Computing Power Basics / TOKEN WIKI
There is a difference between the theoretical peak value of
GPU / graphics processor
In one sentence
GPU is a processor suitable for large-scale parallel computing and is commonly used for deep learning training, inference and scientific computing.
Why it matters
The video memory, bandwidth, precision support and software ecosystem of different chips will affect the deployable model and unit cost.
Practical considerations
first confirms the model memory requirements, parallel mode and framework compatibility, and then compares it through the target task stress test.
FAQ
When choosing a GPU, is the video memory size enough?
is not enough, bandwidth, computing power, interconnection, driver and reasoning framework support need to be considered.
