We consider $ k $-means clustering of $ n $ data points in Euclidean space in the Massively
Parallel Computation (MPC) model, a computational model which is an abstraction of …

In this paper we study the problem of dynamically maintaining graph properties under
batches of edge insertions and deletions in the massively parallel model of computation. In …

We present $ O (\log\log n) $ round scalable Massively Parallel Computation algorithms for
maximal independent set and maximal matching, in trees and more generally graphs of …

Miller and Reif's FOCS'85 classic and fundamental tree contraction algorithm is a broadly
applicable technique for the parallel solution of a large number of tree problems …

We present a deterministic algorithm for solving a wide range of dynamic programming
problems in trees in O (log D) rounds in the massively parallel computation model (MPC) …

The idea of dynamic programming (DP), proposed by Bellman in the 1950s, is one of the
most important algorithmic techniques. However, in parallel, many fundamental and …

In this paper we study the problem of dynamically maintaining graph properties under
batches of edge insertions and deletions in the massively parallel model of computation. In …

We investigate whether there are inherent limits of parallelization in the (randomized)
massively parallel computation (MPC) model by comparing it with the (sequential) RAM …

Designing parallel algorithms with sublinear space is an inevitable scenario when the input
data does not fit in the memory of available systems. In recent years, with the abundance of …

The impact of massive data processing on our daily lives is becoming increasingly more
clear. With this, we must guarantee that vital, data-driven decision-making systems mitigate …