Cells: A cell-inspired efficient software framework for ai-enabled application on resources-constrained mobile system

Ching Han Chen, Mu Che Wu

Research output: Contribution to journalArticlepeer-review

Abstract

Today’s mobile processors generally have multiple cores and sufficient hardware resources to support AI-enabled software operation. However, very few AI applications make full use of the computing performance of mobile multiprocessors. This is because the typical software development is sequential, and the degree of parallelism of the program is very low. In the increasingly complex AI-driven and software development projects with natural human–computer interaction, this will undoubtedly cause a waste of mobile computing resources that are originally limited. This paper proposes an intelligent system software framework, CellS, to improve smart software development on multicore mobile processor systems. This software framework mimics the cell system. In this framework, each cell can autonomously aware changes in the environment (input) and reac-tion (output) and may change the behavior of other cells. Smart software can be regarded as a large number of cells interacting with each other. Software developed based on the CellS framework has a high degree of scalability and flexibility and can more fully use multicore computing resources to achieve higher computing efficiency.

Original languageEnglish
Article number568
Pages (from-to)1-29
Number of pages29
JournalElectronics (Switzerland)
Volume10
Issue number5
DOIs
StatePublished - 1 Mar 2021

Keywords

  • Accelerators
  • Parallel programming models and languages
  • Programming for resilience
  • Reconfigura-ble and embedded computing

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