[[Digital signal processing]] (DSP) is a ubiquitous methodology in scientific and engineering computations. However,In practicallypractice, DSP problems are often not only 1-Done dimensional. For instance, image data areis a 2-D signalssignal and radar signalsis area 3-D signalssignal. While the number of dimensiondimensions increases, the time and/or storage complexity of processing digital signals grow dramatically. Therefore, solving multidimensional 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 havinghave an excellent throughput on vector operations and numeric manipulations through a high degree of parallel computations. While processingProcessing 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 processing|video codecs]], [[Radar signal characteristics|radar signal analysis]], [[sonar signal processing]], and [[ultrasound scan]]ning. Conceptually, using GPGPU devices to perform multidimensional DSP is able toGPGPUs dramatically reduce the computation complexity when compared with [[Cpu|central processing units (CPUs)]], [[Digital signal processor|digital signal processors (DSPs)]], or other [[Field-programmable gate array|FPGA]] accelerators.
