When evaluating ARM processors, efficiency is a key consideration along with performance. The most efficient ARM processor balances high performance with low power consumption to provide the best overall value.
What makes an ARM processor efficient?
There are several factors that contribute to ARM processor efficiency:
- Architecture design – An efficient ARM architecture will utilize techniques like reduced instruction set computing (RISC), superscalar pipelines, out-of-order execution, branch prediction, and speculation to maximize performance.
- Manufacturing process – Smaller manufacturing processes like 5nm or 7nm allow for lower voltage operation and better power efficiency.
- Core design – Efficient processor cores utilize optimizations like deeper pipelines, improved branch prediction, larger caches, and better prefetching to gain performance while minimizing power.
- Idle power management – Advanced power gating, clock gating, and multi-core thermal management greatly reduce idle and standby power.
- Task scheduling – Intelligently scheduling tasks across cores can optimize for performance or efficiency as needed.
- SIMD support – SIMD instruction sets like NEON provide power efficient parallel processing for multimedia and math functions.
Chip designers combine all of these techniques to maximize efficiency for different application requirements. For mobile applications, the focus is heavily on idle and active power reduction. In data centers, performance per watt is critical for operational costs.
Most Efficient Overall ARM Processor
When considering the best balance of performance and efficiency across applications, most experts point to Arm’s Cortex-A77 CPU as the most efficient ARM processor design to date.
The Cortex-A77 is a 7nm high performance CPU core launched in 2019. It uses Arm’s latest architecture innovations to push the performance envelope while still prioritizing energy efficiency.
Key efficiency features of the Cortex-A77 include:
- 7nm manufacturing for reduced voltage operation.
- Out-of-order superscalar pipeline capable of dispatching 8 instructions per cycle.
- Improved branch prediction accuracy.
- Larger low-latency caches including a 512KB L2 cache.
- Enhanced multi-core power management and efficiency optimizations.
- Support for 64-bit instructions and ARMv8-A architecture.
In benchmarks, the Cortex-A77 achieved over 20% better performance than the prior Cortex-A76 while still improving energy efficiency. This combination of enhancements makes the Cortex-A77 stand out as Arm’s most efficient high performance processor design.
Most Efficient for Mobile Applications
For mobile and embedded applications, idle and standby power efficiency is critical to preserve battery life. The Cortex-A77 focuses mainly on active power efficiency during intensive workloads.
For mobile applications, Arm’s Cortex-A55 CPU offers class leading idle and standby power efficiency. The Cortex-A55 is an ultra-efficient 64-bit CPU launched in 2017. It leverages optimizations like:
- Arm’s DynamIQ technology for flexibility in single to octa-core configurations.
- Advanced low-power inactive and sleep states.
- Power gating of individual cores and internal domains.
- Operation down to 0.8V for low voltage modes.
- Tuneable performance from 1GHz to 2GHz for flexibility.
- Small core design optimized for low leakage operation.
These extensive low power optimizations make the Cortex-A55 an ideal choice for mobile processors where battery life savings are critical. The Cortex-A55 offers energy efficiency comparable to the Cortex-A77 but with much lower peak performance.
Most Efficient for Machine Learning
For machine learning workloads, optimized neural processing engines integrated with ARM CPU cores provide the best efficiency. Standalone accelerators can offload ML work from the main CPUs to improve energy efficiency.
Arm offers the Ethos line of machine learning processors to pair with Cortex CPUs in SoC designs. Key features for ML efficiency include:
- Support for INT4 and INT8 calculations to optimize for inference workloads.
- High throughput matrix multiply units to accelerate ML math.
- Flexible multi-processor configurations from NPU-100 to NPU-1200.
- INT8 models allow 4x higher throughput over INT16 while using the same die area.
- Designed on 7nm and 5nm processes specifically for ML efficiency.
Combining the Ethos NPU with Cortex CPUs provides optimal efficiency and performance for mobile, automotive, and server workloads using machine learning. The tightly coupled acceleration minimizes data movement energy costs.
Most Efficient for Data Center Servers
For data center and server applications, the key efficiency metric is performance per watt. The Neoverse line of server-optimized ARM processors is designed to maximize throughput while minimizing power.
The latest Neoverse N2 CPU provides leading efficiency via techniques like:
- Use of mature 7nm TSMC manufacturing process.
- High frequency operation up to 3.4GHz.
- 512KB L2 + 64MB L3 cache hierarchy.
- High bandwidth memory subsystem.
- Server-focused branch predictors and prefetchers.
- High core counts up to 128 in a single socket.
- Extensive power management for idle and active power.
In data center benchmarks, the Neoverse N2 achieves comparable throughput to leading x86 processors while consuming 30% less power. This delivers best-in-class performance per watt efficiency for cloud workloads.
Evaluating Real-World Efficiency
When evaluating real-world ARM processor efficiency, factors like SoC integration, manufacturing process, operating system support, and intended workload are important considerations beyond just the CPU core design.
For mobile applications, processors like the Snapdragon 8 Gen 1 SoC combine Arm’s latest Cortex-X2, A710, and A510 CPUs with a modern 5nm manufacturing process, advanced DSU, and power optimized Adreno GPU to achieve exceptional energy efficiency.
Apple’s A-series SoCs have also consistently utilized Arm’s efficient CPU cores and paired them aggressive low-power silicon fabrication and extensive power management to produce the industry’s most efficient mobile processors.
On the server side, AWS’s Graviton processors with up to 64 Neoverse N1 cores can deliver up to 40% better performance per dollar versus competing x86 EC2 instances in the cloud.
These examples reinforce that real-world efficiency is dependent on full SoC design and software integration beyond just the CPU core architecture. Arm’s ongoing improvements in high efficiency processor IP continues to enable impressive gains in many end products across mobile, enterprise, and infrastructure markets.
The Road Ahead for ARM Efficiency
Looking to the future, Arm is pushing efficiency even further with upcoming CPU, GPU, and NPU IP targeting advanced manufacturing processes down to 4nm and 3nm nodes.
Key innovations in next-gen products like the Cortex-X3, Cortex-A715, and next-gen Ethos NPU include:
- New memory subsystem enhancements such as AMU and DSU-110 technology.
- Continued expansion of machine learning capabilities across CPUs, GPUs, and NPUs.
- Broader adoption of big.LITTLE configurations pairing large and small cores.
- FinFET transistor structures enabling ultra-low voltage operation.
- Increased AI-driven software optimization of power management policies.
Arm’s processor roadmap will leverage these advancements and expand their extensive ecosystem to drive the next generation of power efficient computing from cloud to edge devices.