GPT OSS 20B MoE Expert Power Traces (320k, ChipWhisperer) This dataset contains analog power traces captured with a ChipWhisperer Husky while running forced single expert MoE computations derived from openai/gpt oss 20b on an NVIDIA H100. What is recorded Each trace corresponds to one capture trial where: 1. A fixed expert id is selected ( expert 00 ... expert 31 ). 2. A random hidden state tensor is generated once per trial . 3. The selected expert computation is executed repeatedly inside one capture window ( expert iters=12 ). 4. ChipWhisperer records a ~10 ms analog trace from the power sensing setup. Important: this is not a full unmodified model forward pass. It is a controlled harness for expert identification side channel experiments. Dataset layout capture meta.json : capture configuration and metadata traces/expert XX/trial YYYYYY.npy : raw captured trace for a class/trial Class count: 32 experts ( expert 00 .. expert 31 ) Samples per class: 10,000 Total traces: 320,000 Trace format File type: NumPy .npy Array dtype: floating point (captured analog samples) Typical duration: ~10 ms per trace Captures include repeated expert activity inside one window (12 repetitions) Base…
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