| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Cirrus Logic |
EVAL BRD FOR CS5484 4-CH IC |
1 |
|
 |
Cirrus Logic |
BOARD EVAL GEN PURPOSE PLL |
5 |
|
 |
Cirrus Logic |
BOARD EVAL FOR CS3318 VOL CTRL |
0 |
|
 |
Cirrus Logic |
EVAL BD - BASE BRD WM8960 |
0 |
|
 |
Cirrus Logic |
EVAL BOARD FOR CS7250B MEMS MIC |
0 |
|
 |
Cirrus Logic |
CS47L15 MINI BOARD |
6 |
|
 |
Cirrus Logic |
EVAL BD - BASE BRD WM1700 |
0 |
|
 |
Cirrus Logic |
BOARD EVAL FOR CS42438 CODEC |
9 |
|
 |
Cirrus Logic |
REFERENCE DESIGN FOR CS42L52 |
1 |
|
 |
Cirrus Logic |
BOARD EVAL FOR CS3310 COL CTRL |
0 |
|
 |
Cirrus Logic |
BOARD EVAL FOR CS5467 ADC |
0 |
|
 |
Cirrus Logic |
BOARD EVAL FOR CS8422 RCVR |
2 |
|
 |
Cirrus Logic |
MOON DAUGHTER BOARD |
32 |
|
 |
Cirrus Logic |
EVAL BRD FOR CS5490 2-CH IC |
2 |
|
 |
Cirrus Logic |
EVAL BD - DSP DAUGHTER CARD DAGD |
0 |
|
 |
Cirrus Logic |
CS47L85 CRAIGDUFF MINI EVAL BRD |
12 |
|
 |
Cirrus Logic |
EVAL BRD CHAS REF BOARD |
4 |
|
 |
Cirrus Logic |
EVAL BD - WM8960 MINI EVAL BOARD |
3 |
|
 |
Cirrus Logic |
BOARD EVAL 2CH ADC/4CH DAC DSP |
0 |
|
 |
Cirrus Logic |
EVAL BOARD MINI HILLSIDE |
1 |
|
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.
| Type | Functional Features | Application Examples |
|---|---|---|
| Microcontroller Development Boards | Embedded CPUs, GPIOs, integrated peripherals | IoT devices, robotics |
| FPGA Evaluation Boards | Reconfigurable logic, high-speed interfaces | Communication systems, AI accelerators |
| Sensor Expansion Kits | Multi-sensor integration (temperature, motion, etc.) | Smart agriculture, environmental monitoring |
| Wireless Communication Modules | Bluetooth/Wi-Fi/LoRa protocols, antenna interfaces | Connected 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.
| Parameter | Description |
|---|---|
| Processor Performance (MHz/GHz) | Determines computational capability |
| Memory Capacity (RAM/Flash) | Affects program complexity and data storage |
| Interface Types | Dictates 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
| Manufacturer | Representative Products |
|---|---|
| STMicroelectronics | STM32 Nucleo Series, SensorTile Kit |
| Intel | Intel Edison, Movidius Neural Compute Stick |
| Xilinx | Zynq UltraScale+ MPSoC Evaluation Kit |
| Arduino | Arduino 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)