Embedded - Microprocessors

Part Number	Description / PDF	Quantity
TT8050366166 Intel	MICROPROCESSOR, 32-BIT, 166MHZ	46800
RH80530GZ006512 Intel	MPU, 32-BIT, 1133MHZ CPGA478	2156
NE80546KG0802MM Intel	LOW VOLTAGE INTEL XEON PROCESSOR	5524
NG80960JD40 Intel	RISC MPU, 32-BIT, 40MHZ PQFP132	205
FWIXP425ABB Intel	INTEL IXP425 NETWORK PROCESSOR	117
KC80524KX333HW Intel	MICROPROCESSOR, PENTIUM, X86 ARC	847
LE80554NC009512 Intel	INTEL CELERON M PROCESSOR	7833
WP81348M0828 Intel	INTEL 81348 I/OPROCESSOR	7661
RH80530NZ001256 Intel	MPU, 32-BIT, 1000MHZ CPGA478	4978
MQ80960MC20 Intel	RISC MPU, 32-BIT, 20MHZ	170
MQ80386-16/B Intel	MICROPROCESSOR, X86 ARCH., 32 BI	43
WPIXP2350AET Intel	WESTPORT NETWORK PROCESSOR	1475
RH80535NC017512 Intel	RISC MPU, 64-BIT	211
NQ6702PXHV Intel	INTEL 6702PXH 64-BIT PCI HUB	12586
RK80532PC064512 Intel	MPU, 32-BIT, 2600MHZ CPGA478	68430
EWIXP460BAE Intel	INTEL IXP460 NETWORK PROCESSOR	9
TN87C196KJ Intel	196 MICROCONTROLLER	1295
NE80546RE077256 Intel	LOW VOLTAGE INTEL XEON PROCESSOR	646
RH80536GE0302M Intel	MPU, 64-BIT, 1730MHZ CPGA478	9940
LE80539GF0342MX Intel	YONAH, CORE DUO PROCESSOR, T2400	6197

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