CROSS compiler maps HE workloads to TPU architecture via basis-aligned and memory-aligned transformations, reporting higher throughput-per-watt than prior GPU and ASIC libraries on NTT and HE operators.
Accelerating number theoretic transformations for bootstrappable homomorphic encryption on gpus
2 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
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15
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PROMISE tool automates mixed-precision tuning with user-defined floating-point formats, validated on linear solvers and Rodinia benchmarks showing many variables can use lower precision safely.
citing papers explorer
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Leveraging ASIC AI Chips for Homomorphic Encryption
CROSS compiler maps HE workloads to TPU architecture via basis-aligned and memory-aligned transformations, reporting higher throughput-per-watt than prior GPU and ASIC libraries on NTT and HE operators.
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Floating-point autotuning with customized precisions
PROMISE tool automates mixed-precision tuning with user-defined floating-point formats, validated on linear solvers and Rodinia benchmarks showing many variables can use lower precision safely.