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ASIC Dedicated Accelerators

ASICs (Application-Specific Integrated Circuits) are currently the most energy-efficient AI accelerator chips. Unlike GPUs, ASICs are architecturally optimized for specific compute patterns (such as matrix multiplication, sparse inference, and Transformer models), making them ideal for large-scale, high-load deployment scenarios. AWS Trainium is used for cloud training, Cerebras WSE challenges traditional clusters with wafer-scale integration, and the Cambricon Siyuan series spans from edge to cloud. The domestic camp is also rapidly catching up: Hygon DCU is compatible with the ROCm ecosystem, Enflame Blaze focuses on cloud inference and training, and the TsingMicro reconfigurable architecture balances flexibility and efficiency. When choosing an ASIC, consider ecosystem maturity and alignment with specific workload characteristics.

This category includes the following AI accelerator chips/compute cards: