This description relates to managing task execution.
A data processing system typically stores, manages, processes, and analyzes data. A data processing system may simply handle one or more tasks scheduled to be completed at a certain time. Alternatively, a data processing system may be a large-scale customer relationship management system. Simple or complex, a data processing system often includes one or more components, such as processing elements, input data, and output data. The processing elements of a data processing system determine the function of the data processing system, for example, data warehouse, customer relationship management, and data mining, etc. Input data of a data processing system can come from many sources. For example, input data may come from flat files, database tables, operational systems, etc. Input data may also come from the Internet, carrying information from one system to another. Output data of a data processing system are what the processing elements generate. Formats of output data vary depending on the processing elements that generate them.
In one aspect, in general, a method for managing task execution includes receiving a specification of a plurality of tasks to be performed by respective functional modules; processing a flow of input data using a dataflow graph that includes nodes representing data processing components connected by links representing flows of data between data processing components; in response to at least one flow of data provided by at least one data processing component, generating a flow of messages; and in response to each of the messages in the flow of messages, performing an iteration of a set of one or more tasks using one or more corresponding functional modules.
Aspects can include one or more of the following features.
At least one of the functional modules is configured to initiate execution of the dataflow graph.
The specification of the plurality of tasks specifies dependency relationships between the at least two of the tasks.
A dependency relationship between the at least two tasks defines at least a partial ordering for execution of the functional modules corresponding to the tasks.
A dependency relationship between the at least two tasks defines conditional logic for determine at least one condition upon which execution of at least one of the functional modules is based.
At least one of the functional modules includes a fault-handling module that is executed when the conditional logic detects that a fault has occurred in execution of one of the other functional modules.
Multiple iterations of a given set of one or more tasks are executed concurrently in response to two or more messages in the flow of messages.
One or more of the messages in the flow of messages is generated in response to an element of data in the flow of data without including the element of data.
One or more of the messages in the flow of messages includes at least a portion of an element of data in the flow of data.
At least one of the functional modules is configured to send an acknowledgement in response to receiving one of the messages in the flow of messages.
At least one of the data processing components resends an unacknowledged message.
The method further includes storing a parameter value identifying the specification of a plurality of tasks.
The method further includes transmitting the generated flow of messages to an application for receiving the messages identified by the parameter value.
The method further includes storing messages received by the application in parameters visible to multiple processes for performing the tasks.
In another aspect, in general, a system for managing task execution includes: a task managing system including circuitry for receiving a specification of a plurality of tasks to be performed by respective functional modules; and a data processing system including circuitry for processing a flow of input data using a dataflow graph that includes nodes representing data processing components connected by links representing flows of data between data processing components. The data processing system is configured to generate a flow of messages in response to at least one flow of data provided by at least one data processing component. The task managing system is configured to perform an iteration of a set of one or more tasks using one or more corresponding functional modules in response to each of the messages in the flow of messages.
In another aspect, in general, a system for managing task execution includes: means for receiving a specification of a plurality of tasks to be performed by respective functional modules; and means for processing a flow of input data using a dataflow graph that includes nodes representing data processing components connected by links representing flows of data between data processing components. The data processing to system is configured to generate a flow of messages in response to at least one flow of data provided by at least one data processing component. The task managing system is configured to perform an iteration of a set of one or more tasks using one or more corresponding functional modules in response to each of the messages in the flow of messages.
In another aspect, in general, a computer-readable medium stores a computer program for managing task execution. The computer program includes instructions for causing a computer to: receive a specification of a plurality of tasks to be performed by respective functional modules; process a flow of input data using a dataflow graph that includes nodes representing data processing components connected by links representing flows of data between data processing components; in response to at least one flow of data provided by at least one data processing component, generate a flow of messages; and in response to each of the messages in the flow of messages, perform an iteration of a set of one or more tasks using one or more corresponding functional modules.
Aspects can include one or more of the following advantages.
The techniques enable data flow to be converted into control flow and can facilitate data processing situations where incoming data are continuous and unpredictable and each piece of data may need elaborate handling.
Dataflow graphs can be incorporated into the control flow of a task managing application, allowing different dataflow graphs for data processing based on the values stored in the incoming message generated in response to elements of a data flow.
Having separate development environments for data processing and task management allows development of data processing applications and task managing applications to be sandboxed into independent environments that do not interfere with each other.
Since data processing applications often emphasize data availability, data transformation, and data integrity, and task managing applications often emphasize error handling, system resource allocation, and computation order, using separate graphical development tools in a complex data processing system for developing data processing applications and task managing applications allow each tool to meet the unique requirements of each type of the applications.
Having a separate data processing application and task managing application also facilitates software reuse.
In a complex data processing system, data may come from diverse external sources and take on different formats. Incoming data may be corrupted and error checking may be used to ensure data integrity. A separate data processing application that handles reformatting and error checking encapsulates and isolates this complexity from a downstream task managing application, allowing task managing application to be developed without specific knowledge of possible data sources and to be reused when data sources or formats are changed. Likewise data processing applications can be developed with a focus on the data sources and without specific knowledge of the downstream computation environment and can be reused even when downstream handling has been changed.
Other features and advantages of the invention will become apparent from the following description, and from the claims.
The data processing system 120 in
A complex data processing system, such as the one shown in
Applications in a complex data processing system tend to specialize. For example, some applications may mainly handle data processing and some may mainly handle task managing. Data processing applications usually handle data-related computations, such as reformatting, sorting, and organizing data. Data processing applications tend to have a focus on how data flow from a source to a destination and how data are transformed in the process. Task managing applications usually handle scheduling and initiating execution of computation-related jobs, such as executing programs, scheduling events, managing processes, and dealing with faulty conditions. Task managing applications tend to have an emphasis on how control flows from task to task and how control flow is affected by conditional logic and faulty conditions.
