book chapter · Institution of Engineering and Technology eBooks · 2019

Modelling many-core architectures

Cited by 0Abstract and details only

Abstract

Architectural modelling has two primary objectives: (1) navigating the design space exploration, i.e. guiding the architects to arrival at better design choices, and (2) facilitating dynamic management, i.e. providing the functional relationships between workloads'characteristics and architectural configurations to enable appropriate runtime hardware/software adaptations. In the past years, many-core architectures, as a typical computing fabric evolving from the monolithic single-/multicore architectures, have been shown to be scalable to uphold the staggering the Moore's Law. The many-core architectures enable two orthogonal approaches, scale-up and scale-out, to utilize the growing budget of transistors. Understanding the rationale behind these approaches is critical to make more efficient use of the powerful computing fabric.

Cite this paper

APA 7

Yan, G., Li, J., & Li, X. (2019). Modelling many-core architectures. Institution of Engineering and Technology eBooks, 297–322. https://doi.org/10.1049/pbpc022e_ch12

MLA 9

Yan, Guihai, et al. “Modelling many-core architectures.” Institution of Engineering and Technology eBooks, 2019, pp. 297–322, https://doi.org/10.1049/pbpc022e_ch12.

Chicago

Yan, Guihai, Jiajun Li, and Xiaowei Li. 2019. “Modelling many-core architectures.” Institution of Engineering and Technology eBooks: 297–322. https://doi.org/10.1049/pbpc022e_ch12.

Harvard

Yan, G., Li, J. and Li, X. (2019) ‘Modelling many-core architectures’, Institution of Engineering and Technology eBooks, pp. 297–322. Available at: https://doi.org/10.1049/pbpc022e_ch12.

BibTeX

@incollection{yan2019modelling,
  title = {{Modelling many-core architectures}},
  author = {Yan, Guihai and Li, Jiajun and Li, Xiaowei},
  booktitle = {Institution of Engineering and Technology eBooks},
  pages = {297--322},
  year = {2019},
  doi = {10.1049/pbpc022e_ch12}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.