Version 9 of the Arm (ARMV9) architecture was presented in March 2021 and marks an important step in the evolution of the architecture of ARM processors. It provides improvements in terms of performance, safety and management of modern workloads such as artificial intelligence (AI).
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News and developments compared to ARMV8
The Armv9 ARMC processor architecture, presented in March 2021, brings Three major developments Compared to ARMV8, its previous version.
One of the most striking characteristics of the Armv9 architecture is the introduction of Confidential Compute Architecture (CCA). This New safety standard Guarantees that the data is protected not only at rest or during transmission, but also during processing. Arm CCA uses what are called realms. These are isolated environments within a processor, which isolate sensitive data from the rest of the infrastructure. Critical data can thus be safely processed in environments such as cloud or shared infrastructure.
Although Evolutionary vector extensions (SVE) have already been introduced in ARMV8, Armv9 relies on them with SVE2 to allow better parallel processing of data. SVE2 has been designed to meet the growing needs of modern applications, particularly in the field of Machine learning and digital signal processing. SVE2 optimizes simultaneous processing capacity of several data points, which is particularly useful for carrying out Complex calculations For AI, image processing or video coding.
The surely the most important field of ARMV9 concerns various Optimizations for artificial intelligence and machine learning. The need for specialized calculation power for AI workloads has increased considerably in recent years, as applications such as language processing, image processing or generative AI have spread. Thanks to improving the processing of vector data via SVE2, ARMV9 makes it possible to execute neural networks and machine learning models on ARM servers more effectively. This not only reduces the latencybut also the energy consumptionwhich is particularly advantageous for mobile devices and on -board systems.
The main advantages of ARMV9
The introduction of ARMV9 provides a number of advantages, so that architecture is perfectly suited to specialized calculation applications as well as general use. The following points particularly characterize the latest version of Arm:
Increased security : Thanks to the new confidential calculation architecture (CCA), companies and organizations can process their data in a safer than ever. It protects sensitive data even in shared cloud environments, which is a big step forward towards infrastructure Zero Trustwhere access to data is strictly controlled.
Improved performance for specialized workloads : ARMV9 offers a considerable increase in the computing power thanks to SVE2 extensions. This is particularly useful for applications that must process large amounts of data in parallel. These include artificial intelligence models, video processing and scientific calculations.
Optimized energy efficiency : One of the great forces of all Arm architectures is energy efficiency. ARMV9 maintains this priority and offers optimized energy management despite performance improvements. This efficiency makes ARMV9 processors particularly attractive for mobile devices, on -board systems and the Internet of Objects (IoT).
The main areas of application of ARMV9
Thanks to its versatility and its performance, Armv9 architecture is used in many areas of application. The most relevant are dedicated servers and artificial intelligence.
Dedicated servers
ARMV9 is used in dedicated servers, made available in data centers and by cloud suppliers. Since ERMV9 offers both high performance and energy efficiency, architecture is perfectly suited to specialized tasks and workloads required in modern data centers. Cloud suppliers benefit from reduced operating costs thanks to the low energy consumption processors, while customers take advantage of best performance and a increased reliability.
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Artificial intelligence and machine learning
Armv9 optimizations for AI and machine learning make this architecture particularly adapted to applications in the field of artificial intelligence. Thanks to the management of SVE2, AI algorithms can be executed more quickly, which makes it possible to process large amounts of data and to perform complex calculations, such as those used in neural networks or image analysis
