US chip company NVIDIA’s $40-billion acquisition of UK-based chip designer Arm from Japan’s SoftBank Group, which was announced on September 13, comes at a time when AI computing, networking and data processing are more important than ever. This acquisition has a big possibility of pushing a dramatic change or improvement in IoT, PC and server architecture.
Since both NVIDIA and Arm are leading vendors in their own territories, the complementary synergies between the two are expected to make the deal a win-win for both. At the same time, the deal will create more concern for other stakeholders.
Arm is a company that almost monopolizes the SoC core design in several segments. However, Arm is not involved in chip manufacturing or creates any chip with its own brand. Instead, it licenses IP, instruction set architecture (ISA) and other technologies to other chip companies, allowing them to design their own unique SoCs for a variety of applications. In the past, the low power consumption capability of Arm's IP allowed it to grow and dominate in the mobile device market. Currently, almost all mobile phones, tablets and IoT devices use Arm technology. In recent years, it has gradually expanded to high-speed computing devices such as PCs, and data centers.
NVIDIA specializes in graphics processing technology and is one of the leading GPU vendors. Thanks to the fast-growing demand for AI and high performance of its GPU, Nvidia has become one of the leading vendors both in edge computing and data center in the past few years.
While NVIDIA and Arm have quite complementary businesses, they also share common goals, such as the server and data center businesses. By combining Nvidia’s AI capability and Arm’s complete ecosystem for edge devices, NVIDIA hopes to empower more edge devices, including smartphones, PCs, self-driving cars, robots and 5G devices, to be able to process inference.
The AIoT market is undoubtedly the initial target of NVIDIA-Arm merger, but the data center is the final. NVIDIA's AI started in the cloud and is moving quickly to the edge, such as warehouses, hospitals, streets and airports. With the deployment of AI capability moving from the cloud to edge, smart sensors connected to AI computers can improve the user experience and save cost. These small autonomous machines will compute continuously and connect to powerful cloud data centers in every corner of the world.
However, NVIDIA's merger with Arm may run into hurdles, such as opposition from other related companies and antitrust examination in different regions.
Conclusion
Through this acquisition, NVIDIA wants to enhance the AI capabilities of Arm-based IoT endpoints to achieve smart devices everywhere, while continuing to consolidate its position in the data center segment. However, the acquisition is still challenging and unpredictable and may take longer than expected to produce the desired result.
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Sep 13, 2021