With the sanctions imposed by US, Huawei wants to build its own stack of AI hardware and software without relying on external partners. Eric Xu, Rotating Chairman announcing Ascend 910 AI Chip
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of the AI accelerators delivers the Huawei’s Ascend 910 [16], which reaches 256Tflop/s of raw FP16 performance, leading to 208Gflop/s /mm2 of compute density—nearly an order of magnitude (7.7x) more than IBM Power10 and but still only 55% of the NVIDIA A100’s peak performance. To summarize: modern architectures are moving towards
We will talk through Nvidia’s process technology plans, HBM3E speeds/capacities, PCIe 6.0, PCIe 7.0, and their incredibly ambitious NVLink and 1.6T 224G SerDes plans. If this plan is successful, Nvidia blows everyone out the water. We will also include an discussion into the competitive dynamics and large wins of AMD’s MI300.

With 640 Tensor Cores, V100 is the world’s first GPU to break the 100 teraFLOPS (TFLOPS) barrier of deep learning performance. The next generation of NVIDIA NVLink™ connects multiple V100 GPUs at up to 300 GB/s to create the world’s most powerful computing servers. AI models that would consume weeks of computing resources on previous

However, NVIDIA is one of many players in the Chinese AI market. Its rivals, such as Huawei and AMD, are also vying for a slice of the lucrative pie. Huawei, the Chinese telecom giant, has
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huawei ascend 910 vs nvidia v100