AMD Xilinx: Complete Guide to Products, History & FPGA Solutions (2026)

If you’ve spent any time in PCB design or embedded systems, you know that Xilinx FPGAs have been the backbone of programmable logic for decades. I’ve personally worked with everything from Spartan-3 boards in my early career to modern Versal ACAPs in complex industrial projects, and the evolution has been remarkable. Now under AMD’s umbrella following the historic $50 billion acquisition, Xilinx technology continues to push boundaries in adaptive computing. This guide breaks down everything you need to know about Xilinx products, their history, and how to select the right FPGA solution for your next project.

What is Xilinx? Understanding the FPGA Pioneer

Xilinx invented the field-programmable gate array in 1984, fundamentally changing how engineers approach digital circuit design. Unlike ASICs that require expensive fabrication for each design iteration, Xilinx FPGAs allow you to program and reprogram hardware logic after manufacturing. This flexibility has made Xilinx devices essential across industries from aerospace and defense to telecommunications and automotive applications.

The company was founded by Ross Freeman, Bernard Vonderschmitt, and James V. Barnett II in Silicon Valley. Their vision was straightforward but revolutionary: create programmable logic devices that would make specialized circuits profitable for smaller production runs. By 1985, they shipped their first commercial FPGA, and by 1987, the company was generating nearly $14 million in annual revenue.

The AMD Acquisition: A New Chapter for Xilinx

On February 14, 2022, AMD completed its acquisition of Xilinx in an all-stock transaction valued at approximately $50 billion. This merger created what AMD calls the “high-performance and adaptive computing leader,” combining AMD’s CPU and GPU expertise with Xilinx’s FPGA and adaptive SoC technologies.

Former Xilinx CEO Victor Peng became president of AMD’s newly formed Adaptive and Embedded Computing Group (AECG). The acquisition expanded AMD’s total addressable market from $80 billion to $135 billion, opening doors to sectors like 5G infrastructure, automotive ADAS, and data center acceleration where Xilinx already had strong footholds.

Acquisition Details	Information
Announcement Date	October 27, 2020
Completion Date	February 14, 2022
Transaction Value	~$50 billion (all-stock)
Exchange Ratio	1.7234 AMD shares per Xilinx share
Combined Engineers	15,000+
Market Expansion	$80B → $135B TAM

Xilinx FPGA Product Families: Complete Breakdown

Understanding the Xilinx product lineup is crucial for selecting the right device for your application. Each family targets specific performance, power, and cost requirements.

Spartan Series: Entry-Level Cost Optimization

The Spartan family represents Xilinx’s most budget-friendly FPGAs, designed for high-volume applications where cost sensitivity is paramount. The Spartan-7 devices, built on 28nm technology, offer the lowest power consumption and smallest footprint in the 7 Series lineup.

Best applications for Spartan FPGAs:

• Consumer electronics
• Industrial sensors and IoT edge devices
• Display interfaces
• Basic motor control systems
• Cost-sensitive embedded applications

Artix Series: Low-Power Performance Balance

Artix FPGAs deliver 50% lower power and 35% lower cost compared to previous Spartan-6 devices while providing enhanced transceiver capabilities. The Artix-7 and Artix UltraScale+ families excel in applications requiring compact form factors with moderate performance requirements.

From my experience designing portable medical devices, Artix devices hit that sweet spot where you need more processing capability than Spartan offers but can’t justify the power budget of larger FPGAs. The integrated transceivers support data rates up to 6.6 Gbps, making them ideal for:

• Software-defined radio systems
• Battery-powered portable equipment
• Machine vision cameras
• Wireless communication systems
• Small form factor embedded applications

Kintex Series: Mid-Range Performance Leader

The Kintex family offers what many PCB engineers consider the best price-performance ratio in the Xilinx portfolio. With 28nm architecture in the 7 Series and 16nm FinFET in UltraScale+, Kintex devices provide substantial logic capacity without Virtex pricing.

