Abstract: A compilation system can define, at compile time, the data blocks to be managed by an Even Driven Task (EDT) based runtime/platform, and can also guide the runtime/platform on when to create and/or destroy the data blocks, so as to improve the performance of the runtime/platform. The compilation system can also guide, at compile time, how different tasks may access the data blocks they need in a manner that can improve performance of the tasks.

Abstract: A compilation system generates one or more energy windows in a program to be executed on a data processors such that power/energy consumption of the data processor can be adjusted in which window, so as to minimize the overall power/energy consumption of the data processor during the execution of the program. The size(s) of the energy window(s) and/or power option(s) in each window can be determined according to one or more parameters of the data processor and/or one or more characteristics of the energy window(s).

Abstract: A system for data acquisition and processing includes a selector for obtaining samples from one or more sensors, each of which is configured to collect a sample during one or more sampling intervals forming a dwell period. The selector is configured to obtain only a subset of samples of a complete set of samples that can be collected during a dwell period. A solver is configured to solve an underdetermined system based on the collected samples and a mapping relation/phase function, to jointly determine one or more angles and one or more frequencies of transmissions received by the one or more sensors.

Abstract: A signal pre-compensation system analyzes one or more properties of a communication medium and, taking advantage of the locality of propagation, generates using sparse fast Fourier transform (sFFT) a sparse kernel based on the medium properties. The system models propagation of data signals through the medium as a fixed-point iteration based on the sparse kernel, and determines initial amplitudes for the data symbol(s) to be transmitted using different communication medium modes. Fixed-point iterations are performed using the sparse kernel to iteratively update the initial amplitudes. If the iterations converge, a subset of the finally updated amplitudes is used as launch amplitudes for the data symbol(s). The data symbol(s) can be modulated using these launch amplitudes such that upon propagation of the pre-compensated data symbol(s) through the communication medium, they would resemble the original data symbols at a receiver, despite any distortion and/or cross-mode interference in the communication medium.

Abstract: Methods, apparatus and computer software product for source code optimization are provided. In an exemplary embodiment, a first custom computing apparatus is used to optimize the execution of source code on a second computing apparatus. In this embodiment, the first custom computing apparatus contains a memory, a storage medium and at least one processor with at least one multi-stage execution unit. The second computing apparatus contains at least one local memory unit that allows for data reuse opportunities. The first custom computing apparatus optimizes the code for reduced communication execution on the second computing apparatus. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

Abstract: For balancing load, a forwarder can selectively direct data from the forwarder to a processor according to a loading parameter. The selective direction includes forwarding the data to the processor for processing, transforming and/or forwarding the data to another node, and dropping the data. The forwarder can also adjust the loading parameter based on, at least in part, feedback received from the processor. One or more processing elements can store values associated with one or more flows into a structure without locking the structure. The stored values can be used to determine how to direct the flows, e.g., whether to process a flow or to drop it. The structure can be used within an information channel providing feedback to a processor.

Abstract: In a system for enabling configuration of an ensemble of several solvers, such that the ensemble can efficiently solve a constraint problem, for each one of several candidate configurations, an array of scores is computed. The array corresponds to a statistical parameter related to a problem solution, and the computation is based on, at least in part, a set of features associated with the problem. One candidate configuration is assigned to a solver, and based on the array of scores associated with that candidate configuration the same or a different candidate configuration is assigned to a another solver. A system for dynamically reconfiguring an ensemble of solvers obtains runtime data from several solvers, and a new configuration is determined by applying a machine learning and/or heuristic analysis procedure to the runtime data. The configuration of a solver may be updated according to the new configuration while that solver is running.

Abstract: For balancing load, a forwarder can selectively direct data from the forwarder to a processor according to a loading parameter. The selective direction includes forwarding the data to the processor for processing, transforming and/or forwarding the data to another node, and dropping the data. The forwarder can also adjust the loading parameter based on, at least in part, feedback received from the processor. One or more processing elements can store values associated with one or more flows into a structure without locking the structure. The stored values can be used to determine how to direct the flows, e.g., whether to process a flow or to drop it. The structure can be used within an information channel providing feedback to a processor.