Global ETD Search
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Showing 1 to 6 of 6 for “"graphics processing unit (GPU) computing"”.
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The case for reconfigurable general purpose GPU computing
General purpose graphics processing unit (GPU) computing (GPGPU) has emerged as a new paradigm for programmers to exploit massive amounts of parallelism for relatively low costs. The abundance of GPUs in desktop and mobile computing platforms makes them ideal for accelerating tasks on multiple …
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Lattice Boltzmann liquid simulations on graphics hardware
… the time required. However, general purpose Graphics Processing Unit (GPU) computing has potential as a relatively inexpensive way to reduce these simulation times. In recent years, GPUs have been used to achieve enormous speedups via their massively parallel architectures. Within the field …
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Using hybrid shared and distributed caching for mixed-coherency GPU workloads
Current GPU computing models support a mixture of coherent and incoherent classes of memory operations. Workloads using these models typically have working sets too large to fit in an economical SRAM structure. Still, GPU architectures have last-level caches to primarily fulfill two functions: …
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Adaptive finite element simulation of fracture: from plastic deformation to crack propagation
… two- and three-dimensional problems on CPU and GPU systems with the main goals of either improving computational efficiency or fidelity of the final solution. We investigate quasi-brittle fracture by means of the inter-element extrinsic cohesive zone model approach in which interface elements …
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Development and application of Lattice Boltzmann and accurate volume of fluid numerical techniques on graphics processing units
… LBM procedures and VOF are implemented to run on graphics processing units (GPU) including multiple CPU-GPU platforms. The throughput of a single GPU LBM code is approximately 16 times higher that of a single CPU code. The scaling of a multi-GPU VOF code is nearly linear on the Blue Waters …
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Scalable parallel tridiagonal algorithms with diagonal pivoting and their optimization for many-core architectures
… Recently, many-core architectures, such as GPUs, have become ubiquitous targets for these applications. Therefore, a high-performance general-purpose GPU tridiagonal solver becomes critical. However, no existing GPU tridiagonal solver provides comparable quality of solutions to most common, …