Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
CDB150X-01-Z

CDB150X-01-Z

Cirrus Logic

DEVELOPMENT BOARD FOR CS1501

0

CDK2000-LCO

CDK2000-LCO

Cirrus Logic

KIT EVAL PROTOTYPING CS2300-CP

0

CDBWM7132-M-2

CDBWM7132-M-2

Cirrus Logic

EVAL BOARD WM7132P 2PC

0

CRD5463PM-Z

CRD5463PM-Z

Cirrus Logic

REFERENCE DESIGN FOR POWER METER

0

CDBWM7216-M-1

CDBWM7216-M-1

Cirrus Logic

EVAL BOARD WM7216

0

CDK47L35-S-1

CDK47L35-S-1

Cirrus Logic

KIT-CS47L35 KIT MARLEY

0

CDBWM7236-M-2

CDBWM7236-M-2

Cirrus Logic

EVAL BOARD WM7236

0

CPB496122-CM2-FB

CPB496122-CM2-FB

Cirrus Logic

MODULE COBRANET 4961 CM2 FB

0

CDB48L10CSP

CDB48L10CSP

Cirrus Logic

EVAL BRD - BASE BOARD AUDIO DSP

0

CDBWM7236-M-1

CDBWM7236-M-1

Cirrus Logic

EVAL BOARD WM7236

0

CDBWM7216-M-2

CDBWM7216-M-2

Cirrus Logic

EVAL BOARD WM7216 2PC

0

CPB181022-CM2-MT

CPB181022-CM2-MT

Cirrus Logic

MODULE COBRANET 1810 CM2 MT

0

CDB42L56

CDB42L56

Cirrus Logic

BOARD EVAL 24BIT ULTRA LP STER C

0

CRD1601-120W-Z

CRD1601-120W-Z

Cirrus Logic

REF DESIGN BRD CS1601 W/120W LLC

0

CDK2000-CLK/KIT2

CDK2000-CLK/KIT2

Cirrus Logic

KIT EVAL PROTOTYPING CS2000-CP

0

CDBWM7331-M-1

CDBWM7331-M-1

Cirrus Logic

EVAL BOARD WM7331

0

CDBWM7132-M-1

CDBWM7132-M-1

Cirrus Logic

EVAL BOARD WM7132 2PC

0

CPB496122-CM2-MT

CPB496122-CM2-MT

Cirrus Logic

MODULE COBRANET 4961 CM2 MT

0

CDBCAPTPL2

CDBCAPTPL2

Cirrus Logic

CAPTUREPLUS II SYSTEM

0

CDB42L55

CDB42L55

Cirrus Logic

BOARD EVAL FOR CS42L55 CODEC

0

Evaluation and Demonstration Boards and Kits

Evaluation and Demonstration Boards and Kits are hardware platforms designed to facilitate the development, testing, and demonstration of electronic systems. They serve as critical tools for engineers and developers to prototype applications, validate designs, and accelerate time-to-market. These boards integrate processors, sensors, communication interfaces, and software ecosystems, enabling rapid experimentation across diverse industries such as IoT, automotive, and industrial automation.

TypeFunctional FeaturesApplication Examples
Microcontroller Development BoardsEmbedded CPUs, GPIOs, integrated peripheralsIoT devices, robotics
FPGA Evaluation BoardsReconfigurable logic, high-speed interfacesCommunication systems, AI accelerators
Sensor Expansion KitsMulti-sensor integration (temperature, motion, etc.)Smart agriculture, environmental monitoring
Wireless Communication ModulesBluetooth/Wi-Fi/LoRa protocols, antenna interfacesConnected healthcare, smart cities

Typical architecture includes: - Processing Units: Microcontrollers, FPGAs, or SoCs - Memory: RAM, Flash, EEPROM - Interfaces: USB, UART, SPI, I2C, Ethernet - Power Management: Regulators, battery connectors - Software Stack: SDKs, device drivers, IDEs Physical designs often feature standardized form factors (e.g., Arduino Uno, Raspberry Pi HATs) for modular expansion.

ParameterDescription
Processor Performance (MHz/GHz)Determines computational capability
Memory Capacity (RAM/Flash)Affects program complexity and data storage
Interface TypesDictates peripheral compatibility
Power Consumption (mW/MHz)Critical for battery-operated devices
Operating Temperature (-40 C to +85 C)Defines environmental durability

- Internet of Things (IoT): Smart home controllers, edge AI nodes - Automotive: ADAS sensor fusion platforms - Industrial Automation: PLC controllers, predictive maintenance systems - Consumer Electronics: Wearables, AR/VR prototypes

ManufacturerRepresentative Products
STMicroelectronicsSTM32 Nucleo Series, SensorTile Kit
IntelIntel Edison, Movidius Neural Compute Stick
XilinxZynq UltraScale+ MPSoC Evaluation Kit
ArduinoArduino MKR Series, Nano 33 IoT

Key considerations: 1. Match processor capabilities to application complexity 2. Verify interface compatibility with target peripherals 3. Assess software ecosystem maturity (e.g., ROS support) 4. Evaluate power budget requirements 5. Consider long-term availability and community support

- Growing adoption of RISC-V-based evaluation platforms - Integration of AI/ML accelerators in edge computing boards - Expansion of open-source hardware ecosystems - Increased focus on energy-efficient architectures for IoT - Standardization of form factors (e.g., SparkFun's Qwiic system)

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