Finally, we will study algorithms for distributed data analytics over edge devices. The course content will come from research papers, articles, and software documentation. We will work together to develop …

Papers for this special issue were selected to address data mining methods and processes from both an algorithmic and systems perspective in parallel and distributed environments.

As in all distributed systems, time synchronization is an important component of a sensor network. Time synchronization in a computer network aims at providing a common time scale for local clocks of …

The pre-requisite may be replaced by suitable background and coursework in network programming and distributed systems. Undergraduates who are interested in taking this class should contact the …

Low-precision Second-order-type Distributed Methods for Training and Fine-tuning Foundation Models - We are considering developing low-communication training methods for large scall LLMs, targetting …

The architectural design and evaluation of BDA applications entail new challenges to integrate emerging machine learning algorithms with cutting-edge practices whilst ensuring performance levels even in …

Included in this paradigm are hardware- or software-distributed shared-memory systems. These systems distribute the physical memory among the nodes but provide a shared global address space …

Sections 4, 5, and 6 describe the components of the distributed system. Section 7 outlines the algorithms used for collecting our results efficiently and accurately.

design and develop functional, concurrent (including distributed and mobile), and logic (including constraint satisfaction) programs. compare multiple programming paradigms and know when to …

It is composed of theories from three main domains—distributed systems, mathematics, and network theory. Within each domain, there are theories from various related sub-domains.