Design and Challenges of Multicore Processor Architectures

Multicore processors, which integrate multiple processing units onto one chip, have become an increasingly important solution to meet rising computing needs. In this paper we present an in-depth examination of multicore architecture design principles with regards to interconnects, cache coherence, memory management and power consumption issues as well as heat dissipation challenges and complexity of parallel programming issues as major obstacles facing multicore designs today. By looking both theoretical advances as well as real world implementations we also discuss their future and propose potential solutions to overcome current obstacles to multicore technologies today.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-01
DOI
https://doi.org/10.5281/zenodo.13845096
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Design and Challenges of Multicore Processor Architectures

Zenodo (CERN European Organization for Nuclear Research)
Parallel Computing and Optimization Techniques
article

Design and Challenges of Multicore Processor Architectures

article en

Abstract

Multicore processors, which integrate multiple processing units onto one chip, have become an increasingly important solution to meet rising computing needs. In this paper we present an in-depth examination of multicore architecture design principles with regards to interconnects, cache coherence, memory management and power consumption issues as well as heat dissipation challenges and complexity of parallel programming issues as major obstacles facing multicore designs today. By looking both theoretical advances as well as real world implementations we also discuss their future and propose potential solutions to overcome current obstacles to multicore technologies today.

Zenodo (CERN European Organization for Nuclear Research)
Electronics Design (Estonia) (EE)
Affordable and clean energy
Openalex Percentile: Top 54%
Parallel Computing and Optimization Techniques
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