| dbo:abstract |
Digital signal processing (DSP) is a ubiquitous methodology in scientific and engineering computations. In practice, DSP problems are often not only one dimensional. For instance, image data is a 2-D signal and radar is a 3-D signal. While the number of dimensions increases, the time and/or storage complexity of processing digital signals grow dramatically. Therefore, solving multidimensional DSP problems in real-time is extremely difficult. Modern general purpose graphics processing units (GPGPUs) have an excellent throughput on vector operations and numeric manipulations through a high degree of parallel computations. Processing digital signals, particularly multidimensional signals, often involves a series of vector operations on massive numbers of independent data samples, GPGPUs are now widely employed to accelerate multidimensional DSP, such as image processing, video codecs, radar signal analysis, sonar signal processing, and ultrasound scanning. Conceptually, GPGPUs dramatically reduce the computation complexity when compared with central processing units (CPUs), digital signal processors (DSPs), or other FPGA accelerators. (en) |