Data processing applications and task managing applications typically have different characteristics. Development environments for these two types of applications may be the same or separate. An exemplary development environment for a data processing application is a graph-based computation environment described below.
A graph-based computation environment allows a programmer to build a graph-based application by using components as building blocks. A graph-based application is often represented by a directed graph, with nodes (or “vertices”) in the graph representing components (either data storage components or executable computation components), and the directed links (or “edges”) in the graph representing flows of data between components. A dataflow graph (also called simply a “graph”) is a modular entity. Each graph can be made up of one or more other graphs, and a particular graph can be a component in a larger graph. A graphical development environment (GDE) provides a user interface for developers to develop, test, and deploy applications as executable graphs that are tailored to a given user-specific environment.
A dataflow graph, such as graph 200, embodies the data processing aspects of a data processing application such as, for example, where the data come from, what transformations the data undergo, and where the data arrive.
As a comparison,
Load Transactions Program 304 is a functional module that includes executable code e.g., a script in Python or Perl. Distribute Mail Conditional Task 308 is an implementation of conditional logic, directing the control to either a Top Customers Graph 310, or a Credit SubPlan 312, or a Bottom Customers Graph 314 depending on whether a particular customer is classified as a top customer or a bottom customer or a customer who needs credit extension. Credit SubPlan 312 and Charge SubPlan 316 are themselves control flow diagrams. The functional modules are connected with arrow links, 322, 324, etc. The arrow links specify dependency relationships among the tasks performed by the functional modules and thus indicate how control flows from one functional module to another and define at least a partial ordering according to which the functional modules run. For example, Demographic Graph 302 is run before Mailing Graph 306.
A control flow diagram, such as diagram 300, embodies the control aspects of the task managing application controlled by the control flow diagram. Control aspects of a task managing application include, for example, determining running sequences among different tasks and applying conditional logic.
As mentioned above, a complex data processing system may need to manage large volumes of data as well as perform numerous computations. In a complex data processing system, both task managing applications and data processing applications may be used.
For example, in the call center system 120 shown in
When data processing is a multi-step process that involves parallel processing, conditional logic, and/or fault handling, a simple dataflow graph may not be the best approach to capture the complexity of the multi-step process. It may be advantageous to convert data flow to control flow at a certain stage during the process.
For example, a complex data processing system, such as the call center system 120 shown in
In
Different mechanisms can be used to transmit a message from the data processing application 410 to the task managing application 450, for example, message passing, queues, shared memory space, remote procedure calls. The task managing application 450, based on the messages or certain values contained in the messages, can invoke different processes, such as a process executing a Plan 442, a SubPlan 444, and/or a dataflow graph 446.
In some cases the task managing application 450 invokes a separate iteration of a corresponding set of one or more tasks (e.g., Plan 442, SubPlan 444, or dataflow graph 446) for each incoming message received from the data processing application 410. So if each message is generated in response to an element of data generated as output of the data processing application 410, the application 450 is able to iterate for each element of data. A loop index increments for each iteration of the task managing application 450. In each loop iteration, a process associated with the current loop index is spun off to handle an incoming message. Depending on the message received by the task managing application 450 or a value contained in the message, the process spun off to handle an incoming message can execute a dataflow graph, or a SubPlan, or any program for performing a set of one or more tasks.
In the illustrated example, for the first element of incoming warehouse data 402 processed by the data processing application 410, a message 422 is generated by the data processing application 410 and transmitted to the task managing application 450. The task managing application 450 being in its first loop iteration (with loop index 0), spins off a child process 452 to handle the message 442. The process 452 corresponds to the Plan 442, evoked by the task managing application 450 to reduce the number of merchandise available. A child process 454 is initiated in a second loop iteration associated with loop index 1 of the task managing application 450 to handle the second element of incoming data, generated in response to the manufacturing data 404. The child process 454 may correspond to the SubPlan 444, which, for example, performs the task of increasing the number of merchandise available. A child process 456 is initiated in a third loop iteration associated with loop index 2 to handle the third element of incoming data, generated in response to the retail store sales data 406. The child process 456 may correspond to executing the dataflow graph 446. The task managing application may be configured to invoke the processes, 452, 454, and 456, concurrently or serially.
Processes may refer to processes that run on different CPUs or on the same CPU. In the latter case, the processes may also be known as “threads”.
For increased reliability, the task managing application 450 may be configured to send an acknowledgement to the data processing application 410 when it receives a message. The acknowledgement can be a positive acknowledgement if the task managing application decides that the message received is intact or a negative one if the task managing application decides that the message received is corrupted.
The data processing application 410 can be configured to wait for an acknowledgement that the last-sent message has been received before sending the next message. It can be further configured to send the next message upon receiving a positive acknowledgement and re-send the last message upon receiving a negative acknowledgement.
The system 500 also includes a database 520. The database 520 may be a scalable object-oriented database system that provides storage for various kinds of information (e.g., metadata) for the system 500. The database 520 may be, for example, an enterprise metadata database, which can support the development and execution of graph-based applications and the interchange of data between the graph-based applications and other systems, e.g., operating systems.
The system 500 further includes an operating system 524. The operating system 524 may be, for example, a parallel operating environment. The operating system 524 provides support for running application development environments, such as GDE 512 and GDE 514, and provides for scalable parallel and distributed execution of the applications developed.
In
After being reformatted, the data flow out of the data processing application 518 and into the task managing application 516, and are used to drive the task managing application 516 driven by the control flow diagram 550. The control flow diagram 550 shows two tasks, task 552 and task 554. A task may be a computation performed, for example, by executing a dataflow graph or a script, such as a Perl script. A time sequence 556 shows the running sequence of the tasks specified in the control flow diagram 550. In this case, the task 552 is executed before the task 554.
