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TPU
(Tensor Processing Unit)
TPU is Google's custom-developed application-specific integrated circuit (ASIC) optimized for ML workloads. Designed specifically for tensor operations fundamental to neural networks, TPUs accelerate both training and inference tasks.
TPUs offer significant performance advantages over general-purpose GPUs for certain AI workloads, particularly large-scale deployments. Google Cloud makes TPUs available as a service, enabling researchers and businesses to access this specialized hardware. The latest TPU versions incorporate innovations like systolic arrays for efficient matrix multiplication and high-bandwidth memory (HBM) for improved data throughput, making them ideal for training massive models like LLMs.
TPUs offer significant performance advantages over general-purpose GPUs for certain AI workloads, particularly large-scale deployments. Google Cloud makes TPUs available as a service, enabling researchers and businesses to access this specialized hardware. The latest TPU versions incorporate innovations like systolic arrays for efficient matrix multiplication and high-bandwidth memory (HBM) for improved data throughput, making them ideal for training massive models like LLMs.