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Obsidian: Cooperative State-Space Exploration for Performant Inference on Secure ML Accelerators

By Sarbartha Banerjee and others
Trusted execution environments (TEEs) for machine learning accelerators are indispensable in secure and efficient ML inference. Optimizing workloads through state-space exploration for the accelerator architectures improves performance and energy consumption. However, such explorations are expensive and slow due to the large search space. Current research has to use fast analytical... Show more
September 4, 2024
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Obsidian: Cooperative State-Space Exploration for Performant Inference on Secure ML Accelerators
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