[[Digital signal processing]] (DSP) is a ubiquitous methodology in scientific and engineering computations. However, practically, to DSP problems are often not only 1-D. For instance, image data are 2-D signals and radar signals are 3-D signals. While the number of dimension increases, the time and/or storage complexity of processing digital signalsignals growsgrow dramatically. Therefore, solving DSP problems in real-time is extremely difficult in reality.
Modern [[General-purpose computing on graphics processing units|general purpose graphics processing units (GPGPUs)]] are considered as having an excellent throughput on vector operations and numeric manipulations bythrough a high degree of parallel computationcomputations. While processing digital signals, particularly multidimensional signals, often involves in a series of vector operations on massive amount of independent data samples, GPGPUs are now widely employed to accelerate multidimensional DSP, such as [[image processing]], [[Video processing|video codeccodecs]], [[Radar signal characteristics|radar signal analysis]], [[sonar signal processing]], and [[ultrasound scan]]ning. Conceptually, using GPGPU devices to perform multidimensional DSP is able to dramatically reduce the computation complexity compared with [[Cpu|central processing units (CPUs)]], [[Digital signal processor|digital signal processors (DSPs)]], or other [[Field-programmable gate array|FPGA]] accelerators.
