Many emerging large-scale data science applications require searching large graphs
distributed across multiple memories and processors. This paper presents a distributed …

To tackle the increasingly larger training data and models, researchers and engineers resort
to multiple servers in a data center for distributed machine learning (DML). On one hand …

In this paper, the (bi) panconnectivity and edge-(bi) pancyclicity of n-dimensional torus
networks are investigated. An n-dimensional torus T= T (k 1, k 2,…, kn) with diameter m 0=∑ …

The trend from single processor to parallel computer architectures has increased the
importance of parallel computing. To support parallel computing it is important to map …

We introduce Cartesian Collective Communication as sparse, collective communication
defined on processes (processors) organized into d-dimensional tori or meshes. Processes …

All-to-all communication is one of the most dense collective communication patterns and
occurs in many important applications in parallel and distributed computing. In this paper …

All-to-all personalized exchange is one of the most dense collective communication patterns
and it occurs in many important parallel computing/networking applications. In this paper, we …

There is a growing demand for network support for group applications, in which messages
from one or more sender (s) are delivered to a large number of receivers. Here, we propose …

In this article, we address the problem of finding an optimal schedule for all-to-all
personalized message communication among the processors in a multiprocessor system …

All-to-all personalized exchange (ATAPE) is an inspired process to speedup the parallel and
distributed computing. Recently, ATAPE algorithms were successfully applied on multistage …