Introduction

Overview

DeepCircuitX is a holistic, repository-level dataset curated to address limitations in existing datasets. It provides data and annotations across multiple levels:

• Chip Level: 109repositories, 5508files.

• IP Level: 225repositories, 12,961files.

• Module Level: 2,383 repositories, 38,692 files.

• RISCV: 2,078 repositories, 98,450 files.

Key Features:

• Multi-level Source RTL code：Repository, file, module, and block

• Multi-level annotations by GPT4o : Repository, file, module, and block.

• Includes synthesized netlists, PPA metrics, and layout designs.

• Benchmarks for RTL understanding, generation, and completion.

Pipeline overview of the proposed framework, illustrating the key stages: data collection from GitHub using keywords, data annotation via chain-of-thought (COT), circuit transformation, and evaluation, including RTL code tasks for LLM and PPA prediction.

Table 1: Dataset Summary of DeepCircuitX

Level	Functional Categories	Number of Repositories	Number of RTL Files
Chip	17	109	5,508
IP	3	225	12,961
Module	57	2,383	38,692
RISC-V	-	2,078	98,450

This table summarizes the number of functional categories, repositories, and RTL files across different levels of DeepCircuitX, including Chip, IP, Module, and RISC-V levels.

Table 2: Overview of Annotations in DeepCircuitX

RTL Category	Module-Level Annotations	Block-Level Annotations	Repository-Level Annotations
Chip	5,471	36,955	84
IP	12,863	20,101	183
Module	28,901	-	1,389
RISC-V	2,116	-	560

The table illustrates the number of annotations at the module, block, and repository levels for various RTL categories.

Table 3: Dataset Counts for RTL Code Tasks

Task	IP	Module	RISC-V	Chip	Total
RTL Code Understanding	6,386	14,499	1,348	3,922	26,155
RTL Code Completion	6,178	14,131	1,312	3,822	25,443
RTL Code Generation	6,479	16,511	1,393	3,950	28,333

This table displays the data distribution for code understanding, completion, and generation tasks across different RTL categories.