Iterating Pointers: Enabling Static Analysis for Loop-based Pointers
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866910859591155712 |
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| author | Lepori, Andrea Calotoiu, Alexandru Hoefler, Torsten |
| author_facet | Lepori, Andrea Calotoiu, Alexandru Hoefler, Torsten |
| contents | Pointers are an integral part of C and other programming languages. They enable substantial flexibility from the programmer's standpoint, allowing the user fine, unmediated control over data access patterns. However, accesses done through pointers are often hard to track, and challenging to understand for optimizers, compilers, and sometimes, even for the developers themselves because of the direct memory access they provide. We alleviate this problem by exposing additional information to analyzers and compilers. By separating the concept of a pointer into a data container and an offset, we can optimize C programs beyond what other state-of-the-art approaches are capable of, in some cases even enabling auto-parallelization. Using this process, we are able to successfully analyze and optimize code from OpenSSL, the Mantevo benchmark suite, and the Lempel-Ziv-Oberhumer compression algorithm. We provide the only automatic approach able to find all parallelization opportunities in the HPCCG benchmark from the Mantevo suite the developers identified and even outperform the reference implementation by up to 18%, as well as speed up the PBKDF2 algorithm implementation from OpenSSL by up to 11x. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_03359 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Iterating Pointers: Enabling Static Analysis for Loop-based Pointers Lepori, Andrea Calotoiu, Alexandru Hoefler, Torsten Programming Languages Distributed, Parallel, and Cluster Computing Performance Pointers are an integral part of C and other programming languages. They enable substantial flexibility from the programmer's standpoint, allowing the user fine, unmediated control over data access patterns. However, accesses done through pointers are often hard to track, and challenging to understand for optimizers, compilers, and sometimes, even for the developers themselves because of the direct memory access they provide. We alleviate this problem by exposing additional information to analyzers and compilers. By separating the concept of a pointer into a data container and an offset, we can optimize C programs beyond what other state-of-the-art approaches are capable of, in some cases even enabling auto-parallelization. Using this process, we are able to successfully analyze and optimize code from OpenSSL, the Mantevo benchmark suite, and the Lempel-Ziv-Oberhumer compression algorithm. We provide the only automatic approach able to find all parallelization opportunities in the HPCCG benchmark from the Mantevo suite the developers identified and even outperform the reference implementation by up to 18%, as well as speed up the PBKDF2 algorithm implementation from OpenSSL by up to 11x. |
| title | Iterating Pointers: Enabling Static Analysis for Loop-based Pointers |
| topic | Programming Languages Distributed, Parallel, and Cluster Computing Performance |
| url | https://arxiv.org/abs/2503.03359 |