Embedded - Microprocessors

Part Number	Description / PDF	Quantity
AM5K2E02ABD4 Texas Instruments	AM5K2E02ABD4	0
SN74LVT18512DGG Texas Instruments	MICROPROCESSOR CIRCUIT PDSO64	535
AM3505AZCNA Texas Instruments	IC MPU SITARA 600MHZ 491NFBGA	90
AM3354BZCZA80R Texas Instruments	IC ARM CORTEX MPU 324NFBGA	0
AM5K2E04XABD25 Texas Instruments	SOC MPU KEYSTONE II 1089FCBGA	0
AM3703CBPA Texas Instruments	RISC MICROPROCESSOR, 32 BIT, 800	1509
AM3894CCYG135 Texas Instruments	IC MPU SITARA 1.35GHZ 1031FCBGA	0
AM3358BZCZA80 Texas Instruments	IC MPU SITARA 800MHZ 324NFBGA	252
AM1806EZWT3 Texas Instruments	IC MPU SITARA 375MHZ 361NFBGA	13
AM3517AZERA Texas Instruments	AM3517 SITARA PROCESSOR: ARM COR	70
AM3703CUSD100 Texas Instruments	AM3703 SITARA PROCESSOR: ARM COR	892
XOMAP3503BCBB Texas Instruments	IC MPU OMAP-35XX 600MHZ 515FCBGA	5
AM3354BZCZ100 Texas Instruments	IC MPU SITARA 1.0GHZ 324NFBGA	631
OMAP3530DCUS Texas Instruments	RISC MICROPROCESSOR, 32-BIT	3880
AM3871CCYE100 Texas Instruments	AM3871 SITARA PROCESSOR: ARM COR	19
OMAP3530ECBB72 Texas Instruments	IC MPU OMAP-35XX 720MHZ 515FCBGA	0
XAM3517ZCN Texas Instruments	IC MPU SITARA 600MHZ 491NFBGA	323
AM3351BZCEA30R Texas Instruments	SITARA PROCESSOR: ARM CORTEX-A8	500
AM3357ZCZD72 Texas Instruments	RISC MPU, 32-BIT, 720MHZ	488
OMAP3525ECUS Texas Instruments	IC MPU OMAP-35XX 600MHZ 423FCBGA	0

Embedded - Microprocessors

1. Overview

Embedded microprocessors are specialized computing units designed for dedicated control, monitoring, or processing tasks within electronic systems. Unlike general-purpose CPUs, they integrate processing cores, memory interfaces, and peripheral controllers into a single chip (SoC) to optimize performance, power efficiency, and cost for specific applications. These devices form the backbone of modern IoT, automotive systems, industrial automation, and consumer electronics.

2. Main Types and Functional Classification

Type	Functional Characteristics	Application Examples
ARM Cortex-M Series	Low-power 32-bit cores with real-time capabilities, optional DSP extensions	Smart sensors, wearables, motor control
PowerPC	High reliability, floating-point units, automotive/Aerospace focused	Vehicle ECUs, avionics systems
MIPS	Efficient pipelining, 32/64-bit variants for multimedia processing	Networking equipment, set-top boxes
RISC-V	Open instruction set, modular architecture for customization	AI accelerators, edge computing devices
x86 (Embedded)	PC compatibility, high processing power with integrated GPUs	Industrial PCs, medical imaging equipment

3. Architecture and Components

A typical embedded microprocessor contains:

Processing Core(s): RISC/Complex Instruction Set architectures with 1-8 cores
Memory Subsystem: Integrated SRAM, ROM, and external DRAM controllers
Peripheral Interfaces: UART, SPI, I2C, USB, CAN, PCIe, Ethernet MAC
Real-Time Components: Watchdog timers, PWM generators, ADC/DAC modules
Power Management: Multiple sleep modes, DVFS (Dynamic Voltage/Frequency Scaling)

4. Key Technical Specifications

Parameter	Description	Importance
Clock Frequency	Operating speed (10MHz-6GHz)	Determines processing throughput
Instruction Set	RISC vs CISC architecture	Affects code density and power consumption
TDP (Thermal Design Power)	Power consumption under load (100mW-50W)	Dictates thermal management requirements
Process Node	Manufacturing technology (28nm-5nm)	Impacts performance and energy efficiency
Memory Bandwidth	Data transfer rate between core and memory	Limits performance in data-intensive tasks

5. Application Domains

Consumer Electronics: Smartphones (application processors), home appliances
Automotive: ADAS controllers, engine management systems
Industrial: PLCs (Programmable Logic Controllers), robotics
Healthcare: MRI scanners, portable diagnostic devices
Communications: 5G base stations, optical network transceivers

6. Leading Manufacturers and Products

Manufacturer	Representative Product	Key Features
ARM Holdings	Cortex-A78	128-bit NEON engine, 4nm process, 3.0GHz
Intel	Atom x6425E	Quad-core, 12W TDP, integrated Intel HD Graphics
NXP Semiconductors	i.MX 8M Plus	1.8GHz Cortex-A53, NPU for ML acceleration
Microchip	SAM9X60	32-bit ARM926EJ-S, 120MHz, ECC memory support
Qualcomm	QCS610	Hexagon DSP, Adreno GPU, AI Engine for computer vision

7. Selection Guidelines

Key considerations include:

Performance requirements vs power budget (e.g., Cortex-M55 for ultra-low-power AI)
Real-time constraints (deterministic latency for motor control applications)
Peripheral integration (CAN FD for automotive networks)
Software ecosystem (RTOS support, middleware availability)
Longevity and supply chain stability (automotive-grade qualification)

Case Study: A smart thermostat design selected NXP's MCIMX7U5 (Cortex-M4 + Cortex-A7) for its combination of real-time sensor processing and application-layer connectivity.

8. Industry Trends

Emerging directions include:

AI integration: On-chip neural processing units (NPUs) for edge ML inference
Heterogeneous computing: Multi-architecture SoCs (RISC-V + GPU + NPU)
Advanced packaging: 3D-stacked memory integration for bandwidth-intensive applications
Functional safety: ISO 26262 compliance for autonomous vehicle systems
Open ecosystems: Growth of RISC-V adoption in custom ASIC designs