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AMD ROCm AI Hardware Accelerationcoding
AMD ROCm AI Hardware Acceleration
Nvidia dominated the AI hardware conversation for years, forcing developers to pay heavy GPU premiums. AMD's latest ROCm release brings native PyTorch, Ollama, and vLLM support to consumer Radeon cards at a fraction of the cost.
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Description
ROCm Local LLM Inference Benchmarking Script
Write a Python benchmarking script using PyTorch with ROCm HIP backend to measure tokens-per-second throughput and VRAM allocation across batch sizes 1, 4, 8, and 16 for a 14B parameter quantized model.
Instructions:
- 1.Install AMD ROCm drivers on your Linux/Windows WSL system.
- 2.Pull quantized models using Ollama or vLLM with HIP acceleration.
- 3.Benchmark inference speed and run local models completely private.
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