AI Chips Technology Trends & Landscape (Mobile SoC, Intel, Asian AI Chips, Low-Power Inference Chips)

Habana Labs

Source: Habana Lab. Eight TPC cards each containing a 2000-HL chip with 8 TPC cores.
(Source) Left: 8 TPC cores on a Gaudi chip, Right: a cluster of 8 Gaudi chips
Source: Habana Lab
Source: Habana Lab
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Intel

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  • CPU with MKL-DNN: MKL-DNN is a math kernel library in accelerating DNNs.
  • Integrated GPU: Utilize on-chip processor graphics.
Source: Intel
  • VPU Movidius: Used in machine vision for low power devices.
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Source: Intel
  • Agilex, Stratix FPGA
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  • Habana Labs Gaudi and Goya (discussed in the last section).
Source: Intel

Mobile AI Chip

Apple

Source: Apple
  • 11.8B transistors using the TSMC 5nm process,
  • A six-core ARM CPU with two high-performance cores and four energy-efficient cores. It has a wider superscalar design and a larger cache than the predecessors,
Source: Apple
  • With matrix multiplication accelerations in CPU cores,
  • A 16-core Neural Engine (changed from 8-cores in A13) at 11 TOPs,
Source: Apple
  • A new architecture for the four-core GPU.

Qualcomm

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Samsung

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Huawei/HiSilicon

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Source: HiSilicon

Arm

ARM
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ARM

AI Chips

Huawei/HiSilicon

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Cambricon

Horizon Robotics

Source Journey 2 architecture
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MediaTek

Source: MediaTek
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Source: Wikipedia

Alibaba

Source: Wikichip in ISSCC 2020

Baidu

Source: Baidu

Bitmain/Sophon

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Rockchip

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Intellifusion

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Eyeriss

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Performance/Watt

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Syntiant

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Hailo

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Kneron

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Mythic

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Perceive

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Blaize

Source: Blaize

Stealth Mode Startups

Why do I choose these companies?

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