Kintex UltraScale+ devices support transceivers up to 32.75 Gbps and offer significant DSP resources for signal processing applications. When I’m designing data acquisition systems or video processing pipelines, Kintex is usually my first consideration.

Kintex Feature	7 Series	UltraScale+
Process Node	28nm	16nm FinFET
Max Logic Cells	480K	1.2M+
Transceiver Speed	13.1 Gbps	32.75 Gbps
Memory Interface	DDR3	DDR4/HBM
Power Efficiency	Good	Excellent

Virtex Series: Maximum Performance

Virtex represents Xilinx’s flagship FPGA family for the most demanding applications. These devices support over 2 million logic cells, 58 Gbps transceivers, and High Bandwidth Memory (HBM) integration in UltraScale+ variants.

Virtex FPGAs power critical infrastructure in:

• High-performance computing clusters
• Advanced radar and electronic warfare systems
• 5G wireless infrastructure
• Data center acceleration
• CERN particle physics experiments (the ALICE experiment uses Virtex devices)

The Virtex-7 2000T, introduced in 2011, pioneered 2.5D stacked silicon technology, combining four smaller FPGAs into a single package with 6.8 billion transistors. This breakthrough enabled logic densities impossible with monolithic silicon.

Zynq SoC Family: Processor + FPGA Integration

The Zynq family revolutionized embedded design by integrating ARM Cortex processors directly with programmable logic on a single chip. This eliminates the need for separate processor and FPGA devices, reducing board complexity and power consumption.

Zynq-7000 SoC:

• Dual-core ARM Cortex-A9 processors
• 28nm programmable logic fabric
• Ideal for embedded vision and motor control

Zynq UltraScale+ MPSoC:

• Quad-core ARM Cortex-A53 application processors
• Dual-core ARM Cortex-R5F real-time processors
• Mali-400 GPU integration
• Available in EV variants with H.264/H.265 video codec

The MPSoC achieved IEC 61508 SIL 3 certification in 2018, enabling deployment in safety-critical automotive, aerospace, and industrial applications.

Versal ACAP: The Future of Adaptive Computing

Versal represents Xilinx’s most ambitious architecture, introducing the Adaptive Compute Acceleration Platform (ACAP) concept. Built on TSMC’s 7nm process, Versal combines:

• Scalar Engines: Dual-core ARM Cortex-A72 and Cortex-R5F processors
• Adaptable Engines: Traditional programmable logic fabric
• AI Engines: High-performance VLIW/SIMD vector processors
• Network-on-Chip (NoC): Integrated routing infrastructure

The AI Engines deliver over 100X greater compute performance compared to server-class CPUs for machine learning inference workloads. AMD offers two AI Engine variants: AIE for balanced signal processing and ML workloads, and AIE-ML optimized specifically for machine learning applications.

Versal Product Lines:

Versal Series	Target Application	Key Features
AI Core	Data center AI	Highest AI Engine count
AI Edge	Edge inference	Power-optimized AI
Prime	General purpose	Balanced logic/memory
Premium	Communications	112G PAM4 transceivers
HBM	High bandwidth	Integrated HBM memory

AMD has committed to Versal AI Core, AI Edge, Prime, Premium, and RF Series availability through 2045+, providing long-term support critical for aerospace, defense, and industrial applications with extended product lifecycles.

Xilinx FPGA Selection Guide: Choosing the Right Device

$$$-$$$-$$$$$

Family	Logic Cells	Best For	Typical Cost Range
Spartan-7	6K-102K	Cost-sensitive, high-volume	$
Artix-7	13K-215K	Low-power, transceiver apps	$$
Artix UltraScale+	40K-370K	Cost-optimized performance	$$
Kintex-7	65K-480K	Balanced performance/cost	$$$
Kintex UltraScale+	350K-1.2M	High-bandwidth applications	$$$$
Virtex-7	326K-2M	Highest performance
Virtex UltraScale+	862K-6M	Maximum capability
Zynq-7000	28K-444K	Embedded processing + logic
Zynq UltraScale+	154K-930K	High-end embedded
Versal (all series)	128K-3.7M	AI, adaptive computing

Xilinx Development Tools and Software Ecosystem

One aspect that separates successful FPGA projects from troubled ones is toolchain familiarity. Having worked across multiple FPGA vendors, I can say the Xilinx/AMD tool ecosystem has matured significantly over the past decade. Understanding these tools is essential for efficient development.

