Compiler Optimization for Heterogeneous Computing

Authors

  • Christian Murphy Author

Keywords:

compilers, heterogeneous computing, accelerators, optimization, portability

Abstract

This review examines compiler optimization for heterogeneous computing. The organizing question is how compiler transformations should balance portability, performance, energy, and numerical fidelity across devices. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to reporting device-specific tuning as a portable compiler improvement. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in scientific, data-intensive, and machine-learning workloads.

References

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Published

2026-08-08

Issue

Vol. 1 (2026): Archive

Section

Review

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Copyright (c) 2026 Computing Architectures and Data Systems

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This work is licensed under a Creative Commons Attribution 4.0 International License.