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| Format: | Preprint |
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2026
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| Online-Zugang: | https://arxiv.org/abs/2605.29740 |
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| _version_ | 1866914613310783488 |
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| author | Morgado, José Sousa, Leonel Ilic, Aleksandar |
| author_facet | Morgado, José Sousa, Leonel Ilic, Aleksandar |
| contents | In recent years, HPC systems and CPU architectures as their central components, have become increasingly complex, making application development and optimization quite challenging. In this respect, intuitive performance models like the Cache-aware Roofline Model (CARM) offer effective guidance by providing insights into bottlenecks that limit the application's ability to reach the system's maximum performance. To fully exploit the benefits of CARM optimization guidance for application development, automatic tools for cross-architecture model construction and in-depth application characterization are absolutely essential. Given a plethora of existing CPU architectures, the current landscape of CARM-enabled tools covers either vendor-specific (Intel Advisor), not sufficiently developed (ARM) or simply non-existing (AMD, RISC-V) tools. This is a particular gap that this work intends to close by bringing automatic CARM support to all major CPU architectures and ISAs, i.e., x86 (Intel, AMD), ARM, and RISC-V, by developing assembly microbenchmarks specifically tailored to cover a full performance spectrum of modern CPUs (from scalar to all supported vector ISA extensions) for both computational units and all memory hierarchy levels. Additionally, this work integrates application analysis within the CARM framework using performance counters and dynamic binary instrumentation. Experimental results show that the CARM roofs constructed with the proposed automated framework provide less than a 1% deviation across various tested architectural maximums. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_29740 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | CARM Tool: Cache-Aware Roofline Model Automatic Benchmarking and Application Analysis Morgado, José Sousa, Leonel Ilic, Aleksandar Distributed, Parallel, and Cluster Computing In recent years, HPC systems and CPU architectures as their central components, have become increasingly complex, making application development and optimization quite challenging. In this respect, intuitive performance models like the Cache-aware Roofline Model (CARM) offer effective guidance by providing insights into bottlenecks that limit the application's ability to reach the system's maximum performance. To fully exploit the benefits of CARM optimization guidance for application development, automatic tools for cross-architecture model construction and in-depth application characterization are absolutely essential. Given a plethora of existing CPU architectures, the current landscape of CARM-enabled tools covers either vendor-specific (Intel Advisor), not sufficiently developed (ARM) or simply non-existing (AMD, RISC-V) tools. This is a particular gap that this work intends to close by bringing automatic CARM support to all major CPU architectures and ISAs, i.e., x86 (Intel, AMD), ARM, and RISC-V, by developing assembly microbenchmarks specifically tailored to cover a full performance spectrum of modern CPUs (from scalar to all supported vector ISA extensions) for both computational units and all memory hierarchy levels. Additionally, this work integrates application analysis within the CARM framework using performance counters and dynamic binary instrumentation. Experimental results show that the CARM roofs constructed with the proposed automated framework provide less than a 1% deviation across various tested architectural maximums. |
| title | CARM Tool: Cache-Aware Roofline Model Automatic Benchmarking and Application Analysis |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2605.29740 |