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      • Baidu started to work on its Kunlun AI chip project back in 2011. Initially, the company researched and emulated its many-small-core XPU microarchitecture using FPGAs, but in 2018 the company finally built a dedicated silicon that was built using one of Samsung Foundry's 14nm fabrication process (presumably 14LPP).
      www.tomshardware.com/news/baidu-unveils-kunlun-ii-processor-for-ai
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  2. Aug 18, 2021 · Designed for cloud, edge, and autonomous vehicles applications, the 1st generation Kunlun K200 processor announced three years ago offers around 256 INT8 TOPS performance, around 64 TOPS INT/FP16...

  3. Aug 20, 2021 · Baidu has confirmed that its Kunlun II Core chips have entered volume production and will tackle NVIDIA's A100 processors in AI.

  4. Aug 18, 2021 · Chinese tech giant Baidu said on Wednesday it had begun mass-producing second-generation Kunlun artificial intelligence (AI) chips, as it races to become a key player in the chip industry...

  5. Aug 28, 2021 · The Kunlun II, its second-generation AI semiconductor chip, is designed to help devices process huge amounts of data and boost computing power. The chip will use 7nm process technology, with Baidu saying its computational capability will be around two to three times better than the original Kunlun.

  6. Aug 18, 2021 · BEIJING, Aug. 18, 2021 /PRNewswire/ -- Baidu today showcased its strengths in artificial intelligence technology with the launch of Baidu Brain 7.0, the start of mass production of its 2 nd...

  7. Large variety of computing and memory accessing patterns. Up to thousand operators in mainstream frameworks. Mix of tensor, vector and scalar operations. With sequential and random memory access. Rapid change in algorithm and applications. Developers have high threshold to new hardware.

  8. Aug 18, 2021 · The Kunlun II features a 7nm process and is equipped with Baidu’s homegrown second-generation XPU neural processor architecture for cloud, edge, and AI, according to the company. The Kunlun II chips provide up to 256 TeraOPS (INT8) and 128 TFLOPS(FP16), with a maximum power consumption of 120W, according to Baidu.

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