Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 22 for “"GPU architecture"”.
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Optimizing Lempel-Ziv Factorization for the GPU Architecture
… purpose computing on graphic processing units (GPGPUs) allows us to take advantage of the massively parallel nature of GPUs for computations other that their original purpose of rendering graphics. Our work targets the use of GPUs for general lossless data compression. Specifically, we developed …
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Software-defined pulse-doppler radar signal processing on graphics processors
… for parallel processing. Modern many-core GPUs provide general-purpose computation on the GPU (GPGPU) for high-performance computing applications through fully programmable pipelines, high memory bandwidths of up to hundreds of Gigabytes per second and high floatingpoint computational …
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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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Fast galactic structure finding using graphics processing units
… to the problem using graphics processing units (GPUs) appears largely unexplored. Since these simulations are inherently n-body problems, they contain a high degree of parallelism, which makes them very well suited to a GPU architecture. Therefore, it makes sense to determine the potential for …
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Distributed Support Vector Machine With Graphics Processing Units
… classification to a graphics processing unit (GPU) which has zero scheduling overhead to create concurrent threads. In this thesis, we will take advantage of this GPU architecture to improve the classification performance of SVM.
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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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GPU implementation of block transforms
… ability of Graphics Processing Units (GPUs) has been mainly limited for rendering and visualization application by architecture and programming model. However, with increasing programmability and architecture progress, GPUs inherent massively parallel computational ability have become …
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Optimizations to a massively parallel database and support of a shared scan architecture
This thesis presents a new architecture and optimizations to MapD, a database server which uses a hybrid of multi-CPU/multi-GPU architecture for query execution and analysis. We tackle the challenge of partitioning the data across multiple nodes with many CPUs and GPUs by means of an indexing …
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Combustion Simulations Using Graphic Processing Units
<p>Graphic processing units (GPUs) are powerful graphics engines featuring high levels of parallelism and extreme memory bandwidth, which constitute a powerful computing platform to solve complex problems involving chemically reacting flows. In the present study, computer programs for combustion …
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Automatic Parallelisation of Programs onto CPU+GPU Hybrid Systems
… be efficient on a CPU may be inefficient on a GPU. Furthermore, any program that contains parallel elements must be substantially re-written in order to run on a GPU architecture. This research aims to produce a system that will allow programs to be run without specifying which set of devices …
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A GPU-Enabled Building Block Flow Model for Computational Fluid Dynamics
… In recent years, the rapid development of the GPU industry has led to an explosion of computational power with the GPU architecture. This has allowed wall-modeled large eddy simulation (WMLES), a higher fidelity simulation technique, to become practical for industry use. WMLES requires the use …
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Accelerating The Discontinuous Galerkin Cell-Vertex Scheme (Dg-Cvs) Solver On Cpu-Gpu Heterogeneous Systems
… as an independent unknown, which is amendable to gpu's parallel execution. In this thesis, we use a cpu-gpu heterogeneous processor to accelerate Dg-Cvs to demonstrate that complex scientific applications can benefit from a heterogeneous computing system. There are challenges that such scientific …
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High-level automation of custom hardware design for high-performance computing
… for acceleration on heterogeneous devices (i.e. GPUs and FPGAs). Moreover, the FCUDA framework balances multilevel granularity parallelism synthesis using efficient techniques that leverage fast and accurate estimation models (i.e. do not rely on lengthy physical implementation tools). Finally, …
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Characterization and Exploitation of GPU Memory Systems
Graphics Processing Units (GPUs) are workhorses of modern performance due to their ability to achieve massive speedups on parallel applications. The massive number of threads that can be run concurrently on these systems allow applications which have data-parallel computations to achieve better …
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Reducing Cache Contention On GPUs
The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly popular because, compared to traditional CPUs, they are more cost-effective, their highly parallel nature complements a CPU, and they are more energy efficient. With the popularity of GPUs, many …
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Reconfigurable and heterogeneous architectures for efficient computing
… in the three dominant computing devices -- CPUs, GPUs, and FPGAs. First, we consider general-purpose GPU (GPGPU) computing and highlight the inefficiencies in GPGPU, and identify opportunities to leverage reconfiguration to address these inefficiencies. Our solution is novel reconfigurable GPU …
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Generalizing the Utility of Graphics Processing Units in Large-Scale Heterogeneous Computing Systems
… (i.e., CPUs). The graphic processing unit (GPU) is one such accelerator. Originally designed solely for graphics processing, GPUs have evolved into programmable processors that can deliver massive parallel processing power for general-purpose applications. Using SIMD (Single Instruction …
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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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Towards GPU-accelerated discrete optimization
… accelerators, such as Graphics Processing Units (GPUs), which now constitute a significant portion of the modern HPC infrastructure. Primarily known for their use in graphics rendering and artificial intelligence, we show that GPUs can also be used to accelerate discrete optimization algorithms. …
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Exploring Techniques for Providing Privacy in Location-Based Services Nearest Neighbor Query
… the concept of kernel and parallel computing in GPU. We develop GPU parallel implementation of the snapshot query to handle large number of objects. In our experiment, we exploit parameter tuning. The results show that with parameter tuning and parallel computing power of GPU we are able to …
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