在科技的前沿，人工智能与硬件设计的结合正逐渐成为推动行业进步的关键力量。近日，由佐治亚理工EIC实验室与Nvidia公司联合举办的LLM4HWDesign@ICCAD 2024竞赛正式拉开帷幕，旨在通过大语言模型（LLM）的辅助，探索和提升硬件设计的自动化水平。
#### 大赛背景与目标
随着科技的不断进步，大语言模型在各个领域的应用日益广泛，但在硬件设计这一特定领域，其潜力尚未得到充分挖掘。当前，最先进的人工智能模型在生成硬件设计代码时，往往需要大量的人工干预才能达到实用水平。为解决这一挑战，LLM4HWDesign@ICCAD 2024竞赛应运而生。此次大赛旨在通过构建开源、高质量的硬件代码数据集，进一步提升LLM在辅助硬件设计中的性能，从而实现自动化数据生成、收集、清洗和标注方法的创新，为硬件设计领域带来革命性的变革。
#### 大赛流程与任务
竞赛分为两阶段进行。第一阶段（7月7日至8月10日）将专注于数据样本的收集和生成。参赛者需从开源代码库、学术论文以及专有设计等多渠道收集新的Verilog代码样本，确保所有收集的数据适用于开源和公共使用。这一阶段的关键任务包括高效的数据收集策略、创新的数据生成方法以及对数据样本的精心筛选和标注工作，以构建一个全面、高质量的数据集，为后续的模型训练奠定坚实基础。
### 结语
LLM4HWDesign@ICCAD 2024竞赛不仅是一次技术挑战，更是对人工智能与硬件设计融合可能性的探索。通过这一平台，来自全球的精英们将有机会共同参与这场创新之旅，推动硬件设计领域向自动化、智能化方向迈进。随着竞赛的深入，我们期待看到更多创新成果的涌现，为未来的科技发展注入新的活力。
英语如下：
### Georgia Tech and Nvidia Collaborate in LLM4HWDesign @ ICCAD 2024, Launching a New Era in AI-Assisted Hardware Design
At the forefront of technology, the convergence of artificial intelligence (AI) and hardware design is emerging as a critical driver of industry advancement. Recently, the LLM4HWDesign @ ICCAD 2024 competition, jointly organized by Georgia Tech’s EIC Lab and Nvidia, has officially kicked off. This initiative aims to leverage large language models (LLMs) to explore and enhance the automation of hardware design.
#### Background and Objectives
With continuous technological progress, large language models are increasingly being applied across various fields. However, their potential in the specific domain of hardware design has not been fully explored. Currently, the most advanced AI models often require substantial human intervention to reach practical levels when generating hardware design code. To tackle this challenge, LLM4HWDesign @ ICCAD 2024 was conceived. The competition is focused on developing an open-source, high-quality hardware code dataset to further improve the performance of LLMs in assisting hardware design. This is aimed at innovating methods for automated data generation, collection, cleaning, and annotation, thereby revolutionizing the hardware design domain.
#### Competition Structure and Tasks
The competition is divided into two phases. The first phase (July 7 to August 10) centers on data sample collection and generation. Participants are tasked with gathering new Verilog code samples from open-source code repositories, academic papers, and proprietary designs, ensuring that all collected data is suitable for open and public use. The key tasks in this phase include developing efficient data collection strategies, innovative data generation methods, and meticulous selection and annotation of data samples to construct a comprehensive, high-quality dataset for subsequent model training.
### Conclusion
LLM4HWDesign @ ICCAD 2024 is not merely a technical challenge; it’s a pioneering exploration into the potential of AI integration with hardware design. Through this platform, global elites will have the opportunity to jointly embark on this innovative journey, driving the hardware design domain towards automation and intelligence. As the competition progresses, we anticipate the emergence of innovative outcomes that will infuse new energy into future technological development.
【来源】https://www.jiqizhixin.com/articles/2024-07-15
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