As shown in
In some examples, the above five methods may be implemented as follows.
Method Trigger may be implemented to represent the starting point of the task 554. It may contain the condition for starting the execution. The condition may be whether a specific file exists, or whether a flag has been set to true.
Method At Start may be implemented as a method that prepares the system for the method Perform, such as setting environmental variables to desired values, or setting up log files to log runtime information.
Method Perform may be implemented to perform the main functionality of the task 554. Task 554 may also contain conditional logic to handle what happens after method Perform. If method Perform succeeds during its execution, method At Success is executed to exit task 554 with a return code of zero. If method Perform fails during its execution, method At Failure is executed to exit task 554 with a return code of non-zero. Optionally, additional methods can be added for rollback, error handling, and recovery. For example, a method of rollback can be added to roll back what has been done in reverse execution order starting at the point of failure. Alternatively. a method of cleanup can be added to clean up the failed conditions, by resetting flags, registers, etc.
To handle iterative incoming data, a looping SubPlan can be used. In some implementations, a task managing application is configured to include a looping SubPlan. As shown in
Suppose that we have a business that involves processing customer transactions that arrive continuously and unpredictably. A developer can construct a data processing application 702 to handle data formatting and other preparation work, and a task managing application 704 to perform tasks to further process the data. After the data processing application and the task managing application have been constructed, the data processing application can be configured to pass data to the task managing application and the task managing application can be configured to listen for messages that are coming from the data processing application. In some implementations, messages passed between the data processing application and the task managing application may include data output by the data processing application (e.g., encapsulated and/or encrypted in messages). In some implementations, messages passed between the data processing application and the task managing application can be generated in response to data from the data processing application without including the output data itself. Thus, the term “message” can refer to information passed between the data processing application and the task managing application in any form or format.
On the task managing side, the task managing application 704 includes a looping set of one or more tasks (e.g., a SubPlan) that listens continuously for messages from the data processing application 702. Symbol 706 is a symbol indicating that the application is running iteratively. A message arriving for the task managing application 704 triggers a new loop iteration in which a process can be spun off. The task managing application 704 can be configured to wait until the last loop iteration finishes before starting a new loop iteration or to start a new iteration immediately upon the receipt of a message. In the latter case, processes spun out of each iteration run concurrently.
On the data processing side, a user can configure a message-transmitting application (e.g., a dataflow graph) to “talk” to a counterpart listening application, which in this case is the task managing application 704. In some implementations, the message-transmitting application defines a parameter that holds the name of the counterpart listening application so the message-transmitting application knows where to send messages.
As mentioned before, having a separate data processing application and task managing application provides the advantage of software re-use. However when the task managing application, i.e., the counterpart listening application, has been replaced by a new task managing application, the parameter in the message transmitting application that holds the name of the counterpart listening application needs to be updated correspondingly. A user may need to open the message-transmitting application and make the required change.
To avoid the need of opening the message transmitting application every time the task managing application has been replaced by a new application, parameter Name_of_Listening_Application can be made visible to both the message transmitting application and any counterpart listening application. In the listening application, parameter Name_of_Listening_Application is assigned the value of the listening application's name. Because the parameter is also visible to the message transmitting application, the message transmitting application can read the value of parameter Name_of_Listening_Application to find out the application to which it is supposed to send message. In this way, the listening application can be changed even at run time without any need of opening the message transmitting application for updates.
In some implementations, the listening application stores the received messages in parameters. A parameter of a process defines a system setting for that process. In some cases, a parameter of a parent process can be inherited by and therefore visible to its child processes. For example, parameter 720 in
Optionally, the user can construct a program or a method on the task managing side to kick off the message-transmitting application, as shown in
When the task managing application 722 starts running, the starter program 726 initiates the data processing applications 732 and 734. In the meantime, the listening program 704 begins listening for messages from the message-transmitting data processing application 702. In some implementations, the data processing applications 732 and 734 and the task managing application 722 may be configured to run on the same host. The data processing applications 732 and 734 and the task managing application 722 may also include various error-handling methods, such as rollback, recovery, clean-up, and acknowledgements and message tracking that are used to make message transmitting resilient to failures, as demonstrated in
In
In
When the publisher sends a message with a sequence number X, it may wait for an acknowledgement for the message. When it receives the acknowledgement that contains the sequence number X, it sends the next message of a sequence number X+1 if the acknowledgement is positive or resends the message of the sequence number X if the acknowledgement is negative.
Alternatively, the publisher may send messages without waiting for acknowledgements of previously sent messages. The publisher may store unacknowledged messages and resend the messages if no acknowledgement has been received within a certain period of time. The subscriber can be programmed to ignore messages with the same sequence number so that receiving a repeated message will not cause a problem.
If the system were to crash at some point, the publisher can resend the unacknowledged messages on recovery. The unacknowledged messages can be stored in a persistent storage, such as a disk, if it is desired that the data survive system failures.
Other methods or techniques can be used to ensure that each message is transmitted successfully.
The approach described above can be implemented using software for execution on a computer. For instance, the software forms procedures in one or more computer programs that execute on one or more programmed or programmable computer systems (which may be of various architectures such as distributed, client/server, or grid) each including at least one processor, at least one data storage system (including volatile and non-volatile memory and/or storage elements), at least one input device or port, and at least one output device or port. The software may form one or more modules of a larger program, for example, that provides other services related to the design and configuration of computation graphs. The nodes and elements of the graph can be implemented as data structures stored in a computer readable medium or other organized data conforming to a data model stored in a data repository.
