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 166 for “"cuda"”.
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GPU ray tracing with CUDA
… of a ray tracer, written in C++ and CUDA respectively. A performance analysis reveals that the optimized GPU ray tracer is capable of producing images with speedup gains up to 1852X when compared to the former CPU implementation"--Document.</p>
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Real-Time Smoothed Particle Hydrodynamics For CUDA
… NVIDIA's Compute Unifed Device Architecture (CUDA) has enabled developers to harness the massive computational power of the GPU through the CUDA parallel programming model. Smoothed particle hydrodynamics (SPH) simulations are particularly well suited to CUDA implementation due to the high …
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Real-Time Smoothed Particle Hydrodynamics For CUDA
… NVIDIA's Compute Unifed Device Architecture (CUDA) has enabled developers to harness the massive computational power of the GPU through the CUDA parallel programming model. Smoothed particle hydrodynamics (SPH) simulations are particularly well suited to CUDA implementation due to the high …
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Parallel computing on geostatistical data using CUDA
Data analysis is receiving considerable attention with the design of new graphics processing units (GPUs). Our study focuses on geostatistical data analysis, which is currently applied in diverse disciplines such as meteorology, oceanography, geography, forestry, environmental control, and …
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Optimizing Harris Corner Detection on GPGPUs Using CUDA
… Harris Corner Detection on GPGPUs Using CUDA</p> <p>The objective of this thesis is to optimize the Harris corner detection algorithm implementation on NVIDIA GPGPUs using the CUDA software platform and measure the performance benefit. The Harris corner detection algorithm—developed by C. …
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Performance Portability of CUDA Across NVIDIA GPU Architectures
… framework Compute Unified Device Architecture (CUDA), which only compiles to machine code for NVIDIA hardware. Moreover, NVIDIA releases a new GPU with an updated architecture roughly every two to three years. Since CUDA is commonly forward compatible with the next generation of GPUs, it is …
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CUDA Enhanced Filtering In a Pipelined Video Processing Framework
<p>The processing of digital video has long been a significant computational task for modern x86 processors. With every video frame composed of one to three planes, each consisting of a two-dimensional array of pixel data, and a video clip comprising of thousands of such frames, the sheer volume of …
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FCUDA: Efficient high-level automation CUDA-to-FPGA compilation
… current version of source-to-source compiler FCUDA, which transforms CUDA kernel code into synthesizable C code, exploits the parallelism in different applications with the help of the manually inserted pragmas by the programmers. The additional effort to tweak the code to enable efficient …
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Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA
… as on GPUs; give the reader background on basic CUDA programming for GPUs; discuss performance characteristics of GPUs; we give recommended design choices for GPU implementations of Hermite methods; and present and discuss examples which illustrate the effect these design choices have on …
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Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures
… as part of a heterogeneous system. For years, CUDA has been the de facto programming environment for nearly all general-purpose GPU (GPGPU) applications. In spite of this, the framework is available only on NVIDIA GPUs, traditionally requiring reimplementation in other frameworks in order to …
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Automatic translation of CUDA to OpenCL and comparison of performance optimizations on GPUS
… of any OpenCL program. This thesis presents the CUDAtoOpenCL source-to-source tool that translates code from CUDA to OpenCL, thus ensuring portability of applications on a variety of devices. However, current compiler optimizations are not sufficient to translate performance from a single …
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On the Complexity of Robust Source-to-Source Translation from CUDA to OpenCL
… Much of this growth has been driven by NVIDIA's CUDA ecosystem for developing GPGPU applications on NVIDIA hardware. However, with the increasing diversity of GPUs (including those from AMD, ARM, and Qualcomm), OpenCL has emerged as an open and vendor-agnostic environment for programming GPUs as …
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Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM
Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a …
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Multiple Bounding Boxes Algorithm in Collision Detection and Its Performances in Sequential VS CUDA Parallel Processing
… 3-bounding-boxes both in serial processing and CUDA parallel processing.</p> <p>Our simulation result shows that out of the 1,000,000 tests we run, both the 2-bounding boxes and 3-bounding-boxes partition resulted in far fewer pixel-checks compared to the one bounding box method. Our experiment …
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Acceleration of asymptotic computational electromagnetics physical optics — shooting and bouncing ray (PO-SBR) method using CUDA
… graphics processing unit (GPGPU) using NVIDIA’s CUDA environment. In modern engineering, simulation programs are used to aid the development of advanced devices, and this is where CEM plays the important role of simulating the propagation of electromagnetic (EM) waves and fields using mod-ern …
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CUDA Accelerated X-ray Image Processing for Bone Detection in the Valka X-ray Guided Cutting Machine
… for the Valka X-Ray Guided Cutting Machine using CUDA to further accelerate the bone detection allowing more time for other calculations such as cutting analysis. The new CUDA based bone detection is then compared to its CPU based predecessor for benchmarking. It also involves researching if …
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OpenMP-CUDA implementation of the moment method and multilevel fast multipole algorithm on multi-GPU computing systems
… for GPU computation based on the hybrid OpenMP-CUDA parallel programming model. The resultant algorithms are called the OpenMP-CUDA-MoM and the OpenMP-CUDA-MLFMA, respectively. Both of the proposed methods are applied to compute electromagnetic scattering by a three-dimensional conducting …
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Achieving performance portability across parallel accelerator architectures
… This thesis focuses on SPMD code written in CUDA, noting that programs must obey a number of constraints to achieve high performance on an NVIDIA GPU. Under such constraints, source-level optimizations can improve the performance of CUDA code on Rigel, a MIMD accelerator architecture …
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Fast simulation of E1, B1 and Specific Absorption Rate for 7T MRI with the use of graphical processors
… the use of Compute Unified Device Architecture (CUDA) enabled graphics cards in Finite Difference Time Domain (FDTD) simulations for SAR computation. We show that using this framework can speed up computation by at least an order of magnitude compared to regular CPU computation. This will allow …
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