National Instruments Corporation

National Insurance Corporation

Newton G Petersen

Hugo A Andrade

Tai A Ly

Hojin Kee

Joseph E Peck

Matthew E Novacek

Adam T Arnesen

Dustyn K Blasig

David C Uliana

Brian Sierer

John Pasquarette

Ganesh Ranganathan

Haoran Yi

Brian Keith Odom

Cary Paul Butler

Duncan G Hudson, Iii

Taylor L Riche

Swapnil D Mhaske

David W Fuller, Iii

Jeffrey N Correll

Michael L Santori

Gregory O Morrow

Rishi H Gosalia

Jeffrey L Kodosky

Steven W Rogers

Jeffrey D Washington

Satish V Kumar

James M Lewis

Guang Yu Yang

James Wesley McCoy

Jacob Kornerup

James J Truchard

Ian C Wong

James C Nagle

Kaushik Ravindran

Rhishikesh Limaye

Guoqiang Wang

Michael J Trimborn

Arkadeb Ghosal

Sadia B Malik

Julian G Valdez

Trung N Tran

Qing Ruan

Gandiinaa Gumenjav

Adam T Amesen

Charles E Crain Ii

Guang Yang

Techniques are disclosed relating to encoding communications. In some embodiments, for different rows of an encoding matrix, the following operations are performed: generate a set of operations for entries in the row, where the set of operations includes respective operations to be performed on the entries for multiplication of the matrix by a vector, propagate values of entries in the encoding matrix into the set of operations, and simplify ones of the set of operations based on the propagated values to generate an output set of operations. In some embodiments, the output sets of operations are usable to encode input data for communication over a medium. In some embodiments, the disclosed techniques facilitate loop unrolling within compiler memory constraints. In some embodiments, an apparatus (e.g., a mobile device) is configured with the output sets of operations.

Incremental loop modification for LDPC encoding

Techniques are disclosed relating to self-addressing memory. In one embodiment, an apparatus includes a memory and addressing circuitry coupled to or comprised in the memory. In this embodiment, the addressing circuitry is configured to receive memory access requests corresponding to a specified sequence of memory accesses. In this embodiment, the memory access requests do not include address information. In this embodiment, the addressing circuitry is further configured to assign addresses to the memory access requests for the specified sequence of memory accesses. In some embodiments, the apparatus is configured to perform the memory access requests using the assigned addresses.

Self-addressing memory

System and method for convergence analysis. One or more state variables of a first program may be determined based on dependencies of variables in a first program. A second program corresponding to the first program is created based on the state variables and their dependencies, and executed multiple times. Each execution may include recording values of the state variables, determining an execution count, comparing the values to corresponding values from previous executions of the second program, and terminating the executing in response to the values matching corresponding values from at least one previous execution of the second program. A convergence property for the first program is determined based on the execution count, and indicating a number of executions of the first program required to generate all possible values of the one or more variables. The convergence property is stored, and may be useable to optimize the first program.

Program variable convergence analysis

Techniques are disclosed relating to resolving memory access hazards. In one embodiment, an apparatus includes a memory and circuitry coupled to or comprised in the memory. In this embodiment, the circuitry is configured to receive a sequence of memory access requests for the memory, where the sequence of memory access requests is configured to access locations associated with entries in a matrix. In this embodiment, the circuitry is configured with memory access constraints for the sequence of memory access requests. In this embodiment, the circuitry is configured to grant the sequence of memory access requests subject to the memory access constraints, thereby avoiding memory access hazards for a sequence of memory accesses corresponding to the sequence of memory access requests.

Memory system configured to avoid memory access hazards for LDPC decoding

Techniques are disclosed relating to implementation of LDPC encoding circuitry on a single integrated circuit (IC). In some embodiments, circuitry on a single IC includes message circuitry configured to receive or generate a message to be encoded, encode circuitry configured to perform low density parity check (LDPC) encoding on the message, noise circuitry configured to apply noise to the encoded message, and decode circuitry configured to perform LDPC decoding of the message. In some embodiments, the disclosed techniques may reduce production costs (e.g., by reducing overall chip area), facilitate LDPC testing, and/or provide multiple different functions relating to message transmission on a single chip.

