Tech

SEMIFIVE and ICY Tech Achieve Successful Tape-out of 8nm eMRAM-Based Edge AI SoC, Targeting First Commercialization in Asia

A major breakthrough in edge AI processing has been achieved with the successful tape-out of an 8nm eMRAM-based SoC, boasting on-device inference capabilities with up to 2 billion parameters, a significant leap towards ultra-low-power AI applications in devices like AI PCs and humanoid robots. This milestone marks a crucial step towards commercialization in Asia, where the demand for edge AI solutions is rapidly growing. The 8nm process and eMRAM technology are key enablers of this innovation.

SEMIFIVE, a leading global provider of custom AI semiconductor (ASIC) solutions, and ICY Tech, a Chinese AI semiconductor company, have announced the successful tape-out of next-generation Edge AI SoC jointly developed utilizing Samsung Foundry's 8nm (8LPU) embedded Magnetic Random Access Memory (eMRAM) technology. This marks a significant milestone toward the first commercial deployment of 8nm eMRAM technology in Asia.

Overview

The Edge AI SoC boasts on-device inference capabilities with up to 2 billion parameters, a significant leap towards ultra-low-power AI applications in devices like AI PCs and humanoid robots. This collaboration represents SEMIFIVE's first ASIC design project leveraging eMRAM technology.

What it does

The SoC integrates eMRAM into an Edge AI accelerator, enabling high-speed, on-device inference for models with up to 2 billion parameters in edge environments. This enables operation without any network connectivity, making it suitable for edge devices operating in offline environments, including AI PCs, private AI agents, and humanoid robots.

Tradeoffs

Compared to SRAM, eMRAM features a smaller bit cell, enabling higher data density within the same area. Unlike DRAM, it does not require periodic refresh operations, significantly reducing power consumption. With its non-volatile characteristics that retain data even when power is removed, eMRAM is widely regarded as a

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