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AI Accelerator - Page 3

An AI accelerator is a processor or hardware system optimized for the highly parallel mathematical operations used by machine learning models. GPUs, tensor processing units, neural processing units, and purpose-built inference chips are common examples. Compared with general-purpose processors, accelerators can increase throughput, reduce latency, or lower the energy required to train and run models. Their design may emphasize matrix multiplication, low-precision arithmetic, fast memory access, or communication between many chips. Choosing an accelerator depends on the model architecture, batch size, software support, deployment environment, power budget, and whether the workload involves training, real-time inference, or both.