The software may be provided on a storage medium, such as a CD-ROM, readable by a general or special purpose programmable computer or delivered (encoded in a propagated signal) over a communication medium of a network to the computer where it is executed. All of the functions may be performed on a special purpose computer, or using special-purpose hardware, such as coprocessors. The software may be implemented in a distributed manner in which different parts of the computation specified by the software are performed by different computers. Each such computer program is preferably stored on or downloaded to a storage media or device (e.g., solid state memory or media, or magnetic or optical media) readable by a general or special purpose programmable computer, for configuring and operating the computer when the storage media or device is read by the computer system to perform the procedures described herein. The inventive system may also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer system to operate in a specific and predefined manner to perform the functions described herein.
A number of embodiments of the invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. For example, some of the steps described above may be order independent, and thus can be performed in an order different from that described.
It is to be understood that the foregoing description is intended to illustrate and not to limit the scope of the invention, which is defined by the scope of the appended claims. For example, a number of the function steps described above may be performed in a different order without substantially affecting overall processing. Other embodiments are within the scope of the following claims.
This application is a continuation of U.S. application Ser. No. 12/704,998, filed on Feb. 12, 2010, which claims priority to U.S. application Ser. No. 61/152,669, filed on Feb. 13, 2009, the entire contents of each of which are incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
3662401 | Collins et al. | May 1972 | A |
4228496 | Katzman et al. | Oct 1980 | A |
4922418 | Dolecek | May 1990 | A |
4972314 | Getzinger et al. | Nov 1990 | A |
5127104 | Dennis | Jun 1992 | A |
5276899 | Schneiderman | Jan 1994 | A |
5280619 | Wang | Jan 1994 | A |
5323452 | Dickman et al. | Jun 1994 | A |
5495590 | Comfort et al. | Feb 1996 | A |
5504900 | Raz | Apr 1996 | A |
5630047 | Wang | May 1997 | A |
5692168 | McMahan | Nov 1997 | A |
5701400 | Amardo | Dec 1997 | A |
5712971 | Stanfill et al. | Jan 1998 | A |
5745778 | Alfieri | Apr 1998 | A |
5799266 | Hayes | Aug 1998 | A |
5802267 | Shirakihara et al. | Sep 1998 | A |
5805462 | Poirot et al. | Sep 1998 | A |
5857204 | Lordi et al. | Jan 1999 | A |
5923832 | Shirakihara et al. | Jul 1999 | A |
5930794 | Linenbach et al. | Jul 1999 | A |
5933640 | Dion | Aug 1999 | A |
5950212 | Anderson et al. | Sep 1999 | A |
5966072 | Stanfill et al. | Oct 1999 | A |
5999729 | Tabloski, Jr. et al. | Dec 1999 | A |
6006242 | Poole et al. | Dec 1999 | A |
6012094 | Leyman | Jan 2000 | A |
6014670 | Zamanian et al. | Jan 2000 | A |
6016516 | Horikiri | Jan 2000 | A |
6032158 | Mukhopadhhyay et al. | Feb 2000 | A |
6038558 | Powers et al. | Mar 2000 | A |
6044211 | Jain | Mar 2000 | A |
6044374 | Nesamoney et al. | Mar 2000 | A |
6088716 | Stanfill et al. | Jul 2000 | A |
6173276 | Kant et al. | Jan 2001 | B1 |
6208345 | Sheard et al. | Mar 2001 | B1 |
6256637 | Venkatesh et al. | Jul 2001 | B1 |
6259988 | Galkowski et al. | Jul 2001 | B1 |
6272650 | Meyer et al. | Aug 2001 | B1 |
6301601 | Helland | Oct 2001 | B1 |
6314114 | Coyle et al. | Nov 2001 | B1 |
6324437 | Frankel et al. | Nov 2001 | B1 |
6330008 | Razdow et al. | Dec 2001 | B1 |
6332212 | Organ et al. | Dec 2001 | B1 |
6339775 | Zamanian et al. | Jan 2002 | B1 |
6400996 | Hoffberg et al. | Jun 2002 | B1 |
6401216 | Meth et al. | Jun 2002 | B1 |
6437796 | Sowizral et al. | Aug 2002 | B2 |
6449711 | Week | Sep 2002 | B1 |
6480876 | Rehg et al. | Nov 2002 | B2 |
6496961 | Gupta et al. | Dec 2002 | B2 |
6538651 | Hayman et al. | Mar 2003 | B1 |
6584581 | Bay et al. | Jun 2003 | B1 |
6608628 | Ross et al. | Aug 2003 | B1 |
6611862 | Reisman | Aug 2003 | B2 |
6640244 | Bowman-Amuah | Oct 2003 | B1 |
6651234 | Gupta et al. | Nov 2003 | B2 |
6654907 | Stanfill et al. | Nov 2003 | B2 |
6658464 | Reisman | Dec 2003 | B2 |
6728879 | Atkinson | Apr 2004 | B1 |
6760903 | Morshed et al. | Jul 2004 | B1 |
6813761 | Das et al. | Nov 2004 | B1 |
6816825 | Ashar et al. | Nov 2004 | B1 |
6832369 | Kryka et al. | Dec 2004 | B1 |
6848100 | Wu et al. | Jan 2005 | B1 |
