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A GPU cluster is a computer cluster in which each node is equipped with a Graphics Processing Unit (GPU). By harnessing the computational power of modern GPUs via general-purpose computing on graphics processing units (GPGPU), very fast calculations can be performed with a GPU cluster.
The hardware classification of GPU clusters fall into two categories: Heterogeneous and Homogeneous.
Heterogeneous
Hardware from both of the major IHV's can be used (AMD and nVidia). Even if different models of the same GPU are used (e.g. 8800GT mixed with 8800GTX) the GPU cluster is considered heterogeneous.
Homogeneous
Every single GPU is of the same hardware class, make, and model. (i.e. a homogeneous cluster comprising 100 8800GTs, all with the same amount of memory)
Classifying a GPU cluster according to the above semantics largely directs software development on the cluster, as different GPUs have different capabilities that can be utilized.
Interconnect
In addition to the computer nodes and their respective GPUs, a fast enough interconnect is needed in order to shuttle data amongst the nodes. The type of interconnect largely depends on the number of nodes present. Some examples of interconnects include Gigabit Ethernet and InfiniBand.
Vendors
NVIDIA provides a list of dedicated Tesla Preferred Partners (TPP) with the capability of building and delivering a fully configured GPU cluster using the Tesla 20-series GPGPUs. AMAX Information Technologies, Dell, Hewlett-Packard and Silicon Graphics are some of the few companies that provide a complete line of GPU clusters and systems. [1]
The software components that are required to make many GPU-equipped machines act as one include:
Mapping an algorithm to run a GPU cluster is somewhat similar to mapping an algorithm to run on a traditional computer cluster. Example: rather than distributing pieces of an array from RAM, a texture is divided up amongst the nodes of the GPU cluster.
A graphics processing unit (GPU) is a specialized electronic circuit initially designed to accelerate computer graphics and image processing. After their initial design, GPUs were found to be useful for non-graphic calculations involving embarrassingly parallel problems due to their parallel structure. Other non-graphical uses include the training of neural networks and cryptocurrency mining.
General-purpose computing on graphics processing units is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing.
AMD FirePro was AMD's brand of graphics cards designed for use in workstations and servers running professional Computer-aided design (CAD), Computer-generated imagery (CGI), Digital content creation (DCC), and High-performance computing/GPGPU applications. The GPU chips on FirePro-branded graphics cards are identical to the ones used on Radeon-branded graphics cards. The end products differentiate substantially by the provided graphics device drivers and through the available professional support for the software. The product line is split into two categories: "W" workstation series focusing on workstation and primarily focusing on graphics and display, and "S" server series focused on virtualization and GPGPU/High-performance computing.
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The Texas Advanced Computing Center (TACC) at the University of Texas at Austin, United States, is an advanced computing research center that is based on comprehensive advanced computing resources and supports services to researchers in Texas and across the U.S. The mission of TACC is to enable discoveries that advance science and society through the application of advanced computing technologies. Specializing in high performance computing, scientific visualization, data analysis & storage systems, software, research & development and portal interfaces, TACC deploys and operates advanced computational infrastructure to enable the research activities of faculty, staff, and students of UT Austin. TACC also provides consulting, technical documentation, and training to support researchers who use these resources. TACC staff members conduct research and development in applications and algorithms, computing systems design/architecture, and programming tools and environments.
CUDA is a proprietary and closed source parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for general purpose processing, an approach called general-purpose computing on GPUs (GPGPU). CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements, for the execution of compute kernels.
AMD FireStream was AMD's brand name for their Radeon-based product line targeting stream processing and/or GPGPU in supercomputers. Originally developed by ATI Technologies around the Radeon X1900 XTX in 2006, the product line was previously branded as both ATI FireSTREAM and AMD Stream Processor. The AMD FireStream can also be used as a floating-point co-processor for offloading CPU calculations, which is part of the Torrenza initiative. The FireStream line has been discontinued since 2012, when GPGPU workloads were entirely folded into the AMD FirePro line.
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The Irish Centre for High-End Computing (ICHEC) is the national high-performance computing centre in Ireland. It was established in 2005 and provides supercomputing resources, support, training and related services. ICHEC is involved in education and training, including providing courses for researchers.
A computer cluster is a set of computers that work together so that they can be viewed as a single system. Unlike grid computers, computer clusters have each node set to perform the same task, controlled and scheduled by software. The newest manifestation of cluster computing is cloud computing.
The Cray CX1 is a deskside workstation designed by Cray Inc., based on the x86-64 processor architecture. It was launched on September 16, 2008, and was discontinued in early 2012. It comprises a single chassis blade server design that supports a maximum of eight modular single-width blades, giving up to 96 processor cores. Computational load can be run independently on each blade and/or combined using clustering techniques.
Tsubame is a series of supercomputers that operates at the GSIC Center at the Tokyo Institute of Technology in Japan, designed by Satoshi Matsuoka.
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Heterogeneous computing refers to systems that use more than one kind of processor or core. These systems gain performance or energy efficiency not just by adding the same type of processors, but by adding dissimilar coprocessors, usually incorporating specialized processing capabilities to handle particular tasks.
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Multidimensional Digital Signal Processing (MDSP) refers to the extension of Digital signal processing (DSP) techniques to signals that vary in more than one dimension. While conventional DSP typically deals with one-dimensional data, such as time-varying audio signals, MDSP involves processing signals in two or more dimensions. Many of the principles from one-dimensional DSP, such as Fourier transforms and filter design, have analogous counterparts in multidimensional signal processing.
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