GPU
A processor built for massive parallelism, which is what neural network maths needs.
Resumen
A GPU is a processor with thousands of simple cores optimised for doing the same operation across large arrays at once. It solves the problem that training and serving a neural network is almost entirely matrix multiplication, which is exactly that pattern, while a CPU spends its few complex cores poorly on it. It exists as the reason deep learning became practical: the hardware already existed for graphics, and it happened to fit the maths.
Grafo de tecnologías
Cómo se conecta GPU con el resto del stack.
Usa y depende de
- DeepSpeed framework Frameworks DeepSpeed depends on GPU High ✓ source
- vLLM tool Infrastructure vLLM depends on GPU High ✓ source
Aplicado a
- Deep Learning concept Algorithms GPU used for Deep Learning High ✓ source
- NVIDIA CUDA platform Hardware NVIDIA CUDA used for GPU High ✓ source
Classification
- Tensor Core hardware Hardware Tensor Core part of GPU High ✓ source
Alternativas
Comparativas
Comparativas detalladas con las alternativas anteriores.