Modify run.ai code for using a PCIe-based AI accelerator (such as a GPU, FPGA, or ASIC like NVIDIA, Xilinx, or Intel accelerators) for both inference and training
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Set Up the PCIe AI Accelerator Install the required drivers and SDKs for your PCIe accelerator. For example: NVIDIA GPUs: Install CUDA and cuDNN. Intel accelerators: Install OpenVINO Toolkit. Xilinx FPGAs: Install Vitis AI runtime. Ensure the PCIe device is visible via tools like lspci (Linux) or equivalent commands.
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Modify Training Code Use the appropriate deep learning framework and ensure device targeting is set to the PCIe accelerator. Examples:
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and 4. code files
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Use Accelerator-Specific Optimizations For NVIDIA GPUs: Use TensorRT for inference optimization. For Intel FPGAs: Use OpenVINO's optimized inference engine. For Xilinx FPGAs: Use Vitis AI tools for quantization and deployment.
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Monitor and Debug Use monitoring tools to ensure efficient usage of the PCIe accelerator: NVIDIA: nvidia-smi Intel: OpenVINO Benchmark Tool Xilinx: Vitis AI Profiler
