Zico Cox
AI chip design refers to the use of artificial intelligence (AI) technologies in the semiconductor development cycle. More and more companies enter the race for AI chips design, so what are the AI chips that have been introduced?
Source: https://www.kukelec.com/ai-chips-applications-and-commercial-model-lists
NVIDIA A100 Tensor Core GPU delivers unprecedented acceleration at every scale to power the world’s highest-performing elastic data centers for AI, data analytics, and HPC. Powered by the NVIDIA Ampere Architecture, A100 is the engine of the NVIDIA data center platform. A100 provides up to 20X higher performance over the prior generation and can be partitioned into seven GPU instances to dynamically adjust to shifting demands.
Recent breakthroughts in AI have swelled our appetite for intelligence in computing devices at all scales and form factors. Intel Lab’s new Loihi 2 chip outperforms its predecessor by up to 10x and comes with an open-source, community-driven neuromorphic computing framework called Lava.
The TPU v4 chip was unveiled at the company’s 2021 I/O developer conference. Google says the supercomputers are actively used by leading AI teams for ML research and production across language models, recommender systems, and other generative AI.
The Qualcomm Cloud AI 100 is designed for AI inference acceleration, addresses unique requirements in the cloud, including power efficiency, scale, process node advancements, and signal processing.
Introducing our second-generation Colossus™ MK2 IPU processor – the GC200. The IPU is a completely new kind of massively parallel processor, co-designed from the ground up with the Poplar® SDK, to accelerate machine intelligence.
Ambarella’s CV52S provides 4K image processing, video encoding / decoding, and CVflow® computer vision processing in a single, low-power design while achieving power consumption below 3W for 4KP60 video recording with advanced AI processing at 30 fps.
The Hailo-8™ edge AI processor, featuring up to 26 tera-operations per second (TOPS), significantly outperforms all other edge processors. Its area and power efficiency are far superior to other leading solutions by a considerable order of magnitude – at a size smaller than a penny even including the required memory.
