Processors roll for IoT and AI

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Microprocessor and microcontroller makers are delivering improved chips that address power, cost, and security risks in IoT applications

By Gina
Roos, editor-in-chief

Microprocessor (MPU) and
microcontroller (MCU) manufacturers continue to address the growing internet of
things applications with new devices that focus on ultra-low power, faster
system performance, and beefed up security that includes active tamper
detection and secure firmware installation. These chips need to handle massive
amounts of data from more and more sensors while consuming low power. To reduce
power consumption, chipmakers are using techniques such as adaptive voltage
scaling, power gating, and multiple reduced-power operating modes.

The global market for IoT connected devices is forecast to reach about 38.6 billion units by 2025, up from 22
billion in 2018, according to market research firm Statista. These connected
devices now span across industries, ranging from smartphones, smart appliances,
and home security systems to connected cars, smart cities, and industrial IoT.

With the convergence of
artificial intelligence and IoT across many industries, the additional
intelligence adds some challenges around security, reliability, performance,
and, of course, cost. These chips need to deliver high-speed processing with
enhanced performance while reducing power consumption. Some of these chipmakers
are also adopting techniques such as advanced compression to
reduce power consumption and machine-learning (ML) models.

Here
is a sampling of MPUs and MCUs that target IoT and converged AI applications.

Aimed
at a variety of connected applications, Microchip Technology Inc.’s PIC18-Q43 family of microcontrollers integrates
more configurable core independent peripherals (CIPs), which offloads many
software tasks to hardware for faster system performance and time to market.
The CPIs offer greater design flexibility when creating custom hardware-based
functions to make it easier for developers to customize their specific design
configurations. They are designed with additional capabilities to handle tasks
without the need for intervention from the CPU.

The
configurable peripherals are interconnected to allow for near-zero-latency
sharing of data, logic inputs, or analog signals without additional code for
improved system response. Applications include a variety of real-time
control and connected applications, including home appliances, security
systems, motor and industrial control, lighting, and IoT.

Microchip-PIC18-Q43-MCU-application

Microchip’s
PIC18-Q43 microcontrollers (Image: Microchip Technology)

CIPs
including timers, simplified pulse-width-modulation (PWM) output, CLCs,
analog-to-digital converter with computation (ADCC), and multiple serial
communications enable developers to reduce development time and improve system
performance. The CLC allows developers to tailor functions such
as waveform generation and timing measurements. CIPs also enable whole control
loops to be realized in customizable on-chip hardware, said Microchip.

The PIC18-Q43 product family is available in a range of
memory sizes, packages, and price points.

 

Optimized for security and
wireless communications, Renesas Electronics Corp. recently launched the RX23W — a 32-bit MCU with
Bluetooth 5.0 for IoT endpoint devices such as home appliances and
health-care equipment. The MCU also includes Renesas’s Trusted Secure IP,
featured in its RX MCU family, to address Bluetooth security risks such as
eavesdropping, tampering, and viruses.

The RX23W is based on Renesas’s
RXv2 core, which achieves the high performance of 4.33 Coremark/MHz, with
improved floating-point unit (FPU) and DSP functions. The chip operates at a
maximum clock frequency of 54 MHz. Optimized for system control and wireless
communication, the RX23W provides full Bluetooth 5.0 Low Energy support
including long-range and mesh networking functions and claims the industry’s
lowest-level reception mode peak power consumption at 3 mA.

Renesas_RX23W

Renesas’s RX23W 32-bit microcontroller
with Bluetooth 5.0 (Image: Renesas Electronics)

The RX23W also integrates a
range of peripheral functions for IoT equipment, including security, touchkey,
USB, and CAN functions. These functions allow the RX23W to implement both
system control and Bluetooth wireless functions for IoT endpoint equipment such
as home appliances, health-care equipment, and sports and fitness equipment on
a single chip, said Renesas. In addition, the Bluetooth mesh functions make it
optimal for industrial IoT equipment collecting sensor data in a factory or a
building.

The RX23W is available now in
7 × 7-mm 56-pin QFN and 5.5 × 5.5-mm 85-pin BGA packages with 512 KB
of on-chip flash memory.

