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Research map / Architectures and efficiency / RNNs and normalization

Asynchronous Parallel Coordinate Minimization for MAP Inference

NeurIPS 2017 · Architectures and efficiency › RNNs and normalization · approach: Distributed LLM inference systems · 6 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
adaptively reduce number of parallel workers based on estimated delay term (Proposition 1 criterion) (ablation)APCM-Pencil · Synthetic 3-node chain graphconvergence of objectiveHelped
increase workers from 1 to 40 with stale beliefs (ablation)APCM-Pencil · Synthetic 3-node chain graphconvergence of objectiveHurt
use exact block coordinate minimization (Star updates) instead of stochastic gradient stepsAPCM-Star vs HOGWILD! · Disparity estimation grid MRFconvergence speed of dual objectiveHelped
asynchronous parallel coordinate minimization instead of HOGWILD! asynchronous SGDMAP inference on disparity MRF · Disparity estimation grid MRF, connection widths 2/4/8speedup over HOGWILD! at same thread count: ~45x or higherHelped
increase thread count from 1 to 46 for APCM-StarAPCM-Star · Disparity estimation grid MRFspeedup in threadsHelped

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