Comparative Analysis of GCC and LLVM for Performance Optimization on Aarch64

The emergence of ARM-based architectures in high-performance computing (HPC) has necessitated a closer examination of compiler behaviors and optimizations. This paper investigates the performance and optimization capabilities of GCC and LLVM compilers for Aarch64 processors on HPC workloads. We focus on ARM-based HPC processors used in systems like Grace Hopper and Fujitsu A64FX, emphasizing on their implementations of the Scalable Vector Extension (SVE) and other architectural features that enhance performance. Through comprehensive benchmarking, including vectorization analysis with the Test Suite for Vectorizing Compilers (TSVC), we evaluate the performance of the compilers based on execution times, applied optimizations, and code portability across these systems. By comparing recent versions of GCC (v14) and LLVM (v18) with their previous versions, we highlight performance improvements and identify optimization gaps. Our analysis of assembly code offers insights into vectorization, register allocation, and SIMD instruction generation, providing valuable recommendations for future compiler enhancements. This study aims to give insights for the development of more efficient compilers, ultimately advancing the performance of Aarch64-based HPC systems.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/hpec62836.2024.10938451
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.49

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article

Comparative Analysis of GCC and LLVM for Performance Optimization on Aarch64

P Haribabu, Prachi Pandey, Sathish Kumar, S D Sudarsan et al.
1 citations
Parallel Computing and Optimization Techniques
0.49
article

Comparative Analysis of GCC and LLVM for Performance Optimization on Aarch64

P Haribabu, Prachi Pandey, Sathish Kumar, S D Sudarsan, Mriganka Bezbaruah, Samruddhi Dhakulkar
article en
1 citations

Abstract

The emergence of ARM-based architectures in high-performance computing (HPC) has necessitated a closer examination of compiler behaviors and optimizations. This paper investigates the performance and optimization capabilities of GCC and LLVM compilers for Aarch64 processors on HPC workloads. We focus on ARM-based HPC processors used in systems like Grace Hopper and Fujitsu A64FX, emphasizing on their implementations of the Scalable Vector Extension (SVE) and other architectural features that enhance performance. Through comprehensive benchmarking, including vectorization analysis with the Test Suite for Vectorizing Compilers (TSVC), we evaluate the performance of the compilers based on execution times, applied optimizations, and code portability across these systems. By comparing recent versions of GCC (v14) and LLVM (v18) with their previous versions, we highlight performance improvements and identify optimization gaps. Our analysis of assembly code offers insights into vectorization, register allocation, and SIMD instruction generation, providing valuable recommendations for future compiler enhancements. This study aims to give insights for the development of more efficient compilers, ultimately advancing the performance of Aarch64-based HPC systems.

Centre for Development of Advanced Computing (IN)
University of Oregon
Openalex Percentile: Top 31%
Parallel Computing and Optimization Techniques
0.49
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Comparative Analysis of GCC and LLVM for Performance Optimization on Aarch64 — P Haribabu, Prachi Pandey, et al. · (2024) | TGRS Research Map | TGRS