Vivado Design Suite

Vivado replaced the legacy ISE Design Suite in 2012, providing a modern development environment for 7 Series and newer devices. The suite includes:

• Vivado IP Integrator: Block-based design entry for rapid system integration
• Vivado HLS: High-Level Synthesis for C/C++ to RTL conversion
• Vivado Simulator: Integrated behavioral and timing simulation
• Vivado Logic Analyzer: Real-time debugging via integrated logic analyzer cores

The 2025.2 release added production support for Versal AI Edge Series Gen 2 and Versal Prime Series Gen 2 devices, along with SystemVerilog interface support for simplified AXI connections.

Vivado Licensing Options:

Edition	Cost	Supported Devices
Vivado ML Standard	Free	Entry-level devices
Vivado ML Enterprise	Subscription	All devices + advanced features
Vivado Lab Edition	Free	Programming/debug only

Pro Tip from the Field: When working on timing-critical designs, enable the incremental compilation feature in Vivado. This preserves successful placement and routing from previous runs, dramatically reducing iteration time when making small RTL changes. I’ve seen compile times drop from 4+ hours to under 30 minutes on complex Kintex UltraScale+ designs using this approach.

Vitis Unified Software Platform

Launched in October 2019, Vitis provides higher-level abstraction for software developers who may not have traditional FPGA experience. The platform includes:

• Vitis AI: Deep learning inference optimization for AMD devices
• Vitis HLS: Enhanced high-level synthesis from C/C++
• Vitis Model Composer: MATLAB/Simulink integration
• Accelerated Libraries: Pre-optimized functions for common operations

Vitis AI supports TensorFlow, PyTorch, and Caffe neural networks, enabling AI/ML developers to deploy models without learning VHDL or Verilog.

PetaLinux Tools

PetaLinux provides a Yocto-based embedded Linux development framework specifically for Zynq and Versal devices. It simplifies bootloader configuration, kernel customization, and root filesystem creation.

More Xilinx FPGAs:

Xilinx Kria System-on-Modules: Ready-to-Deploy Solutions

The Kria SOM portfolio represents Xilinx’s push toward simplified deployment for edge AI applications. These production-ready modules eliminate the need for custom board design while maintaining flexibility through carrier board interfaces.

Kria K26 SOM

The flagship K26 SOM features a custom Zynq UltraScale+ MPSoC with:

• 256K logic cells
• Quad-core ARM Cortex-A53 at 1.2 GHz
• 4GB DDR4 memory onboard
• 245 user I/Os via dual 240-pin connectors
• Commercial grade ($250) and industrial grade ($350) options

Kria K24 SOM

Introduced for cost-optimized DSP-intensive applications like motor control, the K24 offers:

• Lower power consumption (approximately 2X lower latency than competing solutions)
• 132 user I/Os
• TSN-enabled networking with 4x 1G Ethernet
• Hardware root of trust with discrete TPM 2.0

Starter Kits

Kit	Price	Target Application
KV260 Vision AI	$199	Smart vision, robotics
KR260 Robotics	$349	Industrial automation
KD240 Drives	$299	Motor control, power

Xilinx Applications Across Industries

The flexibility of programmable logic makes Xilinx FPGAs suitable for virtually any application requiring custom digital logic, parallel processing, or hardware-level timing control. Here’s where I’ve seen these devices deployed most successfully across my engineering career.

