Embedded - Microprocessors

Image Part Number Description / PDF Quantity Rfq
XLP416XD0800-21

XLP416XD0800-21

Broadcom

FCBGA+HS 47.5X47.5 2003

0

BCM5891PD0KFB133G

BCM5891PD0KFB133G

Broadcom

SECURE PROCESSOR

0

AU1350-533MBDA2

AU1350-533MBDA2

Broadcom

537 BGA 21X21MM

0

BCM58711DB0IFEB20G

BCM58711DB0IFEB20G

Broadcom

CPU QUAD CORE A57 STRATAGX

0

XLP204B1IFSB00120G

XLP204B1IFSB00120G

Broadcom

FCBGA+HS 29X29 779

0

XLS204XD0750-11

XLS204XD0750-11

Broadcom

XLS204 750MHZ NOMINAL 845BGA PR

0

XLP316LXD0800-20

XLP316LXD0800-20

Broadcom

862 FCBGA+HS 31X31MM

0

AU1500-333MBD

AU1500-333MBD

Broadcom

AU1500 MIPS PROCESSOR 333MHZ

0

XLS208XD0750-11

XLS208XD0750-11

Broadcom

845 BGA+HS 31X31MM

0

BCM47083SB03

BCM47083SB03

Broadcom

3+3 GE WLAN CHIPSET(11N+11AC)

0

XLR73234XLPD1000

XLR73234XLPD1000

Broadcom

XLR732 C4 1.0GHZ LOW POWER PROCE

0

XLR73234X0800

XLR73234X0800

Broadcom

XLR732 C4 0.8GHZ PROCESSOR

0

XLP316LXD0800-21

XLP316LXD0800-21

Broadcom

862 FCBGA+HS 31X31MM

0

BCM58525BB0KF12G

BCM58525BB0KF12G

Broadcom

DUAL CORE

0

XLP208B1KFSBS0050G

XLP208B1KFSBS0050G

Broadcom

FCBGA+HS 29X29 779

0

AU1250-500MGD

AU1250-500MGD

Broadcom

AU1250 MIPS PROCESSOR 500MHZ ROH

0

XLS208SXD0750-11

XLS208SXD0750-11

Broadcom

IC PROCESSOR 750MHZ IND

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

TypeFunctional CharacteristicsApplication Examples
ARM Cortex-M SeriesLow-power 32-bit cores with real-time capabilities, optional DSP extensionsSmart sensors, wearables, motor control
PowerPCHigh reliability, floating-point units, automotive/Aerospace focusedVehicle ECUs, avionics systems
MIPSEfficient pipelining, 32/64-bit variants for multimedia processingNetworking equipment, set-top boxes
RISC-VOpen instruction set, modular architecture for customizationAI accelerators, edge computing devices
x86 (Embedded)PC compatibility, high processing power with integrated GPUsIndustrial 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

ParameterDescriptionImportance
Clock FrequencyOperating speed (10MHz-6GHz)Determines processing throughput
Instruction SetRISC vs CISC architectureAffects code density and power consumption
TDP (Thermal Design Power)Power consumption under load (100mW-50W)Dictates thermal management requirements
Process NodeManufacturing technology (28nm-5nm)Impacts performance and energy efficiency
Memory BandwidthData transfer rate between core and memoryLimits 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

ManufacturerRepresentative ProductKey Features
ARM HoldingsCortex-A78128-bit NEON engine, 4nm process, 3.0GHz
IntelAtom x6425EQuad-core, 12W TDP, integrated Intel HD Graphics
NXP Semiconductorsi.MX 8M Plus1.8GHz Cortex-A53, NPU for ML acceleration
MicrochipSAM9X6032-bit ARM926EJ-S, 120MHz, ECC memory support
QualcommQCS610Hexagon 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
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