How would you distribute an LLM across TPU GPU and CPU for cost-effective deployment

Question

With the help of code tell me How would you distribute an LLM across TPU, GPU, and CPU for cost-effective deployment?

Answer 1

You can distribute an LLM across TPU, GPU, and CPU by assigning compute-heavy layers to accelerators and offloading static or memory-intensive tasks to CPUs using device mapping.

Here is the code snippet below:

In the above code, we are using the following key points:

• Manual device_map defines precise device allocation for each model component.

• load_checkpoint_and_dispatch efficiently loads only needed model chunks.

• Accelerate ensures optimal hardware-aware deployment across heterogeneous devices.

Hence, cross-device mapping allows scalable and cost-efficient LLM deployment using available hardware tiers.