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View All on GitHubReproducible ML inference benchmarking across heterogeneous hardware: one YAML config drives llama.cpp and ONNX Runtime sweeps on laptops, Raspberry Pi (SSH) and GPUs, with TTFT, throughput, per-rail power, thermal and utilization telemetry in self-describing records, plus publication-quality tables and figures.
Reproducible ML inference benchmarking across heterogeneous hardware: one YAML config drives llama.cpp and ONNX Runtime sweeps on laptops, Raspberry Pi (SSH) and GPUs, with TTFT, throughput, per-rail power, thermal and utilization telemetry in self-describing records, plus publication-quality tables and figures.
Reproducible ML inference benchmarking across heterogeneous hardware: one YAML config drives llama.cpp and ONNX Runtime sweeps on laptops, Raspberry Pi (SSH) and GPUs, with TTFT, throughput, per-rail power, thermal and utilization telemetry in self-describing records, plus publication-quality tables and figures.