Published October 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Leveraging Partially Context-Sensitive Profiles for Enhanced AOT Compilation: A Review

Authors/Creators

  • 1. Department of Software Engineering, Redoak Technologies, San Jose, CA, United States of America (USA).

Contributors

Contact person:

Researcher:

  • 1. Department of Software Engineering, Redoak Technologies, San Jose, CA, United States of America (USA).

Description

Abstract: In the realm of compiler optimization, just-in-time (JIT) compilation dynamically adjusts code execution based on runtime profiling, contrasting with the static approach of ahead-of-time (AOT) compilation. While JIT benefits from real-time profiling data, AOT lacks this advantage, necessitating innovative strategies to enhance performance without runtime feedback. This review article explores the integration of partially context-sensitive profiles into AOT compilation, offering insights into optimizing statically compiled programs through advanced profiling techniques. Also, it explores the utilization of partially context-sensitive profiles in ahead-of-time (AOT) compilation to enhance program performance. It delves into the challenges of AOT optimization without runtime profiling, contrasting it with the dynamic optimization capabilities of just-in-time (JIT) compilation. The proposed algorithm strategically leverages partial profiles to identify and optimize hot code segments, presenting a promising avenue for improving AOT compilation efficiency. Through empirical evaluation of diverse benchmarks, the article validates the technique's effectiveness, underscoring its significance in advancing compiler optimization strategies for statically compiled programs.

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Additional details

Identifiers

DOI
10.35940/ijeat.A4538.14011024
EISSN
2249-8958

Dates

Accepted
2024-10-15
Manuscript received on 31 July 2024 | Revised Manuscript received on 14 August 2024 | Manuscript Accepted on 15 October 2024 | Manuscript published on 30 October 2024.

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