| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Xilinx |
KINTEX-7 FPGA KC705 CON EVAL KIT |
1 |
|
 |
Xilinx |
KINTEX-7 FPGA KC705 EVAL KIT |
10 |
|
 |
Xilinx |
DEV KIT CONNECTIVITY SPARTAN 6 |
0 |
|
 |
Xilinx |
EVALUATION KIT ZYNQ-7000 ZC706 |
0 |
|
 |
Xilinx |
KIT EVAL VIRTEX7 VC707 JAPAN |
0 |
|
 |
Xilinx |
KIT EVAL VIRTEX FPGA VCU108 |
20 |
|
 |
Xilinx |
XILINX ZYNQ ULTRASCALE+ MPSOC ZC |
0 |
|
 |
Xilinx |
EVAL BOARD KIT ZCU111 |
50 |
|
 |
Xilinx |
KIT FOR VIRTEX ULTRASCLE FPGA |
0 |
|
 |
Xilinx |
KINTEX-7 FPGA KC705 EMB EVAL KIT |
0 |
|
 |
Xilinx |
SPARTAN7 SP701 FPGA KIT |
50 |
|
 |
Xilinx |
KIT EVAL VIRTEX FPGA VCU108 JP |
0 |
|
 |
Xilinx |
KIT EVAL VCU128 VIRTEX USCALE |
8 |
|
 |
Xilinx |
KIT EVAL ZYNQUS+ MPSOC ZCU104 ED |
9 |
|
 |
Xilinx |
DEV KIT EMBEDDED SPARTAN 6 |
0 |
|
 |
Xilinx |
KIT EVAL ZYNQUS+ MPSOC ZCU106 ED |
5 |
|
 |
Xilinx |
KIT VCU118 VIRTEX ULTRASCALE |
0 |
|
|
Xilinx |
KIT ZUP RFSOC ZCU1275 W/O PS |
0 |
|
|
Xilinx |
EVAL BOARD VIRTEX-7 CHARACTER |
0 |
|
|
Xilinx |
BOARD CHARACTERIZATN KCU1250 JP |
0 |
|
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.
| 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 |
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
| 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 |
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)
| 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 |
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
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)