6879946 | Rong et al. | Apr 2005 | B2 |
7062483 | Ferrari et al. | Jun 2006 | B2 |
7082604 | Schneiderman | Jul 2006 | B2 |
7085426 | August | Aug 2006 | B2 |
7103597 | McGovern | Sep 2006 | B2 |
7103620 | Kunz et al. | Sep 2006 | B2 |
7130484 | August | Oct 2006 | B2 |
7137116 | Parkes et al. | Nov 2006 | B2 |
7164422 | Wholey et al. | Jan 2007 | B1 |
7165030 | Yi et al. | Jan 2007 | B2 |
7167850 | Stanfill | Jan 2007 | B2 |
7316001 | Gold et al. | Jan 2008 | B2 |
7356819 | Ricart et al. | Apr 2008 | B1 |
7398514 | Russell | Jul 2008 | B2 |
7412658 | Gilboa | Aug 2008 | B2 |
7417645 | Beda et al. | Aug 2008 | B2 |
7457984 | Kutan | Nov 2008 | B2 |
7467383 | Inchingolo et al. | Dec 2008 | B2 |
7505975 | Luo | Mar 2009 | B2 |
7577628 | Stanfill | Aug 2009 | B2 |
7594220 | Kodosky et al. | Sep 2009 | B2 |
7636699 | Stanfill | Dec 2009 | B2 |
7716630 | Wholey et al. | May 2010 | B2 |
7756940 | Sagawa | Jul 2010 | B2 |
7840949 | Schumacher et al. | Nov 2010 | B2 |
7870556 | Wholey et al. | Jan 2011 | B2 |
7877350 | Stanfill et al. | Jan 2011 | B2 |
7979479 | Staebler et al. | Jul 2011 | B2 |
8286176 | Baumback et al. | Oct 2012 | B1 |
8396886 | Tsimelzon et al. | Mar 2013 | B1 |
8566641 | Douros et al. | Oct 2013 | B2 |
9274926 | Larson et al. | Mar 2016 | B2 |
9886319 | Wakeling | Feb 2018 | B2 |
20010055019 | Sowizral et al. | Dec 2001 | A1 |
20020080181 | Razdow et al. | Jun 2002 | A1 |
20020091747 | Rehg et al. | Jul 2002 | A1 |
20020091748 | Rehg et al. | Jul 2002 | A1 |
20020107743 | Sagawa | Aug 2002 | A1 |
20020111876 | Rudraraju et al. | Aug 2002 | A1 |
20020129340 | Tuttle | Sep 2002 | A1 |
20020147745 | Houben et al. | Oct 2002 | A1 |
20020184616 | Chessell et al. | Dec 2002 | A1 |
20030004771 | Yaung | Jan 2003 | A1 |
20030023413 | Srinivasa | Jan 2003 | A1 |
20030033432 | Simpson et al. | Feb 2003 | A1 |
20030091055 | Craddock et al. | May 2003 | A1 |
20030126240 | Vosseler | Jul 2003 | A1 |
20040006745 | Van Heldan et al. | Jan 2004 | A1 |
20040041838 | Adusumilli et al. | Mar 2004 | A1 |
20040073529 | Stanfill | Apr 2004 | A1 |
20040093559 | Amaru et al. | May 2004 | A1 |
20040098452 | Brown et al. | May 2004 | A1 |
20040107414 | Bronicki et al. | Jun 2004 | A1 |
20040111469 | Manion et al. | Jun 2004 | A1 |
20040148373 | Childress et al. | Jul 2004 | A1 |
20040177099 | Ganesh et al. | Sep 2004 | A1 |
20040205726 | Chedgey et al. | Oct 2004 | A1 |
20040207665 | Mathur | Oct 2004 | A1 |
20040225657 | Sarkar | Nov 2004 | A1 |
20040260590 | Golani et al. | Dec 2004 | A1 |
20050021689 | Marvin et al. | Jan 2005 | A1 |
20050033720 | Verma et al. | Feb 2005 | A1 |
20050034112 | Stanfill | Feb 2005 | A1 |
20050039176 | Fournie | Feb 2005 | A1 |
20050059046 | Labrenz et al. | Mar 2005 | A1 |
20050086360 | Mamou et al. | Apr 2005 | A1 |
20050097515 | Ribling | May 2005 | A1 |
20050097561 | Schumacher et al. | May 2005 | A1 |
20050102325 | Gould et al. | May 2005 | A1 |
20050114778 | Branson et al. | May 2005 | A1 |
20050144277 | Flurry et al. | Jun 2005 | A1 |
20050144596 | McCullough et al. | Jun 2005 | A1 |
20050149935 | Benedetti | Jul 2005 | A1 |
20050172268 | Kuturiano et al. | Aug 2005 | A1 |
20050177531 | Bracewell | Aug 2005 | A1 |
20050193056 | Schaefer et al. | Sep 2005 | A1 |
20050216421 | Barry et al. | Sep 2005 | A1 |
20050240621 | Robertson et al. | Oct 2005 | A1 |
20050262470 | Gavrilov | Nov 2005 | A1 |
20050289527 | Illowsky et al. | Dec 2005 | A1 |
20060085462 | Todd | Apr 2006 | A1 |
20060095722 | Biles et al. | May 2006 | A1 |
20060130041 | Pramanick et al. | Jun 2006 | A1 |
20060206872 | Krishnaswamy | Sep 2006 | A1 |
20060282474 | MacKinnon | Dec 2006 | A1 |
20060294150 | Stanfill et al. | Dec 2006 | A1 |
20060294459 | Davis et al. | Dec 2006 | A1 |
20070011668 | Wholey et al. | Jan 2007 | A1 |
20070022077 | Stanfill | Jan 2007 | A1 |
20070035543 | David et al. | Feb 2007 | A1 |
20070094211 | Sun et al. | Apr 2007 | A1 |
20070118839 | Berstis et al. | May 2007 | A1 |
20070139441 | Lucas et al. | Jun 2007 | A1 |
20070143360 | Harris et al. | Jun 2007 | A1 |
20070150429 | Huelsman et al. | Jun 2007 | A1 |
20070174185 | McGovern | Jul 2007 | A1 |
20070198971 | Dasu | Aug 2007 | A1 |
20070239766 | Papaefstathiou et al. | Oct 2007 | A1 |
20070271381 | Wholey et al. | Nov 2007 | A1 |
20070271562 | Schumacher et al. | Nov 2007 | A1 |
20070279494 | Aman et al. | Dec 2007 | A1 |
20070285440 | MacInnis et al. | Dec 2007 | A1 |
20080049022 | Sherb et al. | Feb 2008 | A1 |
20080126755 | Wu et al. | May 2008 | A1 |
20080134138 | Chamieh | Jun 2008 | A1 |
20080244524 | Kelso | Oct 2008 | A1 |
