Embedded - Microprocessors

Image Part Number Description / PDF Quantity Rfq
R7S721031VCFP#AA0

R7S721031VCFP#AA0

Renesas Electronics America

IC MCU 32BIT ROMLESS 208LFQFP

79

MCIMX6G2DVK05AA557-NXP

MCIMX6G2DVK05AA557-NXP

NXP Semiconductors

I.MX 32 BIT MPU, ARM CORTEX A7 C

0

AM3703CBCA

AM3703CBCA

Texas Instruments

RISC MICROPROCESSOR, 32 BIT, 800

1123

P1014NXE5DFB

P1014NXE5DFB

NXP Semiconductors

IC MPU Q OR IQ 800MHZ 425TEBGA

0

MCIMX6Y2DVM05AB

MCIMX6Y2DVM05AB

NXP Semiconductors

I.MX6ULL ROM PERF ENHAN

0

MIMX8MN3CVTIZAA

MIMX8MN3CVTIZAA

NXP Semiconductors

I.MX 8M NANO ARM CORTEX

27

MC8640THJ1067NE

MC8640THJ1067NE

NXP Semiconductors

IC MPU MPC86XX 1.067GHZ 994BGA

0

LS1046AXN8Q1A

LS1046AXN8Q1A

NXP Semiconductors

QORIQ LAYERSCAPE 4XA72 64BIT ARM

78

MPC8548ECPXAUJB

MPC8548ECPXAUJB

Freescale Semiconductor, Inc. (NXP Semiconductors)

MPU, 32-BIT, 1333MHZ, PBGA783

1

MPC8321EVRAFDCA

MPC8321EVRAFDCA

NXP Semiconductors

IC MPU MPC83XX 333MHZ 516BGA

40

MCIMX6S1AVM10AD

MCIMX6S1AVM10AD

NXP Semiconductors

I.MX 6S ROM PERF ENHAN

0

MCIMX6X3EVN10AB

MCIMX6X3EVN10AB

NXP Semiconductors

IC MPU I.MX6SX 1GHZ 400MAPBGA

73

ATSAMA5D27C-LD2G-CUR

ATSAMA5D27C-LD2G-CUR

Roving Networks / Microchip Technology

CORTEX-A5 MPU 2GBIT LPDDR2 BGA I

2000

AM5706BCBDDEA

AM5706BCBDDEA

Texas Instruments

J6ENTRY PG 2.0 17MM GP

0

AM3352BZCEA60R

AM3352BZCEA60R

Texas Instruments

IC MPU SITARA 600MHZ 298NFBGA

0

MC68EN360VR25L

MC68EN360VR25L

Freescale Semiconductor, Inc. (NXP Semiconductors)

QUICC COMMUNICATIONS CONTROLLER,

2373

P5040NSE72QC

P5040NSE72QC

Freescale Semiconductor, Inc. (NXP Semiconductors)

QORIQ, 64-BIT POWER ARCH SOC, 4

28

P3041NSE7MMC

P3041NSE7MMC

NXP Semiconductors

IC MPU Q OR IQ 1.2GHZ 1295FCBGA

0

MC68HC000CEI12

MC68HC000CEI12

Freescale Semiconductor, Inc. (NXP Semiconductors)

32-BIT, 12.5MHZ, CMOS, PQCC68

1055

MCF54410CMF250

MCF54410CMF250

Freescale Semiconductor, Inc. (NXP Semiconductors)

MICROPROCESSOR, 32 BIT, COLDFIRE

3213

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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