Remote Build Execution and Cross-Compilation: Advancing Real-Time AI Appliance Development

This article examines the transformative impact of Remote Build Execution (RBE) and cross-compilation technologies in the development and deployment of real-time AI appliances. The article explores how these technologies address the growing challenges of software deployment across diverse computing environments, particularly in edge computing scenarios. By analyzing the implementation of distributed build systems and platform-specific optimizations, the study demonstrates significant improvements in development efficiency, resource utilization, and runtime performance. The article presents comprehensive findings on build system architecture, integration strategies, and performance optimization techniques, providing valuable insights for organizations developing AI applications. Through examination of real-world case studies and empirical analysis, this article establishes the effectiveness of combining RBE and cross-compilation approaches in bridging the gap between development environments and resource-constrained deployment targets.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-05-14
DOI
https://doi.org/10.32996/jcsts.2025.7.4.46
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

Remote Build Execution and Cross-Compilation: Advancing Real-Time AI Appliance Development

Bhanu Kiran Kaithe
Journal of Computer Science and Technology Studies
IoT and Edge/Fog Computing
article

Remote Build Execution and Cross-Compilation: Advancing Real-Time AI Appliance Development

Bhanu Kiran Kaithe
article en

Abstract

This article examines the transformative impact of Remote Build Execution (RBE) and cross-compilation technologies in the development and deployment of real-time AI appliances. The article explores how these technologies address the growing challenges of software deployment across diverse computing environments, particularly in edge computing scenarios. By analyzing the implementation of distributed build systems and platform-specific optimizations, the study demonstrates significant improvements in development efficiency, resource utilization, and runtime performance. The article presents comprehensive findings on build system architecture, integration strategies, and performance optimization techniques, providing valuable insights for organizations developing AI applications. Through examination of real-world case studies and empirical analysis, this article establishes the effectiveness of combining RBE and cross-compilation approaches in bridging the gap between development environments and resource-constrained deployment targets.

Journal of Computer Science and Technology StudiesVol. 7(4)
Film Independent (US)
Openalex Percentile: Top 89%
IoT and Edge/Fog Computing
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