407 results about "Data dependency" patented technology

A determination can be made of how changes to underlying data affect the value of objects. Examples of applications are: caching dynamic Web pages; client-server applications whereby a server sending objects (which are changing all the time) to multiple clients can track which versions are sent to which clients and how obsolete the versions are; and any situation where it is necessary to maintain and uniquely identify several versions of objects, update obsolete objects, quantitatively assess how different two versions of the same object are, and / or maintain consistency among a set of objects. A directed graph called an object dependence graph, may be used to represent the data dependencies between objects. Another aspect is constructing and maintaining objects to associate changes in remote data with cached objects. If data in a remote data source changes, database change notifications are used to "trigger" a dynamic rebuild of associated objects. Thus, obsolete objects can be dynamically replaced with fresh objects. The objects can be complex objects, such as dynamic Web pages or compound-complex objects, and the data can be underlying data in a database. The update can include either: storing a new version of the object in the cache; or deleting an object from the cache. Caches on multiple servers can also be synchronized with the data in a single common database. Updated information, whether new pages or delete orders, can be broadcast to a set of server nodes, permitting many systems to simultaneously benefit from the advantages of prefetching and providing a high degree of scaleability.

There is provided a highly distributed multi-core system with an adaptive scheduler. By resolving data dependencies in a given list of parallel tasks and selecting a subset of tasks to execute based on provided software priorities, applications can be executed in a highly distributed manner across several types of slave processing cores. Moreover, by overriding provided priorities as necessary to adapt to hardware or other system requirements, the task scheduler may provide for low-level hardware optimizations that enable the timely completion of time-sensitive workloads, which may be of particular interest for real-time applications. Through this modularization of software development and hardware optimization, the conventional demand on application programmers to micromanage multi-core processing for optimal performance is thus avoided, thereby streamlining development and providing a higher quality end product.

A method of tracking instruction dependency in a processor issuing instructions speculatively includes recording in an instruction dependency array (IDA) an entry for each instruction that indicates data dependencies, if any, upon other active instructions. An output vector read out from the IDA indicates data readiness based upon which instructions have previously been selected for issue. The output vector is used to select and read out issue-ready instructions from an instruction buffer.

An Adaptive Software Application consists of several types of modules, called Adaptive Units, which are highly parameterized such that they can adapt to varying business requirements by virtue of externally provided parameters. An Adaptive Application is assembled through repeated use of various combinations of different types of Adaptive Units. Large and complex business systems can be rapidly implemented through this approach. An Adaptive Unit includes interface components that can present information to and accept information from the outside world (such as a web page or a system interface), processing logic components that can manipulate and evaluate information based on received parameters received (such as comparisons and decisions including data dependency decisions), and data persistence logic components that retrieves, adds, updates, and deletes data targeting one or more Occurrence Databases. All three components of an Adaptive Unit are parameter driven. These parameters are not specific to any particular business.

In an illustrative embodiment, an apparatus, computer-readable media, or method may be configured to suggest determine relationships. Interaction with a block diagram model may include receiving a first portion of a block diagram model. The block diagram model may include a plurality of blocks. Each of the plurality of blocks may represent a set of dynamic equations. The interacting may be performed using the computer. Relationships between a plurality of a synthesized input, a synthesized output, a synthesized state, or a synthesized derivative, may be determined. A determination may be performed for the first portion of the block diagram model. The determining may include determining a block Jacobian pattern of relationships between two or more of an input, an output, a state, or a derivative of a first block of the plurality of blocks in the graphical model.

An out-of-order renaming processor is provided with a register file within which aliasing between registers of different sizes may occur. In this way a program instruction having a source register of a double precision size may alias with two single precision registers being used as destinations of one or more preceding program instructions. In order to track this data dependency the double precision register may be remapped into a micro-operation specifying two single precision registers as its source register. In this way, scheduling circuitry may use its existing hazard detection and management mechanisms to handle potential data hazards and dependencies. Not all program instructions having such data hazards between registers of different sizes are handled by this source register remapping. For these other program instructions a slower mechanism for dealing with the data dependency hazard is provided. This slower mechanism may, for example, be to drain all the preceding micro-operations from the execution pipelines before issuing the micro-operation having the data hazard.

A method and system for modeling trends in crop yields is provided. In an embodiment, the method comprises receiving, over a computer network, electronic digital data comprising yield data representing crop yields harvested from a plurality of agricultural fields and at a plurality of time points; in response to receiving input specifying a request to generate one or more particular yield data: determining one or more factors that impact yields of crops that were harvested from the plurality of agricultural fields; decomposing the yield data into decomposed yield data that identifies one or more data dependencies according to the one or more factors; generating, based on the decomposed yield data, the one or more particular yield data; generating forecasted yield data or reconstructing the yield data by incorporating the one or more particular yield data into the yield data.

A detector detects at least one kind of dependence in address between instructions executed by at least a processor, the detector being adopted to detect a possibility of presence of the at least one kind of dependence, wherein if the at least one kind of dependence is present in fact, then the detector detects a possibility of presence of the at least one kind of dependence, and if the at least one kind of dependence is not present in fact, then the detector may detect a pseudo presence of the at least one kind of dependence. The detector has an execution history storing unit with a plurality of entries and an address converter for converting an address of a memory access instruction into an entry number, where different addresses may be converted into entry numbers that are the same.