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Samsung Electronics 5nm process used by Amba in new automotive AI domain controller chip

Update time : 2023-02-23 10:14:26

New CV3-AD685 chip powers autonomous driving and advanced driver assistance system (ADAS) applications with a single-chip solution for multi-sensor fusion and path planning
Samsung Electronics and Ambarella, the US-based edge AI semiconductor company, recently announced that Samsung will provide Ambarella with a 5nm process for its new CV3-AD685 automotive AI domain controller system-on-chip (SoC). The partnership is expected to bring new levels of AI processing performance, functionality and reliability to revolutionise the next generation of self-driving car safety systems.

Amba's CV3-AD685 automotive AI domain controller SoC based on Samsung's 5nm process

The CV3-AD685 is the first volume model in the Amba CV3-AD automotive AI domain controller family, and several Tier-1 automotive suppliers have announced that they will offer solutions using the CV3-AD family of SoCs. Samsung's third-generation 5nm automotive process, optimised for automotive-grade semiconductors, offers superior reliability and traceability thanks to extremely tight process controls and advanced intellectual property (IP).
The maturity and reliability of Samsung's 5nm process will provide a solid technology foundation for Ambac. Leveraging Samsung's extensive experience in automotive process, IP and service pack development, the process helps manufacturers stay at the forefront of innovation in the area of assisted and autonomous driving.
Amba and Samsung foundries have a wealth of experience working together," said Bongmin Wang, President and CEO of Amba. We are excited to bring Samsung Foundry's 5nm to our new CV3-AD685 SoC. samsung's proven and reliable automotive specification technology enables us to achieve new heights in artificial intelligence, system integration and low power consumption in ADAS, L2+ to L4 level autonomous driving vehicles."
The CV3-AD685 is powered by Amba's next-generation CVflow® AI engine with 20 times faster neural network processing than the previous generation CV2 SoC and more general vector and neural network vector processing capabilities to support the overall performance required for fully automated driving (AD) solutions, including computer vision, 4D imaging radar, deep fusion and autonomous driving path planning.
"Samsung brings 5nm EUV FinFET technology to automotive applications to enable superior ADAS and vision processor performance," said Sang-Pil Sim, executive vice president and head of foundry corporate planning at Samsung Electronics, "Tier-1 automotive suppliers have now adopted the technology and we believe other automotive companies will also consider using Samsung's 5nm process for the Amba CV3 -AD domain controller family of SoCs."
The CV3-AD685 is the first member of the CV3-AD product family to use Samsung's 5nm process, which combines advanced image processing, a dense optical flow engine, multiple Arm® Cortex® A78AE and R52 CPUs, an automotive GPU for graphics display and a hardware information security module (HSM) in an "algorithm-first" design philosophy. The central processing architecture supports the entire AD software solution for autonomous driving.
The high performance, high performance and scalable CV3-AD product family, built specifically for ADAS, offers a wide range of solutions for assisted driving while advancing autonomous driving technology. The integrated CV3-AD685 SoC enables multiple sensor sensing for L2+ to L4 level autonomous driving. Samsung's cutting-edge process technology and 3D packaging solutions are powering more of the latest mobile, high performance computing (HPC) and automotive solutions.
Samsung's 5nm process is further supported by the Samsung Advanced Foundry Ecosystem (SAFE™) program, which ensures deep partnerships between Samsung foundries, ecosystem partners and customers, and provides reference flows based on certified key design components including process design kits (PDKs), design methodologies (DMs), multiple IPs and design-on-demand to Enabling robust system-on-chip designs.

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