Search results for "Graphics hardware"

showing 3 items of 3 documents

Real Time Stereo Matching Using Two Step Zero-Mean SAD and Dynamic Programing

2018

Dense depth map extraction is a dynamic research field in a computer vision that tries to recover three-dimensional information from a stereo image pair. A large variety of algorithms has been developed. The local methods based on block matching that are prevalent due to the linear computational complexity and easy implementation. This local cost is used on global methods as graph cut and dynamic programming in order to reduce sensitivity to local to occlusion and uniform texture. This paper proposes a new method for matching images based on a two-stage of block matching as local cost function and dynamic programming as energy optimization approach. In our work introduce the two stage of th…

Matching (statistics)Computational complexity theory010308 nuclear & particles physicsComputer scienceGraphics hardware02 engineering and technology01 natural sciencesDynamic programmingCUDASum of absolute differencesDepth mapComputer Science::Computer Vision and Pattern RecognitionCut0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingAlgorithm2018 15th International Multi-Conference on Systems, Signals & Devices (SSD)
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Implementing Immersive Clustering with VR Juggler

2005

Continuous, rapid improvements in commodity hardware have allowed users of immersive visualization to employ high-quality graphics hardware, high-speed processors, and significant amounts of memory for much lower costs than would be possible with high-end, shared memory computers traditionally used for such purposes. Mimicking the features of a single shared memory computer requires that the commodity computers act in concert—namely, as a tightly synchronized cluster. In this paper, we describe the clustering infrastructure of VR Juggler that enables the use of distributed and clustered computers for the display of immersive virtual environments. We discuss each of the potential ways to syn…

Shared memoryComputer scienceHuman–computer interactionGraphics hardwareOperating systemScene graphGraphicsVirtual realityCluster analysiscomputer.software_genrecomputerVisualization
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CUDA-BLASTP: Accelerating BLASTP on CUDA-enabled graphics hardware

2011

Scanning protein sequence database is an often repeated task in computational biology and bioinformatics. However, scanning large protein databases, such as GenBank, with popular tools such as BLASTP requires long runtimes on sequential architectures. Due to the continuing rapid growth of sequence databases, there is a high demand to accelerate this task. In this paper, we demonstrate how GPUs, powered by the Compute Unified Device Architecture (CUDA), can be used as an efficient computational platform to accelerate the BLASTP algorithm. In order to exploit the GPU's capabilities for accelerating BLASTP, we have used a compressed deterministic finite state automaton for hit detection as wel…

graphics hardwareSource codeComputer sciencemedia_common.quotation_subjectGraphics hardwareGraphics processing unitParallel computingGeneral Purpose Computation on Graphics Processing Unit (GPGPU)Computational scienceInstruction setCUDAGeneticsComputer GraphicsDatabases Proteinmedia_commondynamic programmingFinite-state machineSequence databaseApplied MathematicsProteinsCompute Unified Device Architecture (CUDA)sequence alignmentGeneral-purpose computing on graphics processing unitsAlgorithmsSoftwareBiotechnology
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