Analysis of Cost-Effective Ethernet Architecture for AI Data Centers in the Context of Uzbekistan

Atajonov, Furqat, Polvonov, Dostonbek, Aliyev, Oybek, Saparabayev, To'lqin, Bazarboyev, Nurbek

Al-Farg'oniy avlodlari · 2026-yil

Annotatsiya

Infrastructure for training artificial intelligence (AI) models requires high bandwidth and minimal latency. In developing countries, particularly Uzbekistan, the high cost of traditional InfiniBand networks poses a significant barrier to AI development. This paper proposes a cost-effective, lossless RoCE v2-based Ethernet architecture as an alternative to InfiniBand. Economic and technical analyses demonstrate that a properly configured Leaf-Spine Ethernet topology significantly reduces capital expenditures (CAPEX) while providing the necessary performance.

Maqola ma’lumotlari
MualliflarAtajonov, Furqat, Polvonov, Dostonbek, Aliyev, Oybek, Saparabayev, To'lqin, Bazarboyev, Nurbek
JurnalAl-Farg'oniy avlodlari
Nashr sanasi2026-05-17
Son2
Betlar170-175
TilRus

Kalit so‘zlar

AI model training, GPU clusters, InfiniBand, RoCE v2, Ethernet architecture, Leaf-Spine topology, Lossless networking, Capital expenditures (CAPEX), Minimal latency, Обучение моделей ИИ, GPU кластеры, InfiniBand, RoCE v2, Архитектура Ethernet, Топология Leaf-Spine, Сеть без потерь, Капитальные затраты (CAPEX), Минимальная задержка, AI modellarini o‘qitish, GPU klasterlari, InfiniBand, RoCE v2, Ethernet arxitekturasi, Leaf-Spine topologiyasi, lossless tarmoq, kapital xarajatlar (CAPEX), minimal kechikish

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