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Jun 25Liked by Tony Peng

The Ascend 910B challenges the A100 with its 256 TOPS of computing power, compared to the A100's 312 TFLOPS. Although the A100 has a slight numerical advantage, the Ascend 910B's performance in real-world applications is not to be underestimated.

In terms of memory, the Ascend 910B is equipped with 64GB of HBM2E, while the A100 offers 80GB of HBM2E.

Power consumption is an important metric for measuring chip efficiency. The Ascend 910B has a power consumption of 400W, while Nvidia's A100 is at 300W.

The core of technology lies in the details, and the Da Vinci architecture and Ampere architecture are the hearts of the Ascend 910B and A100, respectively.

The Da Vinci architecture is Huawei's self-developed AI computing architecture, designed to provide efficient AI computing capabilities. With 3D Cube matrix computing units, the Da Vinci architecture can complete a large number of MAC operations in a single clock cycle, accelerating AI computing tasks. In addition, the Da Vinci architecture also supports various precision calculations to meet the needs of different AI application scenarios.

The Ampere architecture, as Nvidia's latest GPU architecture, innovates in optimizing AI and HPC tasks. Ampere introduces new Tensor Cores and structured sparsity techniques, further enhancing the performance and efficiency of AI computing. At the same time, Ampere also strengthens support for Multi-Instance GPU (MIG), providing the possibility for multi-task parallel processing.

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