Evaluation Boards - Embedded - Complex Logic (FPGA, CPLD)

Part Number	Description / PDF	Quantity
MCVEVP-2DB ARIES Embedded	EVK CYCLONEV SOC-FPGA	12
MCVEVP-X6DB ARIES Embedded	EVK CYCLONEV SOC-FPGA	12
SPIDERBASE MX10S16 ARIES Embedded	EVALUATIONKIT MAX10 FPGA	0
M100PFEVP-1ACI ARIES Embedded	EVK POLARFIRE FPGA MPF100T	12
MCXLEVK-S055BC-I ARIES Embedded	EVK CYCLONE10LP FPGA	18
M100PFEVP-3ACI ARIES Embedded	EVK POLARFIRE FPGA MPF300T	4
MCVEVP-6DB ARIES Embedded	EVK CYCLONEV SOC-FPGA	12
SPIDERBASE L ARIES Embedded	EVALUATIONKIT MAX10 FPGA	20
SPIDERBASE MX10U ARIES Embedded	EVALUATIONKIT MAX10 FPGA	0
MCVEVP-X2DB ARIES Embedded	EVK CYCLONEV SOC-FPGA	12
MCXLEVK-H055BBB-I ARIES Embedded	EVK CYCLONE10LP FPGA	5
SPIDERBASE S ARIES Embedded	EVALUATIONKIT MAX10 FPGA	15
M100PFEVP-2ACI ARIES Embedded	EVK POLARFIRE FPGA MPF200T	9

Evaluation Boards - Embedded - Complex Logic (FPGA, CPLD)

1. Overview

Evaluation boards for Field-Programmable Gate Arrays (FPGAs) and Complex Programmable Logic Devices (CPLDs) are hardware platforms designed to test and develop embedded systems using reconfigurable logic. These boards enable engineers to prototype custom digital circuits without permanent integrated circuit fabrication. As key tools in modern electronics development, they support rapid iteration for applications ranging from aerospace systems to consumer electronics.

2. Main Types and Functional Classification

Type	Functional Features	Application Examples
FPGA Evaluation Board	High logic density, reconfigurable fabric, DSP blocks, high-speed transceivers	5G baseband processing, AI accelerators
CPLD Development Kit	Lower power consumption, non-volatile configuration, simpler architecture	Industrial motor control, protocol bridging
SoC Embedded Board	Combines FPGA fabric with hard processor cores (ARM, RISC-V)	Smart sensors, autonomous vehicle perception systems
Prototype Verification Platform	Multi-FPGA systems with clock/data synchronization	ASIC pre-validation, high-energy physics experiments

3. Structure and Components

Typical evaluation boards include: - FPGA/CPLD chip with BGA packaging - On-board memory (DDR4 SDRAM, QDR SRAM) - Communication interfaces (PCIe Gen4, Gigabit Ethernet, USB 3.2) - Power management circuits with multiple voltage rails - Debug interfaces (JTAG, UART, FTDI chips) - Expansion headers (FMC, PMOD) - Oscillators and clock distribution networks

4. Key Technical Specifications

Parameter	Description
Logic Elements Count	Defines design complexity capacity (e.g., 500K-2M LUTs for high-end FPGAs)
Max Clock Frequency	Determines processing speed (up to 1.6GHz for networking applications)
I/O Count & Standards	Supports LVDS, SSTL, HSTL (e.g., 1024 differential pairs)
Power Consumption	Thermal design power (TDP) range 5W-35W
Memory Bandwidth	Up to 256-bit AXI interfaces with 1866MT/s DDR4
Transceiver Speed	28Gbps/58Gbps serial links for optical communication

5. Application Areas

Major industries include: - Telecommunications (5G NR base stations, optical transport) - Industrial Automation (real-time motion control, machine vision) - Automotive (ADAS sensor fusion, autonomous driving) - Medical Imaging (ultrasound beamforming, MRI reconstruction) - Consumer Electronics (AR/VR video processing) - Scientific Research (particle detector data acquisition)

6. Leading Manufacturers and Products

Manufacturer	Representative Product
Xilinx (AMD)	Zynq UltraScale+ MPSoC ZCU106
Intel (Altera)	Stratix 10 GX 10M Evaluation Board
Lattice Semiconductor	iCE40 UltraPlus Breakout Board
Microchip (Microsemi)	SmartFusion2 SoC FPGA Development Kit
Allwinner (China)	Tang Nano 9K FPGA Module

7. Selection Guidelines

Key considerations: - Match logic density to design complexity with 20% margin - Verify interface compatibility (e.g., PCIe Gen5 vs Gen4) - Assess power delivery capability for worst-case scenarios - Check toolchain support (Vivado, Quartus, Lattice Diamond) - Consider thermal management requirements - Evaluate available IP core ecosystem - Compare cost/performance ratio for production scalability

8. Industry Trends

Emerging trends include: - AI/ML acceleration with quantized neural networks - Heterogeneous integration (photonics, RF components) - Open-source toolchain development (e.g., Yosys, SymbiFlow) - Energy-efficient architectures for edge computing - Increased adoption in safety-critical systems (ISO 26262 compliance) - Growth of RISC-V based FPGA SoCs - China's domestic substitution initiatives (Huawei HiSilicon, Phytium)