20080250049 | Chakra et al. | Oct 2008 | A1 |
20080288608 | Johnson | Nov 2008 | A1 |
20080294615 | Furuya et al. | Nov 2008 | A1 |
20090030863 | Stanfill et al. | Jan 2009 | A1 |
20090064147 | Beckerle et al. | Mar 2009 | A1 |
20090083313 | Stanfill et al. | Mar 2009 | A1 |
20090113196 | Jan et al. | Apr 2009 | A1 |
20090182728 | Anderson | Jul 2009 | A1 |
20090193391 | Miller et al. | Jul 2009 | A1 |
20090193417 | Kahlon | Jul 2009 | A1 |
20090224941 | Kansal et al. | Sep 2009 | A1 |
20090235267 | McKinney et al. | Sep 2009 | A1 |
20090245426 | Ratnaker et al. | Oct 2009 | A1 |
20090327196 | Studer et al. | Dec 2009 | A1 |
20100042976 | Hines | Feb 2010 | A1 |
20100070955 | Kahlon | Mar 2010 | A1 |
20100169137 | Jastrebski et al. | Jul 2010 | A1 |
20100174694 | Staebler et al. | Jul 2010 | A1 |
20100180344 | Malyshev et al. | Jul 2010 | A1 |
20100211953 | Wakeling et al. | Aug 2010 | A1 |
20100218031 | Agarwal et al. | Aug 2010 | A1 |
20100281462 | Festa | Nov 2010 | A1 |
20100281488 | Krishnamurthy et al. | Nov 2010 | A1 |
20110078500 | Douros et al. | Mar 2011 | A1 |
20110093433 | Stanfill et al. | Apr 2011 | A1 |
20110307897 | Atterbury et al. | Dec 2011 | A1 |
20120023508 | Flores et al. | Jan 2012 | A1 |
20120036498 | Akirekadu et al. | Feb 2012 | A1 |
20120054255 | Buxbaum | Mar 2012 | A1 |
20120102029 | Larson et al. | Apr 2012 | A1 |
20120151419 | Kent et al. | Jun 2012 | A1 |
20120216176 | Gaikwad et al. | Aug 2012 | A1 |
20120222017 | Hinkle | Aug 2012 | A1 |
20120233599 | Valdiviezo et al. | Sep 2012 | A1 |
20120266074 | Mukundan | Oct 2012 | A1 |
20130124392 | Achanta | May 2013 | A1 |
20130290928 | Johnson | Oct 2013 | A1 |
20140068566 | Coronado et al. | Mar 2014 | A1 |
Number | Date | Country |
---|---|---|
2014262225 | Dec 2014 | AU |
1965296 | May 2007 | CN |
101702942 | May 2010 | CN |
0834810 | Apr 1998 | EP |
3287896 | Feb 2018 | EP |
64-013189 | Jan 1989 | JP |
06-236276 | Aug 1994 | JP |
H08-106540 | Apr 1996 | JP |
08-278892 | Oct 1996 | JP |
08-305576 | Nov 1996 | JP |
63-231613 | Sep 1998 | JP |
11-184766 | Jul 1999 | JP |
2000-010788 | Jan 2000 | JP |
2000-99317 | Apr 2000 | JP |
2000-514219 | Oct 2000 | JP |
2001-022571 | Jan 2001 | JP |
2002-229943 | Aug 2002 | JP |
2005-317010 | Nov 2005 | JP |
2006-504160 | Feb 2006 | JP |
2006-133986 | May 2006 | JP |
WO 9800791 | Jan 1998 | WO |
WO 2002011344 | Feb 2002 | WO |
WO 2005001687 | Jan 2005 | WO |
WO 2005086906 | Sep 2005 | WO |
WO 2008124319 | Oct 2008 | WO |
WO 2009039352 | Mar 2009 | WO |
2014011708 | Jan 2014 | WO |
Entry |
---|
“Modular programming” Wikipedia, retrieved Feb. 10, 2009 (2 pages). |
“RASSP Data Flow Graph Design Application Note.” International Conference on Parallel Processing, Dec. 2000, Retrieved from Internet <http://www.atl.external.lmco.com/projects/rassp/RASSP_legacy/appnotes/FLOW/APNOTE_FLOW_02>, 5 pages. |
“System integration” Wikipedia, retrieved Jan. 25, 2009 (3 pages). |
“Topological sorting,” Wikipedia, accessed Dec. 10, 2012, 2 pages. |
“Visual Lint: Squash Bugs Early with Interactive C/C++, C# and Java Code Analysis for Microsoft Visual Studio and Eclipse,” [ retrieved from the internet Dec. 3, 2012: www.riverblade.co.uk/products/visual_lint.] (2 pages). |
Babaoglu, O et al., “Mapping parallel computations onto distributed systems in Paralex” Compuero '91. Advanced Computer Technology, Reliable Systems and Applications. 5th Annual European Computer Conference. Proceedings. Bologna, Italy May 13-16, 1991, Los Alamitos, CA, USA, IEEE Comput. Soc, US, May 13, 1991, pp. 123-130. |
Baer, J.L. et al., “Legality and Other Properties of Graph Models of Computations.” Journal of the Association for Computing Machinery, vol. 17, No. 3, Jul. 1970, pp. 543-554. |
Bernstein and Newcomer, “Principles of Transaction Processing, 2nd Edition”, Morgan Kaufmann, XP002739946 (Jul. 24, 2009). |
Bookstein, A. et al., “Modeling Word Occurrences for the Compression of Concordances.” ACM Transactions on Information Systems, vol. 15, No. 3, Jul. 1997, pp. 254-290. |
Burch, J.R. et al., “Sequential circuit verification using symbolic model checking.” In Design Automation Conference, 1990, Proceedings of the 27th ACM/IEEE. Jun. 24-28, 1990, pp. 46-51. |
Canadian Office Action in Application No. 2,801,573, dated Apr. 13, 2016. |
Chinese Office Action (English Translation) in Application No. 2010-80042716.8, dated Apr. 8, 2016 (14 pages). |
Chinese Office Action issued in CN 201180039226.7, dated May 4, 2015. |
Cytron, Ron et al., “Efficiently Computing Static Single Assignment Form and the Control Dependence Graph.” ACM Transactions on Programming Languages and Systems, vol. 13, No. 4, Oct. 1991, pp. 451-490. |
