Lune

HPCA2025顶会

CORDOBA: Carbon-Efficient Optimization Framework for Computing Systems

Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu

2025年份
16被引次数
2顶会引用

摘要

The world’s push toward an environmentally sustainable society is highly dependent on the semiconductor industry. Despite existing carbon modeling efforts to quantify carbon footprint of computing systems, optimizing carbon footprint in large design spaces-while also considering trade-offs in power, performance, and area-is especially challenging. To address this need, we present CORDOBA, a carbon-aware optimization framework that optimizes carbon efficiency. We quantify carbon efficiency using the total Carbon Delay Product metric (tCDP): the product of total carbon and application execution time. We justify why tCDP is an effective metric for quantifying carbon efficiency. We use CORDOBA to explore the large design space for carbonefficient specialized hardware, and identify distinct carbonefficient optimal designs across operational use (eliminating up to 98%\mathbf{9 8 \%} of the design space) despite uncertainty in carbon footprint parameters. We quantify opportunities to improve tCDP for real system case studies: (a) optimizing hardware provisioning from 8 to 4 cores in real system CPUs improves tCDP by 1.25×1.25 \times; and (b) leveraging advanced three-dimensional (3D) integration techniques (3D stacking of separately-fabricated logic and memory chips) improves tCDP by 6.9×6.9 \times versus conventional systems.

问问这篇 Paper

问问你的智能体。

Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。

可以从这些问题问起

智能体调用

Lunesearch_papers

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper2

问问它们各自怎么用它

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