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40 Years of FPGA: From Logic Arrays to AI at the Edge

·642 words·4 mins
Xilinx FPGA AI ZYNQ
Table of Contents

As AMD celebrates the 40th anniversary of the first Xilinx FPGA, we reflect on its transformative journey and future potential.

The Beginning: 1985
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The story of FPGAs began in 1985, when Xilinx introduced its first commercially available field-programmable gate array. Just a year later, the XC2018 launched with 1,800 gates on a single chip—paving the way for a revolution in customizable hardware.

The vision started in 1984, when Ross Freeman, Bernie Vonderschmitt, and James Barnett left Zilog to create programmable silicon devices. Backed by $862,000 from Kleiner Perkins, their idea gave rise to what would become a $10+ billion industry.

Witness to a Milestone
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In 1986, I covered the XC2018 for EDA Magazine (formerly Silicon Design), as the industry shifted from fixed PALs and costly gate arrays to reconfigurable, user-programmable logic. The Xilinx logic cell array (LCA), built with CMOS technology, democratized hardware design.

Excerpt from that 1986 article:

FPGA
Published in EDA Magazine, 1986

“The Xilinx LCAs combine high density and flexible architecture with the speed of low gate count arrays. Designers can program off-the-shelf parts on an IBM-PC—no high-volume orders or expensive workstations required.”

AMD’s Take: 3 Billion Devices Later
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Fast forward to 2025: AMD (which acquired Xilinx in 2022 for ~$49B) reports over 3 billion FPGAs and adaptive SoCs shipped to 7,000+ customers.

“FPGAs launched a $10+ billion industry,” AMD stated in its June 2025 blog. “Their adaptability has transformed industries from automotive to aerospace.”

Insights from Kirk Saban: Two Decades in FPGAs
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Kirk Saban, AMD’s corporate VP for adaptive and embedded computing, reflects on his 20-year journey:

“From simple CLBs and LUTs to devices with AI engines and 224 Gbps SerDes—it’s been mind-blowing.”

Saban sees FPGAs now at the heart of real-time, low-latency compute systems. Their flexibility and responsiveness make them ideal for AI inference, edge computing, and communications.

Two Major Turning Points
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1. The Zynq Revolution
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Around 2010, Xilinx introduced Zynq, embedding Arm processors with programmable logic. This marked a leap from hardware-only designs to full software-integrated platforms.

“It changed how we talked to customers,” Saban said. “From Verilog to full application stacks.”

Zynq has since become a multi-billion-dollar franchise, central to industries like robotics and automotive.

2. 2.5D Packaging and Chiplets
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At the same time, Xilinx adopted 2.5D chiplet-based integration using TSMC’s CoWoS tech—enabling heterogeneous systems and massive capacity boosts.

“This reshaped FPGA design and influenced how GPUs and AI accelerators are built today.”

FPGA Evolution
Evolution of FPGA technology (Source: AMD)

The Enduring FPGA Advantage
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Despite the rise of GPUs and ASICs, Saban insists FPGAs remain unmatched in adaptability:

“ASICs make sense for millions of units. FPGAs let you move fast, adapt, and keep up with evolving standards.”

Their reprogrammable nature keeps them relevant in fast-moving sectors like defense, industrial automation, and AI.

AMD Synergy: Accelerating the Roadmap
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The AMD acquisition brought scale without disruption.

“AMD let us stay true to our vision. Now, FPGAs are part of a continuum—from embedded chips to cloud accelerators.”

Saban highlights AMD’s broader approach: Arm and RISC-V both play roles alongside x86. The soft-core MicroBlaze V reflects their flexibility.

“People once struggled to pronounce Xilinx. Now we say AMD, and the brand recognition opens doors.”

The Future: Edge AI and Humanoid Robotics
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Saban sees edge AI as the next frontier. Real-time fusion of sensor, vision, and AI workloads plays to the strengths of FPGAs.

“From robotaxis to agriculture to defense, FPGAs enable predictive analytics in safety-critical environments.”

He also points to rising demand for humanoid robots:

“There’s huge interest—especially for hazardous tasks like firefighting. It’s early days, but the momentum is real.”

Conclusion
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After 40 years, FPGAs continue to evolve—adapting to the needs of tomorrow’s intelligent systems. Whether it’s AI at the edge or humanoid robotics, their legacy of flexibility and performance ensures they’ll remain essential in the decades to come.

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