De Pauw et al., “Web Services Navigator: visualizing the execution of Web Services,” XP2477231, ISSN: 0018-8670, Jan. 1, 2005. |
Dillon, Laura K., et al., “Inference Graphs: A Computational Structure Supporting Generation of Customizable and Correct Analysis Components,” IEEE Transactions on Software Engineering, vol. 29, No. 2, Feb. 2003, pp. 133-150. |
Ebert, Jurgen et al., “A Declarative Approach to Graph-Based Modeling.” Workshop on Graph-Theoretic Concepts in Computer Science, 1994, pp. 1-19. |
European Examination Report in Application No. 10741775.0, dated Jan. 12, 2017. |
European Examination Report issued in EP 06 785 623.7 dated Nov. 24, 2014, 5 pages. |
European Examination Report issued in related EP Application No. 10 741 775.0 dated Jul. 7, 2014. |
European Search Report issued in application No. EP10003554, dated Sep. 24, 2010, 7 pages. |
European Search Report issued in application No. EP10741775, dated Nov. 14, 2012, 4 pages. |
Evripidou, Paraskevas, et al., “Incorporating input/output operations into dynamic data-flow graphs,” Parallel Computing 21 (1995) 1285-1311. |
Examination Report in India Application 250CHENP2009, dated Aug. 31, 2016 (7 pages). |
Extended European Search Report, EP 12165575, dated May 10, 2013, 9 pages. |
Frankl, Phyllis G., et al., “An Applicable Family of Data Flow Testing Criteria,” IEEE Transactions on Sofrware Engineering, vol. 14, No. 10, Oct. 1988, pp. 1483-1498. |
Gamma et al. “Design Patterns: Elements of Reusable Object-Oriented Software”, Sep. 1999. |
Grove et al., “A Framework for Call Graph Construction Algorithms.” Nov. 2001, ACM TOPLAS, vol. 23, Issue 6, pp. 685-746. |
Guyer et al., “Finding Your Cronies: Static Analysis for Dynamic Object Colocation.” Oct. 2004, ACM, pp. 237-250. |
Herniter, Marc E., “Schematic Capture with MicroSim PSpice,” 2nd Edition, Prentice Hall, Upper Saddle River, N.J., 1996, pp. 51-52, 255-280, 292-297. |
IBM: “Concepts and Architecture—Version 3.6,” Internet citation, publibfp.boulder.ibm.com.epubs/pdf/h1262857, retrieved Apr. 19, 2007. |
International Search Report & Written Opinion issued in PCT application No. PCT/US01/23552, dated Jan. 24, 2002, 5 pages. |
International Search Report & Written Opinion issued in PCT application No. PCT/US06/24957, dated Jan. 17, 2008, 14 pages. |
International Search Report & Written Opinion issued in PCT application No. PCT/US07/75576, dated Sep. 16, 2008, 13 pages. |
International Search Report & Written Opinion issued in PCT application No. PCT/US08/71206, dated Oct. 22, 2008, 12 pages. |
International Search Report & Written Opinion issued in PCT application No. PCT/US10/49966, dated Nov. 23, 2010, 8 pages. |
International Search Report & Written Opinion received in PCT application No. PCT/US2011/040440, dated Oct. 12, 2011, 13 pages. |
International Search Report & Written Opinion received in PCT application No. PCT/US2013/070386, dated Feb. 12, 2014, 7 pages. |
International Search Report & Written Opinion received in PCT application No. PCT/US2013/076416, dated Apr. 9, 2014, 10 pages. |
International Search Report and Written Opinion, PCT/US2014/068754, dated May 8, 2015 (17 pages). |
Japanese Office Action (English Translation) in application No. JP2014-077798, dated Nov. 11, 2015 (6 pages). |
Japanese Office Action for Japanese Application No. 2010-518415, with English Translation, dated Nov. 18, 2013, 11 pages. |
Japanese Office Action, with English Translation, JP application No. 2008-519474, dated Sep. 25, 2012, 8 pages. |
Japanese Office Action, with English Translation, JP application No. 2009-523997, dated Oct. 23, 2012, 7 pages. |
Japanese Office Action, with English Translation, JP application No. 2011-000948, dated Jan. 8, 2013, 11 pages. |
Japanese Office Action, with English Translation, JP application No. 2010-518415, dated Feb. 21, 2013, 11 pages. |
Jawadi, Ramamohanrao et al., “A Graph-based Transaction Model for Active Databases and its Parallel Implementation.” U. Florida Tech. Rep TR94-0003, 1994, pp. 1-29. |
Just et al., “Review and Analysis of Synthetic Diversity for Breaking Monocultures.” Oct. 2004, ACM, pp. 23-32. |
Karasawa, K.; Iwata, M.; and Terada, H.—“Direct generation of data-driven program for stream-oriented processing”—Published in: Parallel Architctures and Compilation Techniques., 1997. Proceedings., 1997 International Conference on; Nov. 10-14, 1997 San Francisco, CA—pp. 295-306. |
Kebschull, U. et al., “Efficient Graph-Based Computation and Manipulation of Functional Decision Diagrams.” University of Tubingen, 1993 IEEE, pp. 278-282. |