Single-IC LDPC encoding and decoding implementations

System and method for performing correlation analysis. A program that includes multiple program structures and one or more data objects is stored. Each data object is shared by at least two of the program structures. For each program structure, decomposition effects on each of the data objects shared by the program structure resulting from each of a respective one or more optimizing transforms applied to the program structure are analyzed. One or more groups of correlated structures are determined based on the analyzing. Each group includes two or more program structures that share at least one data object, and at least one optimizing transform that is compatible with respect to the two or more program structures and the shared data object. For at least one group, the at least one optimizing transform is usable to transform the two or more program structures to meet a specified optimization objective.

Correlation analysis of program structures

Techniques relating to LDPC encoding. A set of operations is produced that is usable to generate an encoded message based on an input message. The set of operations corresponds to operations for entries in a smaller matrix representation that specifies locations of non-zero entries in an LDPC encoding matrix. A mobile device is configured with the set of operations to perform LDPC encoding. Circuitry configured with the set of operations performs LDPC encoding with high performance, relatively small area and/or low power consumption.

LPDC encoding techniques using a matrix representation

Techniques are disclosed relating to configuring an interlock memory system. In one embodiment, a method includes determining a sequence of memory access requests for a program and generating information specifying memory access constraints based on the sequence of memory accesses, where the information is usable to avoid memory access hazards for the sequence of memory accesses. In this embodiment, the method further includes configuring first circuitry using the information, where the first circuitry is included in or coupled to a memory. In this embodiment, after the configuring, the first circuitry is operable to perform memory access requests to the memory corresponding to the sequence of memory accesses while avoiding the memory access hazards, without receiving other information indicating the memory access hazards.

Configuring circuitry with memory access constraints for a program

System and method for creating a program. A program may be compiled, including determining one or more value transfer operations in the program. Each value transfer operation may specify a value transfer between a respective one or more source variables and a destination variable. For each of the one or more value transfer operations, the value transfer operation may be implemented, where the implementation of the value transfer operation may be executable to assign each variable of the value transfer operation to a respective memory resource, thereby mapping the variables to the memory resources, and dynamically change the mapping, including assigning the destination variable to the memory resource of a first source variable of the one or more source variables, thereby transferring the value from the first source variable to the destination variable without copying the value between the memory resources.

Value transfer between program variables using dynamic memory resource mapping

When compiling high level, graphical code (e.g. LabVIEW&#x2122; code) representative of a design, parts of the code that do not depend on external input data may be executed during the compilation process. Specific variables and/or value traces of specific variables in the program, e.g. constant values and/or repeating patterns may be recorded then analyzed, and certain transformations may be applied in the compilation process according to the results of the analysis, thereby optimizing the design. In one approach, the graph may be dynamically stepped through one node at a time, and it may be determined whether all inputs to the stepped-through node are known. If those inputs are known, type conversion and the operation corresponding to the stepped-through node may be dynamically performed. In another approach, a subset of the graphical code not depending on external data may be compiled and executed, thereby obtaining the same results as described above.

Program optimization via compile time execution

When compiling high-level, graphical code (e.g. LabVIEW&#x2122; code) to a different representation (e.g. different software code or hardware FPGA), information relating to characteristics of the design may be collected/captured from the compilation process, and automatically provided to all the earlier stages of the compilation process to obtain more optimal results. Without automated feedback of this information, users have to manually identify, produce, and provide the feedback information, or forego the process altogether, having to assume that the tool has produced the best possible results when that may not be the case. To correct timing, failed constraints paths may be parsed and compared to delays obtained during a previous compile, and previous adjustments that didn't yield desired results may be undone. The longest delay that didn't result from an undone path may then be identified, and adjusted, and the process may be repeated until all paths are predicted to pass.

Staged program compilation with automated timing closure

System and method for specifying and implementing relative hardware clocking in a high level programming language. User input specifying a program may be received. The program is specified for deployment to a programmable hardware element (PHE), and includes first and second code portions configured to communicate with each other during execution. The user input may further specify a rational ratio of respective execution rates for the first and second code portions. A hardware configuration program (HCP) implementing the specified program is automatically generated, including automatically determining a respective clock rate for at least one of the first and second code portions based on the rational ratio. The HCP may be deployable to the PHE, including implementing first and second clocks for controlling execution of the first and second code portions in accordance with the rational ratio and the automatically determined respective clock rate for the at least one code portion.

Specifying and implementing relative hardware clocking in a high level programming language

Growing community of inventors

Austin, TX, United States of America

Newton G Petersen