Also
aimed at delivering better protection for IoT-connected devices are the STMicroelectronics
ultra-low-power STM32L5x2 MCUs, based on the Arm Cortex-M33 32-bit RISC core
with Arm TrustZone hardware-based security. Trusted computing authenticates
devices connected to a network by creating a protected execution environment
for cyber-protection and sensitive code (cryptography and key storage) that
blocks attempts to corrupt devices or software, while a second, independent
execution environment allows for the running of untrusted code, said the
company.

With
the new STM32L5 series MCUs, operating at clock frequencies to 110
MHz, ST enables designers to include or exclude each I/O, peripheral, or area
of flash or SRAM from TrustZone protection. This allows sensitive workloads to
be fully isolated for maximum security, said ST.

In
addition, TrustZone was engineered to support secure boot, special read-out and
write protection for integrated SRAM and flash, and cryptographic acceleration,
including AES 128-/256-bit key hardware acceleration, public key acceleration
(PKA), and AES-128 on-the-fly decryption (OTFDEC), to protect external code
or data. Other features include active tamper detection and secure firmware
installation. Together, these security features deliver certification to PSA Certified Level 2.

STMicroelectronics-STM32L5

STMicroelectronics’
STM32L5 microcontrollers (Image: STMicroelectronics)

The STM32L5
family also delivers ultra-low power thanks to the addition of techniques such
as adaptive voltage scaling, real-time acceleration, power gating, and multiple
reduced-power operating modes. These techniques enable the MCUs to deliver high
performance and long runtimes whether the devices are powered by coin cells or
even energy harvesting, said ST.

The
switched-mode step-down regulator can also be powered up or down on the fly to
improve low-power performance when the VDD voltage is high enough. The ULPMark scores,
which measure ultra-low-power efficiency based on real-world benchmarks
developed by EEMBC are: 370 ULPMark-CoreProfile and 54
ULPMark-PeripheralProfile at 1.8 V.

Other
MCU features include 512-Kbyte dual-bank flash that allows read-while-write
operation and supports error correction code (ECC) with diagnostics, a
256-Kbyte SRAM, and support for high-speed external memory including single,
dual, quad, or octal SPI and Hyperbus flash or SRAM, as well as an interface
for SRAM, PSRAM, NOR, NAND, or FRAM.

Digital
peripherals include USB Full Speed with dedicated supply, which allows customers
to keep USB communication even when the system is powered at 1.8 V, and a UCPD
controller compliant with USB Type-C Rev. 1.2 and USB Power Delivery Rev. 3.0
specifications. Smart analog features include an analog-to-digital converter
(ADC), two power-gated digital-to-analog converters (DACs), two ultra-low-power
comparators, and two operational amplifiers with external or internal follower
routing and programmable-gain amplifier (PGA) capability.

The
STM32L5 series offers its own STM32CubeL5 one-stop-shop software package, which includes
hardware abstraction layer and low-level drivers, FreeRTOS, Trusted Firmware-M
(TF-M), Secure Boot and Secure Firmware Update (SBSFU), USB-PD device driver,
MbedTLS and MbedCrypto, FatFS file system, and Touch Sensing drivers.

The STM32L5x2 MCUs are well-suited for industrial IoT applications,
including metering, health (human or machine) monitoring, and mobile
point-of-sale. The STM32L5x2 MCUs are available in standard temperature grade
(−40°C to 85°C) for consumer and commercial applications or high-temperature
grade specified from −40°C to 125°C.

Converged
AI and IoT
Building on its AI
platform, Arm recently introduced its Cortex-M55 processor and Ethos-U55 neural
processing unit (NPU), touted as the industry’s first microNPU for the Cortex-M.
For demanding ML applications, the Cortex-M55 can be paired with the Ethos-U55
microNPU, which together deliver a combined 480× increase in ML performance
over existing Cortex-M processors.

The Cortex-M55 is
called the most AI-capable Cortex-M processor and the first one based on the
Armv8.1-M architecture with Arm
Helium vector-processing technology
, which delivers a more
energy-efficient DSP and ML performance. The Cortex-M55 delivers up to a 15× improvement
in ML performance and a 5× increase in DSP performance, with greater
efficiency, compared to previous Cortex-M generations.

A new feature for
Cortex-M processors, the Arm Custom Instructions, will be available to extend
processor capabilities for specific workload optimization, said the company.

The Ethos-U55 is
highly configurable and specifically designed for ML inference in
area-constrained embedded and IoT devices. It offers advanced compression
techniques to save power and reduce ML model sizes significantly to enable
execution of neural networks that previously ran only on larger systems,
according to the company.

