---
license: apache-2.0
language:
- en
tags:
- code-generation
- decompilation
- cuda
- ptx
- llm
---

# Dataset for "Enhancing LLM to Decompile Optimized PTX to Readable CUDA for Tensor Programs" (ASE 2025)

## Dataset Description

This dataset accompanies the paper:

> Sun X, Tang F, Zhang Y, et al. Enhancing LLM to Decompile Optimized PTX to Readable CUDA for Tensor Programs[C]//2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2025: 2235-2247.

It contains pairs of input PTX kernels and output CUDA kernels generated by two auto-schedulers: **Ansor** and **Welder**. The dataset is designed to train and evaluate large language models (LLMs) for the task of decompiling optimized PTX back to human-readable CUDA code.

## Dataset Structure

The dataset is split into four Parquet files:

- `train_ansor.parquet`
- `train_welder.parquet`
- `test_ansor.parquet`
- `test_welder.parquet`

Each file contains samples with the following fields:

| Field    | Type   | Description                                                                 |
|----------|--------|-----------------------------------------------------------------------------|
| `file`   | string | Source JSON filename (without extension). For Ansor, it encodes parameters. |
| `name`   | string or int | Sample identifier (string for Ansor, integer for Welder).                |
| `kernel` | string | (Ansor only) Kernel function name.                                          |
| `input`  | string | Input PTX kernel.                                  |
| `output` | string | Output CUDA kernel.                              |

> **Note**: The `kernel` field is present only in Ansor samples; Welder samples do not have this field.

## Data Splits

| Split          | Number of Samples |
|----------------|-------------------|
| train_ansor    | 371,472           |
| train_welder   | 383,790           |
| test_ansor     | 1,905             |
| test_welder    | 1,793             |

## Usage Example

```python
from datasets import load_dataset

dataset = load_dataset("your-username/ptxdec-dataset")
train_ansor = dataset["train_ansor"]
print(train_ansor[0])