Accelerating the pace of engineering and science

Accelerating Signal Processing and Communications Algorithms Using GPU Computing

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Kirthi Devleker, MathWorks

In this webinar you will learn how you can leverage the computing power of NVIDIA CUDA-enabled GPUs to accelerate your signal processing and communications applications in MATLAB with minimal programming effort.

Signal processing and communications applications are becoming increasingly complex and computationally intensive. MATLAB GPU functionality is well suited for accelerating the computation and simulation for data and image analysis, communications systems, sensor array and RADAR systems. GPU accelerated algorithms, available in Signal Processing Toolbox, Communications System Toolbox, and Phased Array System Toolbox, enable you to perform computations on powerful GPUs using familiar MATLAB language and from within the MATLAB environment without complicated programming.

Product demonstrations will highlight GPU acceleration of:
• Core math and signal processing functions such as correlation, convolution and FFT filtering
• Communications applications such as error correction, encoding/decoding, channel modeling and Bit-Error-Rate calculations

About the Presenter: Kirthi Devleker is the product marketing manager for Signal Processing Toolbox at MathWorks. He has Master Degree in Electrical Engineering from San Jose State University.

Product Focus

  • Communications System Toolbox
  • DSP System Toolbox
  • Parallel Computing Toolbox
  • Phased Array System Toolbox
  • Signal Processing Toolbox

Recorded: 31 Jan 2013