Aerospace and Defense

Xilinx offers defense-grade (XQ) and space-grade (XQR) variants specifically designed for harsh environments. The XQR Versal for Space 2.0 line provides radiation-tolerant FPGAs for satellite applications, with some variants 1,000 times less sensitive to space radiation than commercial equivalents.

Key defense applications include:

• Phased array radar with adaptive beamforming
• Electronic warfare signal processing
• Satellite communication systems
• Avionics and UAV control systems
• Secure communications infrastructure

The Versal Premium series with 112G PAM4 transceivers enables 4X greater signal processing capacity compared to previous generations, critical for next-generation radar systems operating in spectrum-contested environments. The platform supports various data types including single-precision floating-point for greater dynamic range in radar applications.

Automotive and ADAS

The XA (Xilinx Automotive) product line meets AEC-Q100 qualification requirements for automotive deployment. ZF Friedrichshafen uses Xilinx Zynq devices in its ProAI automotive control unit for automated driving applications.

Automotive Use Cases:

• LiDAR signal processing and point cloud generation
• Camera sensor fusion for ADAS
• Powertrain control systems
• In-vehicle infotainment
• Vehicle-to-everything (V2X) communications

A research paper from May 2024 demonstrated AMD Xilinx ZCU104 FPGA implementation for pavement defect detection in ADAS applications, using Deep Learning Processing Units (DPU) to execute YOLOv3 models for real-time identification of road surface defects with high accuracy and efficiency.

Data Center Acceleration

The Alveo accelerator card family provides PCIe-based FPGA acceleration for data centers. The portfolio includes:

• Alveo U200/U250: General-purpose acceleration
• Alveo U280: High-bandwidth memory variant
• Alveo U55C: Machine learning optimized
• Alveo SN1000: SmartNIC with integrated networking

Telecommunications and 5G

Xilinx FPGAs power critical 5G infrastructure components, handling baseband processing, fronthaul/backhaul interfaces, and network acceleration. The flexibility of programmable logic enables operators to update radio algorithms as standards evolve.

Useful Resources for Xilinx Development

Official Documentation and Downloads

Resource	URL	Description
AMD Documentation Hub	docs.amd.com	Technical documentation, datasheets
Vivado Download	xilinx.com/support/download.html	Design tools and updates
Adaptive Computing Wiki	xilinx-wiki.atlassian.net	Community-maintained guides
GitHub Libraries	github.com/Xilinx	Open-source IP and examples

Development Boards and Evaluation Kits

Board	Device	Price Range	Target Use
Basys 3	Artix-7 A35T	~$179	Education, entry-level
Arty A7	Artix-7 A35T/A100T	~$149-249	Maker projects, prototyping
ZCU104	Zynq US+ ZU7EV	~$1,295	Embedded vision, AI
VCK190	Versal AI Core	~$5,995	AI/ML development
VEK280	Versal AI Edge	~$3,495	Edge AI applications

Third-Party Learning Resources

Several excellent resources exist for learning Xilinx FPGA development:

• Digilent Reference Designs: Example projects for Digilent boards
• AMD University Program: Academic curriculum and materials
• FPGA4Fun: Practical tutorials and project ideas
• Nandland: Beginner-friendly VHDL and Verilog tutorials

Frequently Asked Questions About Xilinx

What happened to Xilinx after the AMD acquisition?

Xilinx became AMD’s Adaptive and Embedded Computing Group (AECG) following the February 2022 acquisition. The Xilinx brand was gradually phased out by June 2023, but all product lines continue under AMD branding. Victor Peng, former Xilinx CEO, initially led the AECG division. Current products, documentation, and support are accessible through AMD’s website, though many engineers still refer to the technology as “Xilinx FPGAs.”

How do I choose between Xilinx and Intel (Altera) FPGAs?

Both vendors offer comparable capabilities, so the choice often comes down to specific requirements. Xilinx (AMD) currently holds approximately 52% market share versus Intel’s 35%. Key differentiators include tool ecosystem familiarity, existing IP compatibility, specific device features, and regional sales support. If your team has experience with Vivado and Vitis, staying with AMD devices reduces learning curve. Similarly, if you have existing Intel Quartus Prime designs, migration costs may outweigh any technical advantages.

