What are Arm-based processors?

Arm-based processors are a type of central processing unit (CPU) architecture known for their energy efficiency and increasingly high performance. Initially prevalent in mobile devices, these processors are now powering a wider range of computing, from embedded systems and IoT devices to servers and even supercomputers. Their design philosophy, emphasizing reduced instruction set computing (RISC), allows them to achieve significant performance per watt, making them a compelling choice for modern, power-conscious computing environments.

Google Axion Processors, explained

Arm-based processors defined

At its core, an Arm-based processor utilizes a reduced instruction set computing (RISC) architecture. This contrasts with the complex instruction set computing (CISC) architecture used by traditional x86 processors. RISC architectures employ a smaller set of simpler instructions, which generally execute faster and require less power.

How do Arm-based processors work?

Arm-based processors operate by fetching and executing instructions from memory. The RISC architecture simplifies this process. Each instruction performs a basic operation, and complex tasks are achieved through a sequence of these simple instructions. This streamlined approach leads to lower power consumption because fewer transistors are active during each instruction cycle. Modern Arm-based processors incorporate advanced features such as pipelining (overlapping instruction execution), superscalar execution (executing multiple instructions simultaneously), and sophisticated branch prediction to enhance performance while maintaining energy efficiency.

How do Arm processors compare?

The landscape of processors includes several key architectures. Here's a comparison highlighting Arm-based processors:

Feature	Arm-based processors	Intel (X86) processors
Architecture	RISC (Reduced Instruction Set Computing)	CISC (Complex Instruction Set Computing)
Energy efficiency	Generally higher, designed for low power consumption	Historically lower, but improving with newer designs
Performance	Progressing rapidly, now competitive in many areas	Historically strong in high-performance computing
Cost	Often lower, especially for embedded and mobile applications	Can be higher, particularly for high-end server CPUs
Market presence	Dominant in mobile, growing in embedded, IoT, and servers	Dominant in desktop and traditional server markets
Instruction set	Simpler, fixed-length instructions	Complex, variable-length instructions

Feature

Arm-based processors

Intel (X86) processors

Architecture

RISC (Reduced Instruction Set Computing)

CISC (Complex Instruction Set Computing)

Energy efficiency

Generally higher, designed for low power consumption

Historically lower, but improving with newer designs

Performance

Progressing rapidly, now competitive in many areas

Historically strong in high-performance computing

Cost

Often lower, especially for embedded and mobile applications

Can be higher, particularly for high-end server CPUs

Market presence

Dominant in mobile, growing in embedded, IoT, and servers

Dominant in desktop and traditional server markets

Instruction set

Simpler, fixed-length instructions

Complex, variable-length instructions

Compared to the traditional x86 architecture, Arm-based processors have historically focused on power efficiency. However, advancements in Arm architecture, such as the Neoverse series, are closing the performance gap in server environments. While x86 processors have a long-standing dominance in high performance computing due to their mature software ecosystem and raw processing power for certain workloads, Arm-based processors offer a compelling alternative with their energy advantages and increasingly competitive performance.

Arm-based processors with Google Cloud

Google Cloud recognizes the growing importance and capabilities of Arm-based processors. This is evident in Google Axion Processors , Google's custom-designed CPUs built on the Arm Neoverse architecture. Axion processors are engineered to deliver exceptional performance and energy efficiency for a wide range of cloud workloads.

Within Google Cloud, Arm-based processors, particularly through Google Axion, can significantly benefit various services:

Compute Engine: Axion instances on Compute Engine provide users with high-performance, energy-efficient virtual machines suitable for demanding workloads like web serving, application servers, and microservices
Google Kubernetes Engine (GKE): Running containerized applications on Axion nodes in GKE can help with potential cost-effectiveness and sustainability due to the processors' power efficiency, without compromising on the scalability and performance required by containerized environments; GKE supports multi-architecture clusters, allowing seamless deployment of applications on both x86 and Arm nodes
Dataproc: For big data processing and analytics, running Spark and Hadoop workloads on Axion-powered instances in Dataproc can help with a balance of performance and potential cost savings, especially for scale-out processing tasks
Dataflow: Stream processing workloads in Dataflow can leverage the efficient performance of Axion processors, potentially leading to lower operational costs for continuous data ingestion and analysis
Batch: High performance computing (HPC) and batch processing jobs can benefit from the core density and performance per watt offered by Axion on Batch , making it a viable option for computationally intensive tasks
Cloud SQL: Running Cloud SQL instances on Compute Engine powered by Axion processors can provide a cost-effective and performant solution for relational database workloads
AlloyDB: AlloyDB , with its PostgreSQL-compatible design, can leverage the performance and efficiency of Axion processors for demanding transactional applications, potentially leading to improved performance and lower TCO

