| --- |
| 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]) |
