With Arm Helium vector extension, it provides significant advancement in digital signal processors (DSP) and machine learning (ML) performance, designed for applications in industrial control and predictive maintenance.
Arm has introduced the Cortex-M52, an addition to its Cortex-M portfolio of processors. This new processor offers a power-efficient solution, making it an ideal replacement for microcontrollers that were previously based on Cortex-M3 and Cortex-M33 designs.
The processor boasts a performance increase of up to 5.6 times for ML and up to 2.7 times for DSP compared to its predecessors due to inclusion of helium technology. This performance enhancement is complemented by better scalar performance and advanced memory interfaces, making it suitable for a wide range of system designs.
Emphasizing the importance of security, the processor incorporates the latest security extensions of the Armv8.1-M architecture, including PACBTI (Pointer Authentication and Branch Target Identification). When combined with TrustZone, these features offer advanced protection against software threats. The processor is also geared to expedite the achievement of PSA Certified Level 2 for silicon, paving the way for the next generation of PSA Certified devices.
It features 32-bit AMBA bus interfaces and 4-stage pipeline.It has data and instruction caches of 64kb each with optional error correction code (ECC). It includes integrated Nested vector interrupt control (NVIC) supporting up to 480 interrupts in addition to the non-maskable interrupts.
Compared to the Cortex-M33, it provides users with increased performance capabilities and improved energy efficiency. These features enable it to support a broader range of applications, particularly in areas involving AI-driven innovation.
The Artificial Intelligence of Things (AIoT) integrates AI into embedded devices, impacting applications in homes, cities, and industries. Built on Arm technology, AIoT is crucial for interpreting data and bridging the gap between the physical and digital worlds. As AI technology evolves, on-device intelligence is increasingly being utilized in smaller, more budget-friendly, and often battery-powered devices. This approach offers cost benefits, enhanced privacy, and improved reliability due to reduced dependence on cloud-based systems.