Arm-based processor examples

The Arm architecture encompasses various processor families designed for specific applications:

Cortex-A series: High-performance processors typically found in smartphones, tablets, and now increasingly in laptops and servers; these cores are designed for complex operating systems and demanding applications
Cortex-M series: Microcontroller-class processors optimized for low power consumption and real-time applications, commonly used in embedded systems and IoT devices
Cortex-R series: Real-time processors designed for applications requiring deterministic and low-latency responses, such as automotive systems and industrial control
Neoverse series: Server-grade processors designed for data center workloads, focusing on high core counts, performance scalability, and power efficiency; Google Axion Processors are built on the Neoverse architecture

Benefits of Arm-based processors

The increasing adoption of Arm-based processors, particularly in high performance computing environments, is driven by several key advantages:

Increased energy efficiency

A fundamental strength of the RISC architecture is its ability to achieve significant processing power with lower energy consumption compared to traditional CISC architectures. This efficiency translates to reduced operating costs, lower heat dissipation, and the ability to pack more processing power into a given thermal envelope.

Smaller size and lower heat generation

The simpler instruction set and efficient design of Arm-based processors often result in smaller die sizes and lower heat generation. This is particularly beneficial in space-constrained environments and allows for more compact and efficient system designs.

Versatile usage for different types of technology

The scalability and adaptability of the Arm architecture allow it to be implemented across a wide spectrum of devices, from tiny sensors to powerful server CPUs. This versatility makes it a foundational technology for the increasingly interconnected and diverse computing landscape.

Challenges of Arm-based processors

Despite their growing prominence, Arm-based processors still face certain challenges:

Software compatibility

Historically, the software ecosystem for Arm-based servers and high performance computing has been less mature compared to the x86 ecosystem. While this is rapidly changing with increased support from operating systems, compilers, and application developers, some legacy applications may require recompilation or may not be readily available for Arm architectures.

Performance for specific workloads

While Arm-based processors are becoming increasingly powerful, certain highly specialized workloads that have been optimized for x86 architectures over many years might still see a performance advantage on those platforms. However, this gap is narrowing with each new generation of Arm-based server processors.

Business use cases for Arm-based processors

The energy efficiency and increasing performance of Arm-based processors make them attractive for various business applications:

Cloud computing: Providers like Google Cloud are using Arm-based processors (Axion) to offer potential cost-effective and sustainable compute instances for a variety of workloads
Edge computing: The low power consumption and small form factor of Arm processors are ideal for edge devices that need to perform local processing with limited power resources

What is the future of Google Cloud Arm architecture?

Google Cloud envisions a future where Arm architecture plays an increasingly significant role in powering diverse workloads. The introduction of Google Axion Processors signifies a long-term commitment to this architecture, offering customers a compelling alternative for performance and efficiency.

Myth: "Arm is only for low-power mobile devices"

While Arm architecture has its roots in mobile, it has evolved dramatically. Arm Neoverse, the foundation of Google's custom-designed Axion CPUs, demonstrates its capability for high-performance server-grade processing. Axion is specifically engineered to handle demanding data center workloads, including HPC, delivering substantial performance and efficiency gains on Google Cloud. This is supported by Axion's Neoverse V2 core and the performance benchmarks we've observed.

Myth: "The software ecosystem for Arm in HPC isn't mature enough"

The software ecosystem for Arm is rapidly expanding. Google Cloud actively supports this growth by ensuring compatibility with a wide range of compilers, such as the Arm Compiler for Linux, and scientific libraries, including Arm Performance Libraries. Furthermore, many open source tools and ISV applications are now available and optimized for Arm. On Google Cloud, users benefit from compatible OS images on Compute Engine, multi-architecture container support in GKE, and Google's ongoing contributions to the Arm software development community. We also provide resources and tools to facilitate the migration process.

Myth: "Getting started with Arm for HPC is too complex for students or developers new to the architecture"

Google Cloud helps you get started with Arm for HPC. Users can quickly launch Axion-powered Arm virtual machines in Compute Engine or deploy Arm-based containers in GKE using familiar tools and workflows. This provides an accessible pathway for developers and students to gain valuable, future-ready skills on a leading cloud platform. We are also exploring opportunities to integrate Arm into our educational programs and labs.