本文探讨了GPU与CPU之间的主要区别，强调GPU在处理并行计算任务方面的能力更强。此外，还介绍了CUDA——一种利用NVIDIA GPU的并行计算引擎来高效解决复杂计算问题的通用并行计算平台和编程模型。
Difference between GPU and CPU
- GPU cares more about data processing ability while CPU concerns more about flow control and data caching.
- GPU is more excellent at computing compute-intensive and high parellel computation due to it’s architechture.
Introduction to CUDA
CUDA is a general purpost parallel computing platform and programming model that leverages the parallel compute engine in NVIDIA GPUs to solve many complex computational problems in a more efficient way than on a CPU.
Three abstractioin of the core of CUDA
- Thread Hierarchy
- Memory Hierarchy
- Heterogeneous Programming
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