Krahmer et al., “Graph-Based Generation of Referring Expressions.” Mar. 2003, MIT Press, vol. 29, No. 1, pp. 53-72. |
Krsul, Ivan et al., “VMPlants: Providing and Managing Virtual Machine Execution Environments for Grid Computing.” Proceedings of the ACM/IEEE SC2004 Conference on Supercomputing, 2001, Nov. 6-12, 2004, 12 pages. |
Li, Xiqing et al., “A Practical External Sort for Shared Disk MPPs.” Proceedings of Supercomputing '93, 1993, 24 pages. |
Martin, David et al., “Models of Computations and Systems—Evaluation of Vertex Probabilities in Graph Models of Computations.” Journal of the Association for Computing Machinery, vol. 14, No. 2, Apr. 1967, pp. 281-299. |
Mattson et al., “Patterns for Parallel Programming,” Addison-Wesley Professional ISBN: 0-321-22811-1 (2004). |
Ou, Chao-Wei et al., “Architecture-Independent Locality-Improving Transformations of Computational Graphs Embedded in κ-Dimensions.” Proceedings of the 9th International Conference on Supercomputing, 1995, pp. 289-298. |
Rajesh K. Gupta and Giovanni de Micheli—“A co-synthesis approach to embedded system design automation” Design Automation for Embedded Systems, vol. 1, issue 1-2, 69-120 (1996). |
Russell, Nick, et al., “Workflow Control-Flow Patterns a Revised View,” Workflow Patterns Initiative, 2006, pp. 1-134. |
Shoten, Iwanami, “Encyclopedic Dictionary of Computer Science,” (with English Translation), May 25, 1990, p. 741. |
Stanfill, Craig et al., “Parallel Free-Text Search on the Connection Machine System.” Communications of the ACM, vol. 29, No. 12, Dec. 1986, pp. 1229-1239. |
Stanfill, Craig, “Massively Parallel Information Retrieval for Wide Area Information Servers.” 1991 IEEE International Conference on Systems, Man and Cybernetics, Oct. 1991, pp. 679-682. |
Stanfill, Craig, “The Marriage of Parallel Computing and Information Retrieval.” IEE Colloquium on Parallel Techniques for Information Retrieval, Apr. 1989, 5 pages. |
Supplemental European Search Report issued in application No. EP07813940, dated Nov. 26, 2009, 7 pages. |
Supplemental European Search Report issued in application No. EP08796632, dated Sep. 24, 2010, 6 pages. |
Supplemental European Search Report issued in application No. EP06774092, dated Dec. 19, 2012, 5 pages. |
Supplemental European Search Report issued in EP 13 80 2160 dated Jul. 6, 2016 (6 pages). |
Supplemental European Search Report issued in EP10819444, dated Jun. 3, 2015. |
Transaction History, U.S. Appl. No. 09/627,252, Jul. 8, 2013, 2 pages. |
Transaction Histoiy, U.S. Appl. No. 10/268,509, Jul. 8, 2013, 2 pages. |
Transaction History, U.S. Appl. No. 11/167,902, Jul. 8, 2013, 3 pages. |
Transaction History, U.S. Appl. No. 11/169,014, Jul. 8, 2013, 2 pages. |
Transaction History, U.S. Appl. No. 11/467,724, Jul. 8, 2013, 2 pages. |
Transaction History, U.S. Appl. No. 11/733,579, Jul. 8, 2013, 2 pages. |
Transaction History, U.S. Appl. No. 11/836,349, Jul. 8, 2013, 4 pages. |
Transaction History, U.S. Appl. No. 12/180,141, Jul. 8, 2013, 3 pages. |
Transaction History, U.S. Appl. No. 12/638,588, Jul. 8, 2013, 3 pages. |
Transaction History, U.S. Appl. No. 12/977,545, Jul. 8, 2013, 6 pages. |
Transaction History, U.S. Appl. No. 13/161,010, Jul. 8, 2013, 2 pages. |
Transaction History, U.S. Appl. No. 13/678,921, Jul. 8, 2013, 1 page. |
Vajracharya, Suvas et al., “Asynchronous Resource Management.” Proceedings of the 15th International Parallel and Distributed Processing Symposium, Apr. 2001, 10 pages. |
Van der Aalst, W.M.P., et al., “Workflow Patterns,” Distributed and Parallel Databases, 14, 5-51, 2003. |
Wah, B.W. et al., “Report on Workshop on High Performance Computing and Communications for Grand Challenge Applications: Computer Vision, Speech and Natural Language Processing, and Artificial Intelligence.” IEEE Transactions on Knowledge and Data Engineering, vol. 5, No. 1, Feb. 1993, 138-154. |
Whiting, Paul G., et al., “A History of Data-Flow Languages,” IEEE Annals of the History of Computing, vol. 16, No. 4, 1994, pp. 38-59. |
Transaction History, U.S. Appl. No. 12/704,998, Jan. 11, 2018, 6 pages. |
“Performance Measurement Supporting Increase in Processing Speed of Java Program/Load Testing Tool,” Java World, IDG Japan, Inc., Apr. 1, 2005 vol. 9, No. 4, pp. 020-021 (partial English translation). |
Number | Date | Country | |
---|---|---|---|
20180143861 A1 | May 2018 | US |
Number | Date | Country | |
---|---|---|---|
61152669 | Feb 2009 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 12704998 | Feb 2010 | US |
Child | 15873095 | US |