About This Architecture

Modern x64 NPU architecture features 256 tensor cores, HBM3 memory, and PCIe 5.0 connectivity for high-throughput AI inference workloads. The NPU Control Unit orchestrates instruction flow through the Instruction Decoder to specialized compute units: Tensor Core Array for matrix operations, Matrix Multiply Unit for dense linear algebra, and Vector Processing Unit for element-wise operations. On-Chip SRAM (32MB) serves as a high-bandwidth cache between HBM3 Memory (16GB) and compute units, while the DMA Engine handles asynchronous data transfers via PCIe 5.0 Interface to the Host CPU and System Memory (DDR5). Quantization Engine supports INT8 and FP16 precision for optimized inference, with Power Management Unit and Thermal Sensors ensuring thermal efficiency under sustained compute loads. Fork this diagram on Diagrams.so to customize memory hierarchies, add custom accelerator blocks, or export as .drawio for hardware design documentation.

People also ask

What are the key components of a modern NPU architecture for AI inference?

A modern NPU architecture includes a Tensor Core Array (256 cores), Matrix Multiply Unit, Vector Processing Unit, HBM3 Memory (16GB), On-Chip SRAM (32MB), Quantization Engine (INT8/FP16), and PCIe 5.0 Interface. This diagram shows how the NPU Control Unit orchestrates data flow between compute units and memory hierarchy for optimized inference throughput.