AI for Hardware Verification

*** Artificial Neural Network for Hardware Functional Verification - a Survey***

*** Artificial Neural Network for Stimulus Generation Optimization in Hardware Functional Verification***.

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Researches
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My research is about the application of Artificial Intelligence and Machine Learning to hardware verification with my current focus on Artificial Neural Networks.

At the moment I am going to write and publish some works in the following direction:

*** Artificial Neural Network for Hardware Functional Verification - a Survey***
*** Artificial Neural Network for Stimulus Generation Optimization in Hardware Functional Verification as a particular research and development project***.

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Development
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In addition to paper writing, I am also planning to develop some tools, codes, apps for use together with verification tools and environments, either as standalone, plugins or modules for EDA tools. As a eginning I will make some AI tools for
***Stimulus Generation Optimization in Hardware Functional Verification***,
and then more tools will be developed using AI techniques.

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Some Background
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My IC career has been undergoing a long path, telling the whole story is not the purpose of this introductory message. However, I can simply summarize them in the following:

I started designing ICs since 2013.

At first,I have been concentrated on design and verification of ICs and IP cores for wireless communications (modulation and demodulation) during 2018-2022, particularly for satellite broadband Internet.

On the other hand, I have been involving in AI well almost for the same time span as my IC career, since 2013, when I was studying the graph-theoretical aspects of IC (integrated circuits) design, where AI is also key to developing EDA algorithms for VLSI design. A couple of years ago my IC verification activities have also been involving lots of AI/ML techniques and algorithms, as well as my quantum circuits design for example qubit routing which employs deep reinforcement learning to improve the routing efficiency.

My current design focuses on hardware verification, particularly verification with UVM, OSVVM, UVVM, cocotb, ABV (SVA, PSL).

My current research activity in this area is the application of Artificial Intelligence and Machine Learning to hardware verification with my current focus on Neural Networks.

Authoring
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I used also to write the gigantic book series titled “Silicon IP – Not just Design”.

As far as authoring about verification technoogy is concerned, I have been authoring a huge volume of books containing all aspects of the verification processes - from methodologies to languages, from platforms to testing systems. My first book in this direction was related to verification languages with Python, and afterwards SystemC, VHDL, (System)Verilog and a bunch of other verification languages.；then come the verification methodologies - UVM, UVVM, OSVVM, OVM etc.

Books I have drafted include the following:

Protecting Your IP Cores
Review of Verification IP & IP Core Verification – An Abstract
Verification Methodologies - A Concise Introduction
Comprehensive Review of Hardware Verification Languages (Except Python)
Hardware Verification Planning - A Concise Introduction
Hardware Verification Planning Tools
Hardware Verification in Python

人工神经网络与芯片设计验证

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研究项目
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我的研究是关于人工智能和机器学习在芯片设计验证中的应用，我目前的重点是人工神经网络。

目前，我将在以下方向撰写和发布一二篇文章和专著：

*** 人工神经网络在芯片设计验证中的应用的 - 目前研究状况调查报告***

*** 人工神经网络在芯片设计验证中的输入生成优化过程中的应用***。

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工具开发
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除了写论文，我还计划开发一些工具、代码、应用程序，以便与验证工具和环境一起使用，无论是作为独立的、插件还是 EDA 工具的模块。首先，我将制作一些 AI 工具，用于
*** 人工神经网络在芯片设计验证中的输入生成优化过程中的应用***
，然后将使用 AI 技术开发更多工具。

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芯片技术方面的著述
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我曾启动过一个本名为“硅 IP - 不仅仅是设计”的系列专著的写作项目，并起草了其中若干部论著，请参考所附写作清单。

在芯片IP Core的设计验证技术的方面，我撰写了大量书籍，涵盖了验证过程的各个方面 - 从方法论到语言，从平台到测试系统。我在这方面的第一本书与 Python 验证语言有关，之后是 VHDL、(System)Verilog 和一堆其他验证语言；然后是验证方法 - UVM、UVVM、OSVVM、OVM ，SVA等。

我起草的书籍包括以下内容：

保护您的 IP 核
验证 IP 和 IP 核验证综述 - 摘要
验证方法 - 简明介绍
硬件验证语言综合综述（Python 除外）
硬件验证规划 - 简明介绍
硬件验证规划工具
Python 中的硬件验证

今后的计划见前面的陈述。

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我的芯片学习与研究方面的一些背景
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我的 IC 职业生涯经历了漫长的道路，讲述整个故事并不是这篇介绍的目的。但是，我可以简单地总结如下：

我从 2013 年开始设计 IC。

起初，我在 2018-2022 年期间专注于无线通信（调制和解调）的 IC 和 IP 核的设计和验证，特别是卫星宽带互联网。当时我的卫星宽带互联网业务有了一点起色，谈了几个上规模的项目，但没有成功，所以该业务就很快销声匿迹。

另一方面，自 2013 年以来，几乎与从事 IC 研究设计的同时，一直在研究 AI，当时我正在研究 IC（集成电路）后端（物理）设计（尤其是布线）的图论基础，其中 AI 也是开发 VLSI 设计的 EDA 算法的关键。几年前，我的 IC 验证活动也涉及许多 AI/ML 技术和算法，以及我的量子电路设计，例如量子比特路由(qubit routing)，它采用深度强化学习(deep reinforcement learning)来提高路由效率。

我目前的设计侧重于硬件验证，特别是使用 UVM、OSVVM、UVVM、cocotb、ABV（SVA、PSL）进行验证。

我目前在该领域的研究活动是将人工智能和机器学习应用于芯片设计验证，目前重点是神经网络。