English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper we study multi-installment divisible load processing in heterogeneous distributed systems. Divisible loads are computations which can be divided into parts of arbitrary sizes, and these parts can be processed independently in parallel. In order to reduce the waiting time during the parallel computation initialization phase, load is sent to the processors in multiple small installments. In a heterogeneous system the sizes of the installments should be adjusted to the communication, and computation capabilities of the processors. We propose two algorithms that gear the load chunk sizes to different communication and computation speeds. The first one is an optimization branch and bound algorithm. The second algorithm is based on genetic search. The running times of both methods and the quality of the genetic algorithm solutions are compared. Then, we use these algorithms to analyze features of the scheduling problem solutions.

On Optimum Multi-installment Divisible Load Processing in Heterogeneous Distributed Systems