Multi-core: Adding a New Dimension to Computing

TL;DR

This paper surveys the evolution, current state, and future trends of multi-core processors, emphasizing their role in enabling ubiquitous parallel processing across various computing devices.

Contribution

It provides a comprehensive overview of multi-core technology, software support for parallelism, and discusses future research directions in the field.

Findings

Multi-core processors are now prevalent in diverse devices.

Software tools for parallelism are evolving to support multi-core architectures.

Future research will focus on optimizing and expanding multi-core processing capabilities.

Abstract

Invention of Transistors in 1948 started a new era in technology, called Solid State Electronics. Since then, sustaining development and advancement in electronics and fabrication techniques has caused the devices to shrink in size and become smaller, paving the quest for increasing density and clock speed. That quest has suddenly come to a halt due to fundamental bounds applied by physical laws. But, demand for more and more computational power is still prevalent in the computing world. As a result, the microprocessor industry has started exploring the technology along a different dimension. Speed of a single work unit (CPU) is no longer the concern, rather increasing the number of independent processor cores packed in a single package has become the new concern. Such processors are commonly known as multi-core processors. Scaling the performance by using multiple cores has gained so much attention from the academia and the industry, that not only desktops, but also laptops, PDAs, cell phones and even embedded devices today contain these processors. In this paper, we explore state of the art technologies for multi-core processors and existing software tools to support parallelism. We also discuss present and future trend of research in this field. From our survey, we conclude that next few decades are going to be marked by the success of this "Ubiquitous parallel processing".