June 2020
Intermediate to advanced
382 pages
11h 39m
English
Content preview from 40 Algorithms Every Programmer Should Know
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Designing parallel algorithms on CUDA
Let's look deeper into how the GPU accelerates certain processing operations. As we know, CPUs are designed for the sequential execution of data that results in significant running time for certain classes of applications. Let's look into the example of processing an image of a size of 1,920 x 1,200. It can be calculated that there are 2,204,000 pixels to process. Sequential processing means that it will take a long time to process them on a traditional CPU. Modern GPUs such as Nvidia's Tesla are capable of spawning this unbelievable amount of 2,204,000 parallel threads to process the pixels. For most multimedia applications, the pixels can be processed independently of each other and will achieve a significant ...
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