What is CUDA?

CUDA stands for Compute Unified Device Architecture, which is a GPU parallel computing platform and programming model developed by NVIDIA. In simple terms, it is a technology that allows GPUs to be utilized as high-performance parallel processors capable of performing complex calculations rather than just a simple graphics processing unit.

Comparison of CPU and GPU cores

What is the difference between CPU and GPU?

CPUs are optimized for sequential processing using a few powerful cores. In contrast, GPUs are specialized for parallel processing, handling many tasks simultaneously through hundreds or thousands of simple cores.

This characteristic enables GPUs to excel in deep learning, scientific computing, simulations, and other tasks that require large-scale matrix operations.

So why is CUDA necessary?

GPUs are fundamentally designed for graphics processing. However, CUDA serves as a software interface that allows developers to utilize the hardware architecture of the GPU directly.

With CUDA, developers can design code structures tailored for GPUs and efficiently distribute processing of data. In other words, CUDA allows programmers not just to use GPUs, but to program GPUs effectively.

CUDA block grid threading structure

What roles does CUDA play?

CUDA performs several key roles:

  • Manages data transfers between CPU (host) and GPU (device)
  • Creates and executes thousands of threads in parallel
  • Utilizes optimized memory structures suitable for GPU computations
  • Provides an API for efficiently implementing parallel algorithms

For instance, in deep learning frameworks like TensorFlow and PyTorch, GPU computations are carried out based on CUDA. This dramatically accelerates model training speeds and makes it possible to process large datasets.

Conclusion

CUDA is a tool that helps maximize the parallel processing capabilities of GPUs. Even if a GPU has powerful computational capabilities, it cannot fully leverage its potential without a means for programmers to control it. CUDA is a critical technology that bridges this gap and has established itself as one of the core elements of AI and high-performance computing.

In the next post, I will explore how beginners can use CUDA during development, so please stay tuned for that!