System-level evaluation reveals that network constraints and hardware costs, rather than raw latency, often dictate the optimal choice between MPC and FHE for privacy-preserving ML.
WarpDrive: GPU-based fully homo- morphic encryption acceleration leveraging tensor and CUDA cores
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Beyond Latency: A System-Level Characterization of MPC and FHE for PPML
System-level evaluation reveals that network constraints and hardware costs, rather than raw latency, often dictate the optimal choice between MPC and FHE for privacy-preserving ML.