大规模并行编程CUDA在计算机断层成像二维图像重建中的性能评价
Performance evaluation in the reconstruction of 2D images of computed tomography using massively parallel programming CUDA
摘要：
分析CPU和GPU架构以及顺序和并行编程之间生成的图像的处理时间和相似性。对于图像处理，使用具有AMD FX-8350处理器和Nvidia GTX 960 Maxwell GPU的计算机，连同CUDAFY库和编程语言C\#以及IDE Visual studio。比较的结果表明，在CPU中的顺序编程的形式产生可靠的图像在一个高的定制的时间相比，在CPU和GPU的并行编程的形式。虽然并行编程产生更快的结果，但重建图像中的噪声增加。对于数据类型浮点数，GPU获得了最好的结果，平均时间相当于处理器的1/3，然而数据类型是并行CPU方法的两倍，获得了最好的性能。对于浮点数据类型，GPU具有最佳的平均时间性能，而对于双精度数据类型，最佳的平均时间性能是并行方法CPU。关于图像质量，顺序方法获得类似的输出，而并行方法在其输出中产生噪声。
英文摘要：
Analysis of processing time and similarity of images generated between CPU and GPU architectures and sequential and parallel programming. For image processing a computer with AMD FX-8350 processor and an Nvidia GTX 960 Maxwell GPU was used, along with the CUDAFY library and the programming language C\# with the IDE Visual studio. The results of the comparisons indicate that the form of sequential programming in a CPU generates reliable images at a high custom of time when compared to the forms of parallel programming in CPU and GPU. While parallel programming generates faster results, but with increased noise in the reconstructed image. For data types float a GPU obtained best result with average time equivalent to 1/3 of the processor, however the data is of type double the parallel CPU approach obtained the best performance. For the float data type, the GPU had the best average time performance, while for the double data type the best average time performance was for the parallel approach CPU. Regarding image quality, the sequential approach obtained similar outputs, while the parallel approaches generated noise in their outputs.
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