Super-squash branch 'main' using huggingface_hub

README.md

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+---
+title: ascad-v2-1
+tags:
+- side-channel-analysis
+- cryptography
+- DLSCA
+parameters:
+  HF_ORG: DLSCA
+  CHUNK_SIZE_Y: 50000
+  CHUNK_SIZE_X: 200
+  TOTAL_CHUNKS_Y: 2
+  TOTAL_CHUNKS_X: 5000
+  NUM_JOBS: 10
+  LOCAL: True
+  CLOUD: False
+  COMPRESSED: True
+---
+
+# ascad-v2-1
+
+This script downloads, extracts, and uploads the optimized ASCAD v2 (1-100k traces) dataset to Hugging Face Hub.
+
+## Dataset Structure
+
+This dataset is stored in Zarr format, optimized for chunked and compressed cloud storage.
+
+### Traces (`/traces`)
+- **Shape**: `[100000, 1000000]` (Traces x Time Samples)
+- **Data Type**: `int8`
+- **Chunk Shape**: `[50000, 200]`
+
+### Metadata (`/metadata`)
+- **ciphertext**: shape `[100000, 16]`, dtype `uint8`
+- **key**: shape `[100000, 16]`, dtype `uint8`
+- **mask**: shape `[100000, 16]`, dtype `uint8`
+- **mask_**: shape `[100000, 16]`, dtype `uint8`
+- **plaintext**: shape `[100000, 16]`, dtype `uint8`
+- **rin**: shape `[100000, 1]`, dtype `uint8`
+- **rin_**: shape `[100000, 1]`, dtype `uint8`
+- **rm**: shape `[100000, 1]`, dtype `uint8`
+- **rm_**: shape `[100000, 1]`, dtype `uint8`
+- **rout**: shape `[100000, 1]`, dtype `uint8`
+- **rout_**: shape `[100000, 1]`, dtype `uint8`
+
+## Parameters Used for Generation
+
+- **HF_ORG**: `DLSCA`
+- **CHUNK_SIZE_Y**: `50000`
+- **CHUNK_SIZE_X**: `200`
+- **TOTAL_CHUNKS_Y**: `2`
+- **TOTAL_CHUNKS_X**: `5000`
+- **NUM_JOBS**: `10`
+- **LOCAL**: `True`
+- **CLOUD**: `False`
+- **COMPRESSED**: `True`
+
+## Usage
+
+You can load this dataset directly using Zarr and Hugging Face File System:
+
+```python
+import zarr
+from huggingface_hub import HfFileSystem
+
+fs = HfFileSystem()
+
+# Map only once to the dataset root
+root = zarr.open_group(fs.get_mapper("datasets/DLSCA/ascad-v2-1"), mode="r")
+
+# Access traces directly
+traces = root["traces"]
+print("Traces shape:", traces.shape)
+
+# Access plaintext metadata directly
+plaintext = root["metadata"]["plaintext"]
+print("Plaintext shape:", plaintext.shape)
+```

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+        "checksum": true
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+  "node_type": "array",
+  "storage_transformers": []
+}

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