This is the first new Arm architecture in over a decade, building on the success of Armv8 which today drives many of the best performance-per-watt everywhere computing happens.
“As we look toward a future that will be defined by AI, we must lay a foundation of leading-edge compute that will be ready to address the unique challenges to come,” said Simon Segars, chief executive officer, Arm. “Armv9 will be at the forefront of the next 300 billion Arm-based chips driven by the demand for pervasive specialized, secure and powerful processing built on the economics, design freedom and accessibility of general-purpose compute.”
The new capabilities in Armv9 are intended to help accelerate the move from general-purpose to more specialized compute across every application as AI, the Internet of Things (IoT) and 5G gain momentum globally.
To address the issue of data security, the Armv9 roadmap introduces the Arm Confidential Compute Architecture (CCA). Confidential computing shields portions of code and data from access or modification while in-use, even from privileged software, by performing computation in a hardware-based secure environment.
The Arm CCA will introduce the concept of dynamically created Realms, useable by all applications, in a region that is separate from both the secure and non-secure worlds. For example, in business applications, Realms can protect commercially sensitive data and code from the rest of the system while it is in-use, at rest, and in transit. In a recent Pulse survey of enterprise executives, more than 90% of the respondents believe that if Confidential Computing were available, the cost of security could come down enabling them to dramatically increase their investment in engineering innovation.
With the ubiquity and range of AI workloads demanding more diverse and specialized solutions - it is estimated there will be more than eight billion AI-enabled voice-assisted devices in use by the mid-2020s - Arm which has partnered with Fujitsu to create the Scalable Vector Extension (SVE) technology, which is at the heart of Fugaku, the world’s fastest supercomputer, has been building on that work and has developed SVE2 for Armv9 to enable enhanced machine learning (ML) and digital signal processing (DSP) capabilities across a wider range of applications.
SVE2 enhances the processing ability of 5G systems, virtual and augmented reality, and ML workloads running locally on CPUs, such as image processing and smart home applications. Over the next few years, Arm will further extend the AI capabilities of its technology with substantial enhancements in matrix multiplication within the CPU, in addition to ongoing AI innovations in its Mali GPUs and Ethos NPUs.
According to Arm, the Armv9 generation can expect to see CPU performance increases of more than 30% over the next two generations of mobile and infrastructure CPUs. However, as the industry moves from general-purpose computing towards ubiquitous specialized processing, annual double-digit CPU performance gains will not be enough.
Along with enhancing specialized processing, Arm’s Total Compute design methodology will accelerate overall compute performance through focused system-level hardware and software optimisations and increases in use-case performance.
By applying Total Compute design principles across its entire IP portfolio of automotive, client, infrastructure and IoT solutions, Armv9 system-level technologies will span the entire IP solution, as well as improving individual IP.
Additionally, Arm is developing several technologies to increase frequency, bandwidth, and cache size, and reduce memory latency to maximize the performance of Armv9-based CPUs.
