Log-squared computation and communication cost for Pareto-optimal MP-AMP

From papers

Let TT be the number of MP-AMP iterations, let RaggR_{agg} be the aggregate coding rate, and let MSE\text{MSE} and MMSE\text{MMSE} denote the mean squared error and minimum mean squared error, respectively. Define the excess MSE by

EMSE=MSEMMSE.\text{EMSE}^*=\text{MSE}^*-\text{MMSE}.

MP-AMP cost conjecture. The total computation and communication cost scales as

O(log2(1/EMSE)).O\left(\log^2\left(1/\text{EMSE}^*\right)\right).

This conjecture follows the proposed geometric decay of the quantization error and Pareto-optimal excess MSE with the iteration number, together with the aggregate-rate definition. The paper presents this as an asymptotic prediction for MP-AMP as the MSE approaches the MMSE and does not provide a proof.

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Sources & referencesView supporting material

Primary source

Junan Zhu, Ahmad Beirami and Dror Baron, “Performance Trade-Offs in Multi-Processor Approximate Message Passing”, arXiv:1604.02752 (2016).

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