Throughput-Distortion Computation Of Generic Matrix Multiplication: Toward A Computation Channel For Digital Signal Processing Systems

The generic matrix multiply (GEMM) function is the core element of high-performance linear algebra libraries used in many computationally-demanding digital signal processing (DSP) systems. We propose an acceleration technique for GEMM based on dynamically adjusting the imprecision (distortion) of computation. Our technique employs adaptive scalar companding and rounding to input matrix blocks followed by two forms of packing in floating-point that allow for concurrent calculation of multiple results. Since the adaptive companding process controls the increase of concurrency (via packing), the increase in processing throughput (and the corresponding increase in distortion) depends on the input data statistics. To demonstrate this, we derive the optimal throughput-distortion control framework for GEMM for the broad class of zero-mean, independent identically distributed, input sources. Our approach converts matrix multiplication in programmable processors into a computation channel: when increasing the processing throughput, the output noise (error) increases due to (i) coarser quantization and (ii) computational errors caused by exceeding the machine-precision limitations. We show that, under certain distortion in the GEMM computation, the proposed framework can significantly surpass 100% of the peak performance of a given processor. The practical benefits of our proposal are shown in a face recognition system and a multi-layer perceptron system trained for metadata learning from a large music feature database.Comment: IEEE Transactions on Signal Processing (vol. 60, 2012

An FPGA Implementation of HW/SW Codesign Architecture for H.263 Video Coding

Chapitre 12 http://www.intechopen.com/download/pdf/pdfs_id/1574

The detection and parameter estimation of binary black hole mergers

In this dissertation we study gravitational-wave data analysis techniques for binary neutron star and black hole mergers. During its first observing run, the Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO) reported the first, direct observations of gravitational waves from two binary black hole mergers. We present the results from the search for binary black hole mergers which unambiguously detected the binary black hole mergers. We determine the effect of calibration errors on the detection statistic of the search. Since the search is not designed to precisely measure the astrophysical parameters of the binary neutron star and black hole mergers, we use Bayesian methods to develop a new parameter estimation analysis. We demonstrate the performance of the analysis on the binary black hole mergers detected during Advanced LIGO’s first observing run. We use the parameter estimation analysis to assess the ability of gravitational-wave observatories to observe a gap in the black hole mass distribution between 52 M and 133 M due to pair-instability supernovae. Finally, we use simulated signals added to the Advanced LIGO detectors to validate the search and parameter estimation analyses used to publish the detection of the astrophysical events