-12-2010 |
| 20100241881 | Environment Based Node Selection for Work Scheduling in a Parallel Computing System - A method, apparatus, and program product manage scheduling of a plurality of jobs in a parallel computing system of the type that includes a plurality of computing nodes and is disposed in a data center. The plurality of jobs are scheduled for execution on a group of computing nodes from the plurality of computing nodes based on the physical locations of the plurality of computing nodes in the data center. The group of computing nodes is further selected so as to distribute at least one of a heat load and an energy load within the data center. The plurality of jobs may be additionally scheduled based upon an estimated processing requirement for each job of the plurality of jobs. | 09-23-2010 |
| 20100241884 | Power Adjustment Based on Completion Times in a Parallel Computing System - A method, apparatus, and program product optimize power consumption in a parallel computing system that includes a plurality of computing nodes by selectively throttling performance of selected nodes to effectively slow down the completion of quicker executing parts of a workload of the computing system when those parts are dependent upon or otherwise associated with the completion of other, slower executing parts of the same workload. Parts of the workload are executed on the computing nodes, including concurrently executing a first part on a first computing node and a second part on a second computing node. The first node is selectively throttled during execution of the first part to decrease power consumption of the first node and conform a completion time of for the first node in completing the first part of the workload with a completion time for the second node in completing the second part. | 09-23-2010 |
