Abstract:
Techniques are disclosed for reducing or eliminating loop overhead caused by function calls in processors that form part of a pipeline architecture. The processors in the pipeline process data blocks in an iterative fashion, with each processor in the pipeline completing one of several iterations associated with a processing loop for a commonly-executed function. The described techniques leverage the use of message passing for pipelined processors to enable an upstream processor to signal to a downstream processor when processing has been completed, and thus a data block is ready for further processing in accordance with the next loop processing iteration. The described techniques facilitate a zero loop overhead architecture, enable continuous data block processing, and allow the processing pipeline to function indefinitely within the main body of the processing loop associated with the commonly-executed function where efficiency is greatest.
Abstract:
Techniques are disclosed for the use of fused vector processor instructions by a vector processor architecture. Each fused vector processor instruction may include a set of fields associated with individual vector processing instructions. The vector processor architecture may implement local buffers facilitating a single vector processor instruction to be used to execute each of the individual vector processing instructions without re-accessing vector registers between each executed individual vector processing instruction. The vector processor architecture enables less communication across the interconnection network, thereby increasing interconnection network bandwidth and the speed of computations, and decreasing power usage.
Abstract:
Software Digital Front End (SoftDFE) signal processing techniques are provided. One or more digital front end (DFE) functions are performed on a signal in software by executing one or more specialized instructions on a processor to perform the one or more digital front end (DFE) functions on the signal, wherein the processor has an instruction set comprised of one or more of linear and non-linear instructions. A block of samples comprised of a plurality of data samples is optionally formed and the digital front end (DFE) functions are performed on the block of samples. The specialized instructions can include a vector convolution function, a complex exponential function, an xk function, a vector compare instruction, a vector max( ) instruction, a vector multiplication instruction, a vector addition instruction, a vector sqrt( ) instruction, a vector 1/x instruction, and a user-defined non-linear instruction.
Abstract:
A processor is provided having an instruction set with a sliding window non-linear convolution function. A processor obtains a software instruction that performs a non-linear convolution function for a plurality of input delayed signal samples. In response to the software instruction for the non-linear convolution function, the processor generates a weighted sum of two or more of the input delayed signal samples, wherein the weighted sum comprises a plurality of variable coefficients defined as a sum of one or more non-linear functions of a magnitude of the input delayed signal samples; and repeats the generating step for at least one time-shifted version of the input delayed signal samples to compute a plurality of consecutive outputs. The software instruction for the non-linear convolution function is optionally part of an instruction set of the processor. The non-linear convolution function can model a non-linear system with memory, such as a power amplifier model and/or a digital pre-distortion function.
Abstract:
Techniques are disclosed for the use of local buffers integrated into the execution units of a vector processor architecture. The use of local buffers results in less communication across the interconnection network implemented by vector processors, and increases interconnection network bandwidth, increases the speed of computations, and decreases power usage.
Abstract:
Techniques are disclosed for a vector processor architecture that enables data interpolation in accordance with multiple dimensions, such as one-, two-, and three-dimensional linear interpolation. The vector processor architecture includes a vector processor and accompanying vector addressable memory that enable a simultaneous retrieval of multiple entries in the vector addressable memory to facilitate linear interpolation calculations. The vector processor architecture vastly increases the speed in which such calculations may occur compared to conventional processing architectures. Example implementations include the calculation of digital pre-distortion (DPD) coefficients for use with radio frequency (RF) transmitter chains to support multi-band applications.
Abstract:
Techniques are disclosed for the use of local buffers integrated into the execution units of a vector processor architecture. The use of local buffers results in less communication across the interconnection network implemented by vector processors, and increases interconnection network bandwidth, increases the speed of computations, and decreases power usage.
Abstract:
Techniques are disclosed for reducing or eliminating loop overhead caused by function calls in processors that form part of a pipeline architecture. The processors in the pipeline process data blocks in an iterative fashion, with each processor in the pipeline completing one of several iterations associated with a processing loop for a commonly-executed function. The described techniques leverage the use of message passing for pipelined processors to enable an upstream processor to signal to a downstream processor when processing has been completed, and thus a data block is ready for further processing in accordance with the next loop processing iteration. The described techniques facilitate a zero loop overhead architecture, enable continuous data block processing, and allow the processing pipeline to function indefinitely within the main body of the processing loop associated with the commonly-executed function where efficiency is greatest.