Coded distributed computing is an effective framework to improve the speed of distributed computing systems by mitigating stragglers (temporarily slow workers). In essence, coded computing allows replacing the computation assigned to a straggling worker by that at a faster worker by assigning redundant computations. Coded computing techniques proposed so far are mostly based on univariate polynomial coding. These codes are not very effective if storage and computation capacity across workers are heterogeneous and lose completely the work done by the straggling workers. For the particular problem of distributed matrix-matrix multiplication, we show how bivariate polynomial coding addresses these two issues.
Bivariate Hermitian Polynomial Coding for Efficient Distributed Matrix Multiplication / Hasircioglu, B.; Gomez-Vilardebo, J.; Gunduz, D.. - (2020), pp. 1-6. ((Intervento presentato al convegno 2020 IEEE Global Communications Conference (GLOBECOM) on Advanced Technology for 5G Plus tenutosi a twn nel 7-11 Dec [10.1109/GLOBECOM42002.2020.9322629].