With next generation of architecture, Arm is building for the next decade of edge-to-cloud processing

Arm, the architecture IP that dominates chip unit volume across the computing spectrum, recently announced the introduction of Arm v9 architecture.  Arm v9 “is the first new Arm architecture in a decade, building on the success of Armv8 which today drives the best performance-per-watt everywhere computing happens” according to Simon Segars, Chief Executive Officer of Arm. (See the related press release on March 30)

Arm v9 improves AI and security

Arm v9 comes with two main enhancements: 2nd generation Scalable Vector Extension (SVE2), and Confidential Compute Architecture (CCA). 

Built on SVE, which is at the heart of the Fugaku supercomputer, Arm developed SVE2 to apply to a wider range of AI application.  SVE2 and its adaptable vector and matrix multiplication are key to integrating DSP and Deep Learning algorithms from edge to cloud across a single architecture.  If widely adopted, it could put a significant barrier up for entrants looking to capture market share in AI applications with coprocessing elements.

CCA which introduces the concept of dynamically created Realms, is an important step given the current growth of cybercrime and digital security issues. The theory here is that the entire application including hardware resources, OS, and software stack are completely isolated into its own realm and thus invisible to another OS instantiation or Hypervisor running in the same processor. While this is extremely more secure in theory, more information is sought on the impact to performance. At what point does more Realms on limited resources start to have a measurable impact to performance?

Additional features Arm v9 could bring about is Raytracing in the next generation of graphics subsystems. This is initially targeted at the Application Processor Cortex A, but Arm stated it would affect the evolution of Cortex-R and Cortex-M as well which may bring a new level of graphics capabilities to future generations of microcontrollers.

Arm is everywhere

From smartphones and base stations to automotive and smart sensors and even the world’s fastest supercomputer, Arm is practically ubiquitous in the technology world.  Most recently, the computing world saw a high-profile convert to Arm-based architecture in Apple’s switch to the M1 processor for the latest MacBook models.  Over the next 18 months, Apple probably moves their whole PC fleet over to in-house designed processors, discontinuing a lineage of Intel-sourced CPUs dating back to 2006. Yole estimates that Apple’s processor sourcing decision will take ARM-based notebooks up from around 10M units in 2019 to more than 30M in 2022. 

Changing market dynamic

The marquee enhancements brought with Arm v9 architecture are well-timed as AI and security are key factors for today’s chip designers.  Especially as x86-based architectures struggle to gain a foothold in edge workloads, Arm looks to continue dominating in this space.  It remains to be seen whether the proposed link-up of Arm and Nvidia could drive some designers to look elsewhere, and whether that leads to the most cost-sensitive applications towards the open-sourced Risc V architecture. 

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About the authors

John Lorenz is a Technology and Market Analyst, Computing & Software within the Semiconductor, Memory & Computing division at Yole Développement (Yole), part of Yole Group of Companies.  John is engaged in the development of market and technology monitors for the logic segment of advanced semiconductors, with an initial focus on processors.  Prior to joining Yole, John held various technical and strategic roles at Micron Technology.

On the engineering side, his roles included thin film process development and manufacturing integration on DRAM, NAND, and emerging memory technologies and industrial engineering / factory physics for the R&D fab. 

On the strategic side, John ran the memory industry supply & capex model for corporate strategy / market intelligence and established the industry front-end costing model within strategic finance. 

John has a Bachelor of Science degree in Mechanical Engineering from the University of Illinois Urbana-Champaign (USA), with a focus on MEMS devices.

Tom Hackenberg is a Principal Analyst for Computing and Software in the Semiconductor, Memory and Computing Division at Yole Développement (Yole). Tom is engaged in developing processor market monitors and research into related technology trends. He is currently focused on low and ultralow power solutions such as MCUs.

Tom is an industry leading expert with more than a decade’s experience reporting on markets for semiconductor processors including CPUs, GPUs, MPUs, MCUs, SoC ASICs & ASSPs, FPGAs and configurable processors. Tom is also well-versed in related technology trends including IoT, heterogeneous processing, chiplets, AI and edge computing.

Prior to joining Yole, Tom was a principal analyst at OMDIA, IHS Markit and began processor market research in 2006 for IMS Research. He worked with market-leading processor suppliers developing both syndicated and custom research. Tom holds a BSECE from the University of Texas at Austin specializing in Processors and FPGAs.

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Source: http://www.yole.fr

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