What is hardware (H/W) deployment in AI?

Hardware Deployment in AI

Hardware deployment in AI refers to the strategy of selecting, configuring, and optimizing the physical computing infrastructure used to run AI models in production — from cloud GPUs to edge devices.

Deployment Hardware Options

Cloud GPU Options

pythonCopy
# AWS SageMaker deployment example
import boto3
import json

sm_client = boto3.client("sagemaker")

# Deploy a model to an endpoint
response = sm_client.create_endpoint(
    EndpointName="llama-inference",
    EndpointConfigName="llama-config"
)

# Invoke the endpoint
runtime = boto3.client("sagemaker-runtime")
result = runtime.invoke_endpoint(
    EndpointName="llama-inference",
    ContentType="application/json",
    Body=json.dumps({"inputs": "What is machine learning?"})
)

On-Premise Deployment (NVIDIA GPU)

bashCopy
# Install NVIDIA drivers and CUDA
nvidia-smi  # Verify GPU

# Run inference server (vLLM)
pip install vllm

python -m vllm.entrypoints.openai.api_server     --model meta-llama/Meta-Llama-3-8B-Instruct     --dtype bfloat16     --gpu-memory-utilization 0.90     --port 8000

pythonCopy
# Use vLLM via OpenAI-compatible API
from openai import OpenAI

client = OpenAI(base_url="http://localhost:8000/v1", api_key="none")
response = client.chat.completions.create(
    model="meta-llama/Meta-Llama-3-8B-Instruct",
    messages=[{"role": "user", "content": "Hello!"}]
)

Edge Deployment (NVIDIA Jetson)

pythonCopy
# Optimized inference on Jetson (TensorRT)
import tensorrt as trt
import pycuda.driver as cuda

def build_trt_engine(onnx_path: str) -> trt.ICudaEngine:
    logger = trt.Logger(trt.Logger.WARNING)
    builder = trt.Builder(logger)
    network = builder.create_network(1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH))
    parser = trt.OnnxParser(network, logger)

    with open(onnx_path, "rb") as f:
        parser.parse(f.read())

    config = builder.create_builder_config()
    config.set_memory_pool_limit(trt.MemoryPoolType.WORKSPACE, 1 << 30)
    config.set_flag(trt.BuilderFlag.FP16)  # Use FP16 on Jetson

    return builder.build_serialized_network(network, config)

Selecting Hardware Based on Model Size

Deployment Patterns

Key Tools for Hardware Deployment