Straightforward DSP Algorithm Suitable for GPU Computation Raul Hazas

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    Data flow analysis within a simplified DSP

    structure provides insight into a likely GPUsuitable algorithm

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    1. Introduction2. IIR Digital Filters and Biquad Structure

    3. Data Flow across biquad structure

    4. Previous work5. Proposed method

    6. Experimental results

    7. Conclusions

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    Digital treatment of sequences resulting fromsampled physical phenomena has manyapplications: image and video processing

    environmental and life sciences, etc.

    DSP processing can consume vast amounts ofcomputing resources

    Trend to migrate signal-processing chores tohighly integrated Graphical Processing Units(GPUs)

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    Infinite Impulse Response digital filters are aparticular kind of filters that act on: current and past input signal samples,

    past filter output values

    +

    =

    = (1)

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    To suit our analysis purposes, we take the Ztransform of the previous difference equation

    =

    + =

    2

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    The polynomial fraction could be factored as

    + +

    =

    Where + .

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    We could rearrange the filter structure if wefactor (4) as:

    5

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    We follow the flow of sequence across thestructure

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    + +

    Then, takes its place as the input to thefeed-forward section

    + +

    Where an apparent inner vector product istaking place

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    There has been a greatdeal of previous workon the parallelimplementation of

    digital filtering

    Most of the speed-upefforts are hindered

    because of datadependency problems

    // u, a float is passed to this// section of the code// x and y arrays are initialized// to {0,0,0}

    // initializationfloat sum = 0;int i=0;

    // compute the valuefor(i=0;i

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    Due to the simplicity of the biquad structure,we suggest:

    For a given input sequence , replace thecontents at each memory location by thecontents of

    Perform a vector inner product with the feed-forward coefficients

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    Matlab and C++ programs were devised tocreate a series of input sequences consistingof a sampled sinusoid signal augmented withrandom values

    C++ program was coded according to thealgorithm described before.

    Filter coefficients were chosen from textbook

    examples for low-pass (LPF), and high-pass(HPF) filters.

    For Matlab we used: filter(bb,aa,x) function

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    The output from theproposed filtercompletely matchesthe one returned by

    Matlab The filters

    characteristic behavioris portrayed by theintermediate sequence

    Note: Output sequence lengthswere adjusted for comparison anddisplay

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    Again, the filterscharacteristic behavioris portrayed by theintermediate sequence

    Moreover, the feed-forward sectionreinforces the high-pass filteringperformance

    Note: Output sequence lengthswere adjusted for comparison anddisplay

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    We implemented a forthright filteringalgorithm

    It behaves in agreement with industrystandard application

    There are well-established approaches forGPU inner-vector product

    We foresee uncoupling recursive operation

    will be accomplished by taking advantage ofGPUs massive parallelism andsynchronization