Content deleted Content added
No edit summary |
|||
Line 5:
Modern [[General-purpose computing on graphics processing units|general purpose graphics processing units (GPGPUs)]] are considered having excellent throughput on vector operations and numeric manipulations by high degree of parallel computation. 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 codec]], [[Radar signal characteristics|radar signal analysis]], [[sonar signal processing]], and [[Ultrasound scan|ultrasound scanning]]. 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.
==
Processing multidimensional signals is a common problem in scientific researches and/or engineering computations. Notwithstanding, with its high degree of time and storage complexity, it is extremely difficult to process multidimensional signals in real-time.
== Existing Approaches ==
Practically, to accelerate multidimensional DSP, some common approaches have been proposed and developed in the past decades.
==== Lower Sampling Rate ====
Using a lower sampling rate can efficiently reduce the number of samples to be processed at one time and thereby decreasing the computation complexity. However, this can lead to the aliasing problem in the [[Nyquist–Shannon sampling theorem|sampling theorem]] and make a poor quality of outputs. In some applications, such as military radars, we are eager to have highly precise and accurate results. In such cases, using a lower sampling rate in multidimensional DSP is not allowable.
==== Digital Signal Processors (DSPs) ====
Digital signal processors are designed specifically to process vector operations. They are widely used in DSP computations. However, most digital signal processors are only capable of manipulating two operations in parallel. This kind of designs is sufficient to accelerate audio processing (1-D signals) and image processing (2-D signals). However, with a large amount of data samples in multidimensional signals, this is still not efficient enough to retrieve computation results in real-time.
==== Adopting Supercomputers ====
Line 17 ⟶ 25:
[[Graphics processing unit|GPUs]] are originally designed to accelerate image processing and video rendering. Moreover, since modern GPUs' have good ability to perform numeric computations in parallel with a relatively low cost and better energy efficiency, GPUs are becoming a popular alternative to replace supercomputers performing multidimensional DSP.
==
== Examples ==
| |||