These processors
work with Arm TrustZone to ensure that security can be more easily incorporated
into the complete system-on-chip.

Designed
for ultra-low-power, secure edge applications including audio, voice, and ML,
NXP Semiconductors’ i.MX RT600 crossover MCU family bridges the gap
between high performance and integration while meeting cost requirements for
embedded processing at the edge. (The i.MX RT1170 is a winner of EP’s 2019 Product of the Year Awards.)

The
expansion builds on the company’s ML offerings, including the recently
announced i.MX 8M Plus applications processors
with a dedicated NPU. This is the first device
in the i.MX family to integrate a dedicated NPU for advanced machine-learning
inference at the industrial and IoT edge. It also packages an independent
real-time subsystem, dual camera ISP, high-performance DSP, and 3D GPU for edge
applications.

NXP-IMX-RT600-EVK-TOP

NXP’s i.MX RT600 development board (Image: NXP Semiconductors)

The
i.MX RT600 multi-core crossover processor family features an Arm Cortex-M33
running up to 300 MHz and an optional Cadence Tensilica HiFi 4 audio/voice
digital signal processor (DSP) running up to 600 MHz, with four MACS and
hardware-based transcendental and activation functions.

Built
on a 28-nm FD-SOI process optimized for active and leakage power, the i.MX
RT600 supports the high-performance cores with 4.5 MB of on-chip low-leakage
SRAM, which has been configured for simultaneous zero-wait state access, making
it suited for real-time execution of audio/voice, ML, and neural network-based
applications.

The
crossover MCUs also feature EdgeLock, NXP’s advanced embedded security
technology, and ML support using the eIQ for Glow neural network compiler.

Security
features include secure boot with immutable hardware “root of trust,” SRAM
physically unclonable function (PUF)-based unique key storage,
certificate-based secure debug authentication, AES-256 and SHA2-256
acceleration, and DICE security standard implementation for secure
cloud-to-edge communication. The chip also includes an optional fuse-based root
key storage mechanism for secure boot and crypto operations and a public key
infrastructure (PKI), or asymmetric cryptography, providing a dedicated
asymmetric accelerator for ECC and RSA algorithms.

The
crossover processors include an audio/voice subsystem with support of up to
eight DMIC channels, with hardware for voice activation detect (VAD) and up to
eight I2S
peripherals. Other peripherals include SDIO for wireless communication,
high-speed USB with on-chip PHY, a 12-bit ADC with temperature sensor, and
several serial interfaces including 50-Mbits/s SPI, I3C, and six configurable serial
interfaces (USART, SPI, I2C,
or I2S)
with individual FIFO and DMA service request support.

NXP
plans to implement the Ethos U-55 in its Cortex-M–based microcontrollers,
crossover MCUs, and real-time subsystems in applications processors, targeting
resource-constrained industrial and IoT edge devices.

The
highly configurable Ethos-U55 machine-learning accelerator works with the
Cortex-M core to achieve a small footprint, delivering greater than 30×
improvement in inference performance compared to high-performing MCUs, said
NXP.

Claimed
as the first AI multicore processor for embedded sensor applications, Eta
Compute Inc.’s ECM3532 neural sensor processor (NSP) features the company’s
patented Continuous Voltage Frequency Scaling (CVFS) and delivers as low as 100-μW
active power consumption in always-on applications. The ECM3532 multicore NSP
combines an MCU and a DSP, both with CVFS, to optimize execution for the best
efficiency, making it suited for IoT sensor nodes.

Designed
for always-on image and sensor applications, Eta Compute’s NSP offers a
complete software and hardware offering. The platform delivers AI to edge
devices and turns sensor data into actionable information for applications such as voice, activity,
gesture, sound, image, temperature, pressure, and biometrics. The platform solves challenges in edge computing, including lower
response time, increased security, and higher accuracy.

The
standalone AI platform includes a multicore processor, that includes flash
memory, SRAM, I/O, peripherals, and a machine-learning software development
platform. The CVFS substantially increases performance and efficiency for edge
devices. The self-timed CVFS architecture automatically and continuously
adjusts internal clock rate and supply voltage to maximize energy efficiency for
the given workload. The ECM3532 is packaged in a 5 × 5-mm, 81-ball BGA.

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