ChatGPT designs and manufactures the first microprocessor! Are chip design engineers dangerous?
Tags: webdev, javascript, programming, ai
Published: 2023-06-20 10:17:39

A team of researchers has successfully designed a microprocessor using plain English instead of a hardware description language. Generative AI like ChatGPT is helping people research, learn and create in ways that were not possible just a few months ago. Now it has begun to find its way into areas such as hardware design.

Dr. Hammond Pearce, a research assistant professor at the Department of Electrical and Computer Engineering and the Center for Cyber Security at New York University Tandon, said that his team's research project Chip Chat was inspired by the desire to explore existing generative artificial intelligence large language models. (LLM) aspirations for capabilities and limitations in the field of hardware design.


![Design flow for creating an IC using LLM](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/dtwva6mu1oxq66udm956.png)

"We're curious to see how good these models are," he said. "A lot of people think that these models are really just toys. I don't think so. They're not ubiquitous yet, but there will definitely be applications in the future. That's why we did Chip Chat—almost like a proof-of-concept demo."

ICs designed with large language models manufactured for the first time

Using chat-based AI assistants could help solve one of the biggest challenges in the chip design industry: hardware description languages (HDL). While HDL codes like Verilog are essential to designing microprocessors, they require very specialized knowledge.

Hardware Description Language (HDL) is a language for describing the behavior, structure, and data flow of electronic system hardware. Using this language, the design of digital circuit systems can describe their own design ideas layer by layer from top to bottom (from abstract to concrete), and use a series of hierarchical modules to represent extremely complex digital systems.

Then, use electronic design automation (EDA) tools to simulate and verify layer by layer, and then combine the modules that need to be turned into actual circuits, and convert them into gate-level circuit netlists through automatic synthesis tools. Next, use ASIC or FPGA automatic layout and routing tools to convert the netlist into the specific circuit wiring structure to be realized.

Hardware Description Language (HDL) has been developed for many years and has been successfully used in all stages of design: modeling, simulation, verification, and synthesis. By the 1980s, hundreds of hardware description languages had appeared, which had greatly promoted and promoted design automation. However, these languages are generally oriented to specific design areas and levels, and the numerous languages make users feel at a loss. Therefore, there is an urgent need for a design-oriented multi-field, multi-level and generally accepted standard hardware description language. In the late 1980s, the VHDL and Verilog HDL languages adapted to the requirements of this trend and became IEEE standards successively.

Dr Pierce said: "The biggest challenge with hardware description languages is that not many people know how to write them. It's hard to be an expert at this, which means we still have the best engineers doing trivial things in these languages because there are no So many engineers can do these things."

In his view, artificial intelligence can speed up the output of engineers, so that artificial intelligence can quickly complete simple things, and engineers can also focus their brainpower on more difficult things.

By making hardware definitions easier to generate, the team believes they can make IC design more accessible and free HDL experts to focus on more important tasks. According to the team, through chat-based generative artificial intelligence, engineers can design microprocessors in plain English instead of HDL.

Using Chip Chat, the team succeeded in designing an 8-bit accumulator-based microprocessor with the same functionality as a comparable PIC product. The chip is then sent to be fabricated on a Skywater 130nm shuttle. The team claims that this research marks the first time an IC designed by LLM has actually been fabricated.


Exploration of ChatGPT and other generative AI in the field of chip design

In fact, after the emergence of ChatGPT, many people began to discuss its potential application in the field of chip design. Chip design is a highly technology-intensive job that requires expertise in multiple fields such as electronics, materials, and physics.

Usually, it requires some professional EDA (Electronic Design Automation) tools, such as logic synthesis, placement and routing, timing analysis, etc. However, these EDA tools require users to have rich professional knowledge and rich design experience, and require users to manually input complex instructions and parameters, which makes chip design a complicated and time-consuming process.

Industry insiders believe that ChatGPT's natural language processing technology can provide a new way for chip design. ChatGPT can automatically generate chip design instructions and parameters by learning existing chip design data and documents, and provide natural language descriptions of solutions to chip design problems. This method can reduce human errors in the chip design process and improve the efficiency and accuracy of chip design.

The code generation capability of ChatGPT can also greatly accelerate the speed of chip design. There is such a case that the quantum control processor is the core control part of the quantum computer. Someone used ChatGPT to synthesize the code of a quantum control processor, as follows:

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/0he2wuuql71gym12of5z.png)
According to reports, although there are some minor problems in this code, such as ChatGPT does not implement timing control well, and there will be a waste of clock cycles, but this code can be compiled correctly and is an effective design solution.

In addition, some people were curious about whether ChatGPT could write a piece of Verilog code, so they tried it. I found that it can not only write a piece of code, but also add an explanation. The industry insider who asked ChatGPT to write Verilog code said that the complete code is very long, and he has not verified it himself, but it looks like it basically has functions.


![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/xjub5q2uroruiyt3rhtl.png)

For overly complex functions, such as the Ethernet protocol stack, when it is written for the first time, it prompts that it is too difficult to write, but after resetting the dialogue, let it write again, and it can write a rough module. There is only a writing interface in it, and then reset the dialog and let it write again, and more programs will be written. This shows that its learning ability has been growing.

Although ChatGPT has its advantages in chip design, there are also some limitations. For example, ChatGPT requires a large amount of chip design data and documents as training data. These data need to be marked and cleaned to ensure that ChatGPT can accurately learn the knowledge and rules of chip design. In addition, the quantity and quality of chip design data directly affect the accuracy and efficiency of ChatGPT in chip design.

For another example, some details in chip design, such as noise, power consumption and other considerations, may require ChatGPT combined with EDA tools for in-depth optimization. In this case, ChatGPT will need to learn and understand the functions and limitations of EDA tools to generate more accurate and feasible chip design instructions and parameters.

Therefore, the application of ChatGPT in chip design cannot completely replace the work of human engineers. Dr Pierce said there will always be tools and jobs that these AIs can't do. There will always be weaknesses in the products they produce.



**summary**

After the emergence of ChatGPT, based on its powerful text and code generation capabilities, people began to explore its application in various fields, including chip design. There are also engineers who use it to write Verilog code, and the basic functions can be realized. Now New York University has used it to design and manufacture a microprocessor, so that the application of ChatGPT in chip design has gone a step further, and the existence of ChatGPT can really solve the challenges that have been difficult to solve in chip design.


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