Algorithms for a Topology-aware Massively Parallel Computation Model

Hu, Xiao; Koutris, Paraschos; Blanas, Spyros

doi:10.1145/3452021.3458318

Cited by 2 publications

(2 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data redistribution problem. This problem arises merely by changing the underlying network topology of [11] from trees to full connected graphs. We have claimed that the communication lower bounds given in [11] is not applicable for full connected networks.…”

Section: Declaration Of New Research Problemsmentioning

confidence: 99%

“…This problem arises merely by changing the underlying network topology of [11] from trees to full connected graphs. We have claimed that the communication lower bounds given in [11] is not applicable for full connected networks. Using the parallel sorting as an introducing example, we define a new problem called Data Redistribution Problem (DRP).…”

Section: Declaration Of New Research Problemsmentioning

confidence: 99%

See 1 more Smart Citation

A New Model for Massively Parallel Computation Considering both Communication and IO Cost

Ma¹,

Gao²,

Li³

et al. 2022

Preprint

View full text Add to dashboard Cite

In the research area of parallel computation, the communication cost has been extensively studied, while the IO cost has been neglected. For big data computation, the assumption that the data fits in main memory no longer holds, and external memory must be used. Therefore, it is necessary to bring the IO cost into the parallel computation model. In this paper, we propose the first parallel computation model which takes IO cost as well as non-uniform communication cost into consideration. Based on the new model, we raise several new problems which aim to minimize the IO and communication cost on the new model. We prove the hardness of these new problems, then design and analyze the approximate algorithms for solving them.

show abstract

Section: Declaration Of New Research Problemsmentioning

confidence: 99%

Section: Declaration Of New Research Problemsmentioning

confidence: 99%