In 1985, Xilinx released the XC2064, the world's first commercial FPGA (Field Programmable Gate Array) chip, marking the beginning of the FPGA era. By 2025, FPGAs will celebrate their 40th anniversary. Over the past 40 years, FPGAs have evolved from communications to industrial applications to becoming an important component in the center of artificial intelligence.
Origins of the field of communication
Early developments: Originally designed to replace small logic boards and simple digital control systems, FPGAs are ideal for rapid prototyping and customization needs in communications equipment.
Growth period: In the 90s, with the advancement of semiconductor technology, FPGAs began to be widely used in telecom switches, routers, and other network equipment. They are used to implement high-speed data transfer protocols, error correction algorithms, and complex signal processing tasks.
Industrial Control & Test & Measurement
Integrate specialized modules: By the early 2000s, FPGA vendors began to integrate specialized hardware modules into their chips, such as multipliers, memory blocks, and high-speed I/O interfaces. This enables FPGAs to handle more complex computational tasks, such as real-time control and monitoring in industrial automation systems.
Transformation in the era of edge computing and AI
Performance Improvements: With the advent of the 28nm process node, FPGAs have made significant progress in performance and energy efficiency. Especially after the rise of deep learning, FPGAs have begun to emerge in the field of AI acceleration due to their parallel computing power and energy efficiency advantages.
Industry M&A: Intel's acquisition of Altera (2015) and AMD's acquisition of Xilinx (2020) reflect the growing centrality of FPGAs in modern computing architectures.
AI applications at the edge: Today, FPGAs play an important role in edge computing scenarios, especially in applications that require low-latency and high-efficiency processing, such as intelligent video analytics, industrial IoT, medical devices, and autonomous driving.
Figure: 40th Anniversary of FPGAs: From Programmable to Ubiquitous, What's Next?
Five trends for FPGAs to move into the future
1. Deeply integrate with AI to become a new force for inference and acceleration
With the increasing diversification and update of AI models, FPGAs are increasingly being used in scenarios such as edge inference, intelligent video analysis, and industrial vision due to their high customizability, low latency, and parallel processing. In the future, the line between AI accelerators and FPGAs will become increasingly blurred.
2. With the rise of chiplets, FPGAs have become important modules for heterogeneous systems
Chiplet designs are reshaping semiconductor architectures. Compared with a single SoC, the modular chip design is easier to flexibly upgrade and integrate into multiple sources. As a flexible computing unit, FPGA is becoming an important piece of the puzzle in the chiplet ecosystem, which can be integrated and packaged with CPU, GPU, AI chips, etc. through interconnection protocols such as UCIe to achieve the optimal energy efficiency ratio for specific tasks.
3. RISC-V and FPGA develop synergistically
The RISC-V ecosystem is a natural fit with FPGAs, which provide an ideal platform for RISC-V core development, testing, and customization. More and more SoC FPGAs are integrating RISC-V controllers, driving the convergence of instruction set architecture innovation and custom hardware.
4. For edge and low-power intelligent applications
Manufacturers such as Lattice and Microchip focus on miniaturized and low-power FPGAs, which are widely used in wearable devices, IoT terminals, smart door locks, drones and other scenarios. These FPGAs are designed to be "lightweight and intelligent" and meet multiple requirements for performance, power, and flexibility.
5. Domestic substitution continues to advance, and ecological construction has become the key
With the progress of local semiconductor technology, domestic FPGA manufacturers such as Unisplendour Tongchuang, Anlu Technology, Zhiduoji, Fudan Microelectronics, etc. are gradually breaking the monopoly of foreign capital, and their products have been implemented in the fields of electric power, rail transit, military industry, and new energy. However, IP cores, EDA tool chains, and ecological support are still bottlenecks restricting the rapid development of the industry, requiring continuous investment and ecological collaboration.
The challenges remain, and the future is worth looking forward to
Although FPGAs have natural advantages in terms of flexibility and customizability, there are still problems such as high development thresholds, difficult power consumption control, and imperfect tool chains. How to further lower the threshold of use and improve the efficiency of software and hardware collaborative development will become the key to determining its position in the next wave of computing.
On the other hand, with the in-depth development of the concept of "software-defined hardware", the form of FPGA is also quietly changing: from a single chip product to IP core, modular hardware, chiplet, SaaS services and other forms. FPGAs may be embedded in more and more intelligent systems in the form of "invisible infrastructure".
