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Research map / Learning theory and algorithms / Matrix and tensor methods

Coded Sequential Matrix Multiplication For Straggler Mitigation

NeurIPS 2020 · Learning theory and algorithms › Matrix and tensor methods · approach: Randomized sketching for matrices · 9 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use DIP coding across time instead of polynomial codecoded matrix multiplication · NN training, i.i.d. stragglersavg processing time R: 0.152 -> 0.096Helped
use IDIP instead of polynomial codecoded matrix multiplication · NN training, i.i.d. stragglersavg processing time R: 0.152 -> 0.115Helped
use DIP instead of polynomial codecoded matrix multiplication · NN training, Fritchman stragglersavg processing time R: 0.482 -> 0.327Helped
use IDIP instead of polynomial codecoded matrix multiplication · NN training, Fritchman stragglersavg processing time R: 0.482 -> 0.281Helped
add uncoded mini-tasks (IDIP) instead of fully coded DIPcoded sequential matrix multiplication · encoding time, i.i.d. stragglersencoding time: 0.091 -> 0.052Helped

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