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--- |
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license: mit |
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dataset_info: |
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features: |
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- name: filename |
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dtype: string |
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- name: cuda_source |
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dtype: string |
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- name: cuda_host |
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dtype: string |
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- name: cuda_device |
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dtype: string |
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- name: hip_source |
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dtype: string |
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- name: hip_host |
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dtype: string |
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- name: hip_device |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 18979794237 |
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num_examples: 70694 |
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- name: stack |
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num_bytes: 6087813411 |
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num_examples: 24170 |
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- name: synth |
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num_bytes: 11766271412 |
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num_examples: 40591 |
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- name: bench |
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num_bytes: 3676152 |
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num_examples: 40 |
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download_size: 10789629544 |
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dataset_size: 36837555212 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: stack |
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path: data/stack-* |
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- split: synth |
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path: data/synth-* |
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- split: bench |
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path: data/bench-* |
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--- |
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# 💻 CASS: CUDA–AMD Assembly and Source Mapping |
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[CASS](https://huggingface.co/datasets/MBZUAI/CASS) is the **first large-scale dataset** for cross-architecture GPU transpilation, providing semantically aligned CUDA–HIP source pairs and their corresponding host/device assemblies for **NVIDIA (SASS)** and **AMD (RDNA3)** platforms. It enables research in: |
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* 🔁 Source-to-source translation (CUDA ↔ HIP) |
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* ⚙️ Assembly-level translation (SASS ↔ RDNA3) |
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* 🧠 LLM-guided GPU code transpilation |
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--- |
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## 📚 Dataset Structure |
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Each sample contains the following fields: |
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| Field | Description | |
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| ------------- | ------------------------------------------ | |
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| `filename` | Sample ID or file name | |
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| `cuda_source` | Original CUDA source code | |
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| `cuda_host` | Compiled x86 host-side assembly from CUDA | |
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| `cuda_device` | Compiled SASS (Nvidia GPU) device assembly | |
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| `hip_source` | Transpiled HIP source code (via HIPIFY) | |
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| `hip_host` | Compiled x86 host-side assembly from HIP | |
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| `hip_device` | Compiled RDNA3 (AMD GPU) device assembly | |
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--- |
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## 🔀 Dataset Splits |
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| Split | Description | # Examples | |
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| ------- | ----------------------------------------- | ---------- | |
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| `train` | Union of `synth`, `stack`, and `opencl` | 70,694 | |
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| `synth` | LLM-synthesized CUDA programs | 40,591 | |
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| `stack` | Scraped and filtered CUDA from StackV2 | 24,170 | |
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| `bench` | 40 curated eval tasks from 16 GPU domains | 40 | |
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--- |
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## 📦 How to Load |
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```python |
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from datasets import load_dataset |
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# 🧠 Load the full dataset (default config with all splits) |
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cass = load_dataset("MBZUAI/cass", name="default") |
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# Access a specific split |
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train_data = cass["train"] # train = stack + synth + opencl |
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stack_data = cass["stack"] |
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synth_data = cass["synth"] |
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bench_data = cass["bench"] |
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``` |
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--- |
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## 📈 Benchmark and Evaluation |
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The `bench` split includes 40 samples across 16 domains like: |
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* 🧪 Physics Simulation |
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* 📊 Data Structures |
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* 📸 Image Processing |
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* 🧮 Linear Algebra |
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All samples have been manually verified for semantic equivalence across CUDA and HIP and come with executable device/host binaries. |
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--- |
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## 📄 License |
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Released under the **MIT license**. |
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--- |
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## 🔗 Useful Links |
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* 🤗 Hugging Face Collection: [CASS on Hugging Face](https://huggingface.co/collections/MBZUAI/cass-6825b5bf7414503cf16f87b2) |
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* 📂 Code & Tools: [GitHub Repository](https://github.com/GustavoStahl/CASS) |
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* Paper: [Arxiv CASS](https://arxiv.org/abs/2505.16968) |
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