What is GPU (Graphics Processing Unit)?
GPU (Graphics Processing Unit) — Specialized hardware essential for parallel processing tasks, such as training and running AI models.
GPUs can perform thousands of calculations simultaneously, making them ideal for the matrix math that powers neural networks. NVIDIA dominates the AI GPU market with its A100 and H100 chips. GPU availability and cost are often the biggest bottlenecks in AI deployment.
Frequently Asked Questions
Why can’t I use regular CPUs for AI?
You can for small models, but GPUs are 10-100x faster for AI workloads because they process thousands of operations in parallel. Training large models on CPUs would take months instead of days.
Do I need to buy GPUs?
Not necessarily. Cloud providers like AWS, Azure, and GCP rent GPU access by the hour. This is more cost-effective for most organizations unless you have continuous, high-volume workloads.
What GPU should I use for AI?
NVIDIA A100 and H100 are the industry standard for training and large-scale inference. For smaller models and experimentation, consumer GPUs like the RTX 4090 can be sufficient.