GPGPU

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GPGPU

(General Purpose computation on GPUs) Using a graphics processing unit (GPU) for general-purpose parallel processing applications rather than rendering images for the screen. For fast results, applications such as sorting, matrix algebra, image processing and physical modeling require multiple sets of data to be processed in parallel. GPUs are also used in desktop computers for improved voice, face and gesture recognition.

The GPU functions as a coprocessor with its own memory that processes many threads simultaneously. For more information, visit www.gpgpu.org. See GPU, CUDA, OpenCL, DirectCompute, PhysX and AMD Fusion.
References in periodicals archive ?
SIFT implementation and optimization for general-purpose GPU [C], In: Proc of the Int Conf in Central Europe on Computer Graphics (WSCG'07).
CUDA by example; an introduction to general-purpose GPU programming.
With new general-purpose GPU programming languages, such as Stream by AMD (2010), CUDA by NVIDIA (2007), Ct by Intel (2010), and Brook by Stanford (Stanford University Graphics Lab 2010), it is possible to expand GPU applications from visualization to general-purpose computing, including linear algebra (Bell and Garland 2008; Ries et al.
Also recommended is Jason Sanders and Edward Kandrot's CUDA BY EXAMPLE: AN INTRODUCTION TO GENERAL-PURPOSE GPU PROGRAMMING (0131387685).
Systems with a floating-point accelerator, such as a general-purpose GPU or other kind of co-processor, are becoming much more prevalent in the high-performance computing arena," says Kalyan Kumaran, SPEC/HPG chair.

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