Parallel Image Processing Based on CUDA CUDA (Compute Unified Device Architecture) is a novel technology of general-purpose computing on the GPU, which makes users develop general GPU (Graphics P... Z Yang,Y Zhu,P Yong - International Conference on Computer Science & Software Engineering 被引量...
Image processing algorithms are more often than not quite complex and a special part of them - the image segmentation task - can become quickly very long-winded because each pixel has to be analyzed and processed repeatedly. NVIDIA has provided a technology called CUDA, based on the C ...
CUDA 学习记录4.2:并行模具(Parallel Stencils) Programming in Parallel with CUDA (cambridge.org),书是 22 年 5 月出版的,已经算比较新的了。 区别于其他 CUDA 书籍的一个特点是,这本书里的 CUDA 示例基于有趣的实际问题,并且还使用现代 C++ 的特性来编写出简单、优雅、紧凑的代码。目前在网上关于 CUDA 的...
Our goal in this section is to develop a work-efficient scan algorithm for CUDA that avoids the extra factor of log2 n work performed by the naive algorithm. This algorithm is based on the one presented by Blelloch (1990). To do this we will use an algorithmic pattern that arises ...
Bay OF, Samet R, Aydn S, Tural S, Bayram A (2015) Performance analysis of GPU-based parallel image segmentation using CUDA. In: Proceedings of the 2th International Conference on Advanced Technology and Sciences (Antalya-Turkey, 2015), ICAT’15, pp 426–429 Hovland RJ Latency and bandwidth...
The UM image processing is realized on GPU by using the OpenCL framework, and it has good data scalability and performance portability. Compared with the performance of serial algorithms, Open Multi-Processing (OpenMP)-based parallel algorithms, and Compute Unified Device Architecture (CUDA)-based ...
The filter_mode field specifies how the values returned by texture reads are computed based on the input texture coordinates. The addr_mode_{0,1,2} fields define the addressing mode in each dimension, which determine how out-of-range coordinates are handled. See the CUDA C Programming Guide ...
If you would like each worker process to have a dedicated GPU, set process_count_per_node equal to the number of GPU devices on a machine. Then, each worker process gets assigned with a unique index to CUDA_VISIBLE_DEVICES. When a worker process stops for any reason, the next started ...
parallel processing,the concurrent or simultaneous execution of two or more parts of a singlecomputer program, at speeds far exceeding those of a conventionalcomputer. Parallel processing requires two or more interconnected processors, each of which executes a portion of the task; some supercomputer pa...
A GPU-accelerated video processing application developed for CMSC416: Parallel Computing, leveraging CUDA and OpenCV to apply convolution-based effects like blurring, edge detection, and sharpening on video frames, with optimized performance using batch