Comparative Analysis of Compiler Efficiency: Energy Consumption Metrics in High-Performance Computing Domains
Abstract
This study presents a comprehensive comparative analysis of compiler efficiency, with a focus on energy consumption metrics across diverse domains of high-performance computing. By rigorously evaluating the performance of GCC, Clang, and ICC, the research aims to elucidate which compilers excel in specific areas, thereby providing valuable insights for the strategic selection of these tools based on the unique requirements of various computational tasks. The findings reveal that, among the total energy consumed during the computations, GCC accounted for 33.23%, Clang for 36.01%, and ICC for 30.76%. Notably, ICC demonstrated superior energy efficiency, being 7.43% more efficient than GCC, while Clang was 8.35% less efficient. These results underscore the critical importance of selecting the appropriate compiler to optimize energy efficiency in high-performance computing environments.
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Amiri, H. and Shahbahrami, A. (2020). Simd programming using intel vector extensions. Journal of Parallel and Distributed Computing, 135:83–100.
Che, S., Sheaffer, J. W., Boyer, M., Szafaryn, L. G., Wang, L., and Skadron, K. (2010). A characterization of the rodinia benchmark suite with comparison to contemporary cmp workloads. In IEEE International Symposium on Workload Characterization (IISWC’10), pages 1–11.
Daniel and Page (2009). Compilers, pages 451–493. Springer London, London.
Embree, P. M., Kimble, B., and Bartram, J. F. (1991). C language algorithms for digital signal processing.
Gawrych, B. and Czarnul, P. (2023). Performance assessment of openmp constructs and benchmarks using modern compilers and multi-core cpus. In 2023 18th Conference on Computer Science and Intelligence Systems (FedCSIS), pages 973–978. IEEE.
Gough, B. J. and Stallman, R. (2004). An Introduction to GCC. Network Theory Limited.
Hatcher, P. J., Quinn, M. J., Lapadula, A. J., Anderson, R. J., and Jones, R. R. (1991). Dataparallel c: A simd programming language for multicomputers. In The Sixth Distributed Memory Computing Conference, pages 91–92. IEEE CS.
Hollman, D. S., Lelbach, B. A., Edwards, H. C., Hoemmen, M., Sunderland, D., and Trott, C. R. (2019). mdspan in c++: A case study in the integration of performance portable features into international language standards. In International Workshop on Performance, Portability and Productivity in HPC, pages 60–70. IEEE.
Hussain, S. M., Wahid, A., Shah, M. A., Akhunzada, A., Khan, F., Amin, N. u., Arshad, S., and Ali, I. (2019). Seven pillars to achieve energy efficiency in high-performance computing data centers. Recent Trends and Advances in Wireless and IoT-enabled Networks, pages 93–105.
Inria, University of Lille (2024). Power api. Copyright © 2024 Inria, University of Lille. Made with Material for MkDocs.
Kiessling, A. (2009). An introduction to parallel programming with openmp. In The University of Edinburgh, A Pedagogical Seminar (accessed 24 September 2020), URL: [link], volume 76.
Lattner, C. and Adve, V. (2004). Llvm: a compilation framework for lifelong program analysis & transformation. In International Symposium on Code Generation and Optimization, 2004. CGO 2004., pages 75–86.
Machado, R. S., Almeida, R. B., Jardim, A. D., Pernas, A. M., Yamin, A. C., and Cavalheiro, G. G. H. (2017). Comparing performance of c compilers optimizations on different multicore architectures. In 2017 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW), pages 25–30.
Mishra, A., Malik, A. M., and Chapman, B. (2020). Extending the llvm/clang framework for openmp metadirective support. In 2020 IEEE/ACM 6th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC) and Workshop on Hierarchical Parallelism for Exascale Computing (HiPar), pages 33–44.
Tiwari, A., Laurenzano, M. A., Carrington, L., and Snavely, A. (2012). Modeling power and energy usage of hpc kernels. In IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum, pages 990–998.
Williams, J. and Curtis, L. (2008). Green: The new computing coat of arms? IT Professional Magazine, 10(1):12.
Published
2024-10-23
How to Cite
DAMASCENO, Erick; QUEIROZ, Fellipe; SIQUEIRA, Luan; RODRIGUES, Thiago; AMARIS, Marcos.
Comparative Analysis of Compiler Efficiency: Energy Consumption Metrics in High-Performance Computing Domains. In: BRAZILIAN SYMPOSIUM ON HIGH PERFORMANCE COMPUTING SYSTEMS (SSCAD), 25. , 2024, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 252-263.
DOI: https://doi.org/10.5753/sscad.2024.244771.
