Allocating Carbon Costs to Computing Payloads across Heterogeneous Infrastructures

As UKRI moves towards a NetZero Digital Research Infrastructure [1, 2] an understanding of how carbon costs of computing infrastructures can be allocated to individual scientific payloads will be required. The IRIS community forms a multi-site heterogeneous infrastructure so is a good testing ground to develop carbon allocation models with wide applicability. Carbon footprints of data centres were measured in the IRISCAST Project [3, 4]. Here we describe and test the models of the IRIS Carbon Mapping Project [5] which allocates carbon costs of compute and storage to individual users and payloads. It is shown that the simple storage and payload models can be implemented and that with improved monitoring enhanced models are also practical.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-10-07
DOI
https://doi.org/10.1051/epjconf/202533701202/pdf
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Allocating Carbon Costs to Computing Payloads across Heterogeneous Infrastructures

R.A. Owen, D. Toroz, D. Z. Li, D. Traynor et al.
Springer Link (Chiba Institute of Technology)
Distributed and Parallel Computing Systems
article

Allocating Carbon Costs to Computing Payloads across Heterogeneous Infrastructures

R.A. Owen, D. Toroz, D. Z. Li, D. Traynor, J. Hays
article en

Abstract

As UKRI moves towards a NetZero Digital Research Infrastructure [1, 2] an understanding of how carbon costs of computing infrastructures can be allocated to individual scientific payloads will be required. The IRIS community forms a multi-site heterogeneous infrastructure so is a good testing ground to develop carbon allocation models with wide applicability. Carbon footprints of data centres were measured in the IRISCAST Project [3, 4]. Here we describe and test the models of the IRIS Carbon Mapping Project [5] which allocates carbon costs of compute and storage to individual users and payloads. It is shown that the simple storage and payload models can be implemented and that with improved monitoring enhanced models are also practical.

Springer Link (Chiba Institute of Technology)
Industry, innovation and infrastructure
Openalex Percentile: Top 27%
Distributed and Parallel Computing Systems
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