What is the difference between an FPGA and an ASIC?

FPGAs contain programmable logic blocks that can be configured after manufacturing, allowing unlimited design iterations without fabrication costs. ASICs (Application-Specific Integrated Circuits) have fixed functionality etched during manufacturing, offering higher performance and lower per-unit cost at high volumes but requiring expensive mask sets and long lead times. Xilinx FPGAs serve as ASIC alternatives for low-to-medium volume production or applications requiring field upgradability.

Can I use Xilinx FPGAs for AI and machine learning?

Absolutely. AMD’s Vitis AI platform enables deployment of TensorFlow, PyTorch, and Caffe models on Xilinx devices. The Versal ACAP architecture includes dedicated AI Engines delivering over 100X compute performance compared to CPUs for inference workloads. The Kria SOM family specifically targets edge AI vision applications with pre-built accelerated applications available through the AMD app store.

Are older Xilinx FPGAs still supported?

AMD continues manufacturing legacy devices (Spartan-6, Virtex-6, and earlier) for existing designs, though they’re not recommended for new development. The ISE Design Suite supports these older devices but hasn’t received feature updates since 2013. For new projects, AMD recommends 7 Series or newer devices supported by Vivado.

Making the Right Xilinx Choice for Your Project

After years of working with Xilinx devices across industrial automation, telecommunications, and embedded vision projects, my advice is straightforward: start with your constraints. If power budget is critical, look at Artix or Spartan. If you need raw processing capability, Virtex is your path. For embedded systems requiring both processor flexibility and hardware acceleration, the Zynq family eliminates integration headaches.

The Kria SOMs deserve special mention for teams lacking extensive FPGA experience. The $199 KV260 starter kit running Ubuntu provides an approachable entry point that you can have running vision AI demos within an hour of unboxing. That accessibility was unimaginable when I first started working with Xilinx devices that required weeks of board bring-up.

Security Considerations for Xilinx Designs

An often-overlooked aspect of FPGA design is bitstream security. Xilinx provides several protection mechanisms:

• AES-256 bitstream encryption: Prevents reverse engineering of your design
• eFuse key storage: One-time programmable secure key storage
• Battery-backed SRAM keys: Enables self-destruct capability upon tampering
• Device DNA: Unique per-device identifier for licensing and authentication
• Hardware root of trust: Built into UltraScale+ and Versal architectures

For designs destined for defense or high-security commercial applications, leverage the XQ device variants that include additional anti-tamper features and controlled mask sets.

Cost Optimization Strategies

When budgeting for Xilinx projects, consider these approaches from my experience:

1. Right-size your device: Use Vivado’s resource utilization reports early in development. Many designs can drop to a smaller device with careful optimization.
2. Consider speed grades carefully: The -1 speed grade often meets timing requirements at significantly lower cost than -2 or -3 variants. Only specify faster grades when timing analysis proves necessary.
3. Evaluate package options: Wire-bond packages cost less than flip-chip for equivalent devices. If your I/O requirements fit, significant savings are possible.
4. Plan for production volumes: For quantities exceeding 50,000 units, investigate EasyPath FPGA options that reduce per-unit cost while maintaining drop-in compatibility with standard devices.

Whatever your application, the combined AMD-Xilinx ecosystem now offers the most comprehensive adaptive computing portfolio in the industry. The real question isn’t whether Xilinx technology can meet your needs—it’s which product line best matches your performance, power, and budget requirements.

The FPGA market is projected to reach $13.5 billion by 2032, driven by AI, IoT, and edge computing demands. Whether you’re prototyping a new embedded system, accelerating data center workloads, or designing the next generation of 5G infrastructure, AMD’s Xilinx technology provides the programmable foundation to bring your vision to production.