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What is Data Parallelism in CUDA C Programming about?

This chapter discusses data parallel computing using CUDA C, a programming language designed for heterogeneous computing systems that leverage both CPUs and GPUs. It explains the concepts of data parallelism, task parallelism, and provides examples such as color-to-greyscale conversion and vector addition to illustrate how parallel computations can be structured and executed. The chapter also outlines the structure of a CUDA C program, including the compilation process and the execution of kernel functions

Author

Piyush Singh

Language

EN