Distributed computing has become a common approach for large-scale computation tasks
due to benefits such as high reliability, scalability, computation speed, and cost …

It is known that deeper and wider neural networks can achieve better accuracy. But it is
difficult to continue the trend to increase model size due to limited GPU memory. One …

A new model for task scheduling that dramatically improves the efficiency of parallel systems
Task scheduling for parallel systems can become a quagmire of heuristics, models, and …

Nature inspired algorithm plays a very vibrant role in solving the different optimization
problems these days. The fundamental attitude of naturalistic approaches is to boost the …

Most algorithms developed for scheduling applications on global Grids focus on a single
Quality of Service (QoS) parameter such as execution time, cost or total data transmission …

Distributed computing has become a common approach for large-scale computation of tasks
due to benefits such as high reliability, scalability, computation speed, and costeffectiveness …

Task scheduling is one of the key factors in a distributed system. That is, how proper
allocating the tasks to the processor of each computer in order to achieve better …

The multiprocessor task scheduling problem has received considerable attention over the
last three decades. In this context, a wide range of studies focuses on the design of …

In this paper we tackle the task assignment problem (TSAP) in heterogeneous computer
systems. The TSAP consists of assigning a given distributed computer program formed by a …

This paper presents and evaluates a new method for process scheduling in distributed
systems. Scheduling in distributed operating systems has a significant role in overall system …