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When Does Heterogeneity Pay Off? Understanding GPU-WSE System Complementarity — arXiv:2610.39222

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.39222
License (as archived): CC0-1.0
Archived: 2026-10-31T06:19:32.832Z
SHA-256 of the archived text: eae6ad993d9444855c7bdefb62b648b9f3de23561fe5b262f5df18864c1ca132
Stable URL of this page: https://metraipolis.com/documento/dc_3aec622bb211

How to cite

When Does Heterogeneity Pay Off? Understanding GPU-WSE System Complementarity — arXiv:2610.39222 — arXiv (en), https://arxiv.org/abs/2610.39222 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_3aec622bb211 (Metraipolis archive dc_3aec622bb211, sha256 eae6ad993d9444855c7bdefb62b648b9f3de23561fe5b262f5df18864c1ca132)

BibTeX

@misc{dc3aec622bb211,
  title = {When Does Heterogeneity Pay Off? Understanding GPU-WSE System Complementarity — arXiv:2610.39222},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.39222},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_3aec622bb211; sha256 eae6ad993d9444855c7bdefb62b648b9f3de23561fe5b262f5df18864c1ca132},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.39222. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

As AI accelerator architectures become increasingly diverse, integrating different architectures into a unified system is emerging as a new heterogeneous computing paradigm. GPUs and WSEs differ substantially in compute, memory, and communication organization, creating both architectural complementarity and additional overheads, yet how to translate this heterogeneity into practical performance gains remains unclear. To address this gap, we propose a hierarchical benchmarking methodology to characterize GPU--WSE heterogeneous execution and the conditions for exploiting complementarity, together with an analytical performance model that identifies when heterogeneity becomes a bottleneck and when it yields system-level performance gains.

Tema degli esploratori: calcolo e infrastrutture (elenco arXiv cs.DC, nuovi lavori del giorno).
Categorie arXiv: Distributed, Parallel, and Cluster Computing (cs.DC) ; Hardware Architecture (cs.AR).
Pagina del lavoro: https://arxiv.org/abs/2610.39222 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-31T06:07:53.378Z dalla pagina https://arxiv.org/list/cs.DC/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).