The single largest factor in determining the CO2 footprint of a compute resource is the CO2 intensity of the electricity used to power it. The carbon intensity ranges from 20 to 800gCO2/kWh, depending on the energy mix of the region. Due to the interconnectivity of the European electricity grid, it is not sufficient to look only at the regional electricity carbon intensity, but also at that of...
KIT operates not only the GridKa WLCG Tier-1 Center but also extensive HPC facilities, large-scale storage services, and the fundamental KIT IT infrastructure.
Across these domains, we are actively working on various initiatives to optimize energy consumption and maximize waste heat reuse. We'll present our multifaceted approach which encompasses the following key areas:
- Component-Level...
In this talk, we will describe the studies undertaken at the University of Manchester to estimate and improve the energy efficiency of computing hardware and software used by students and researchers.
The goal of these studies is to build an understanding of the environmental impact of paticle physics research focusing on two fronts:
1) the carbon cost of the hardware uses for high power...
The Tier-2 computing center at MIT has been established in 2006 and has been a prominent contributor to the CMS computing ever since. Over the years hardware has aged and we are faced with a major re-design which affects our principal design ideas that have driven our purchases over the years. In this context we have done a more holistic evaluation of the cost which for the first time includes...
Sustainability is becoming an ever-increasing part in the planning, designing and operation of large-scale infrastructures. Due to the international nature of the collaborators, these large-scale infrastructures end up being both joint-ventures building large machines, and the pooling of smaller resources to provide services for these machines. Research Facility 2.0 is an EU-funded project...
CERN has been tracking its energy consumption and carbon footprint at the level of the organisation and department for several years. We are compliant with the ISO 50001 energy management certification. However, this gives only a rough overview of the impact. CERN IT has been working on improving the monitoring of efficiency and power consumption as well as understanding the total impact of...
This study presents preliminary analyses of natural job drainage and power reduction patterns in the PIC Tier-1 data center, which uses HTCondor for workload scheduling. By examining historical HTCondor logs, we simulate natural job drainage behaviors, in order to understand natural job drainage patterns: when jobs naturally conclude without external intervention. These findings provide...
The Scientific Data and Computing Center (SDCC) at Brookhaven National Laboratory provides data services (storage, transfer and management), computing resources and collaborative tools to our worldwide scientific communities. Growing needs from our various programs coupled with data centre floor space and power constraints led us to the construction and occupancy of a new power-efficient data...
GreenDIGIT (https://greendigit-project.eu/) is a TECH-01-01 Horizon Europe project that started in March 2024 to pursue environmental sustainability within digital services and service ecosystems that research infrastructures (RIs) rely on. GreenDIGIT brings together institutes from 4 digital RIs: EGI, SLICES, EBRAINS, and SoBigData to address the pressing need for sustainable practices in...
LOCO2024, the 1st International Workshop on Low Carbon Computing was held in Glasgow on 3 Dec. It was an initiative of the Scottish Informatics and Computer Science Alliance that aimed to bring together researchers and practitioners from all over the world working on low carbon and sustainable computing.
The workshop provided a forum for presenting and discussion of new ideas, ongoing work...
Collaborative approaches to raise awareness about climate change or ICT impact in the environment have become very popular in the past years. Examples like Climate Fresk or Digital Collage, where collective intelligence is used to understand and identify mitigation strategies, have found a tremendous success among general public and are happening worldwide. Getting inspiration from these...
The rapid evolution of computing technologies, including AI and high-performance computing (HPC), has significantly impacted scientific advancements, particularly in high-energy physics (HEP). However, this progress comes at an environmental cost, as the energy and carbon footprints of computing tasks continue to grow. This presentation explores the energy consumption and carbon footprint of...
Einstein Telescope (ET) is the proposed third generation ground-based gravitational wave observatory to be built in Europe in the mid-2030s. Sustainability is a key concern for Research Infrastructures and, thanks to its significant computing needs, ET has been charged with incorporating Sustainability criteria in its Computing Model already at the design phase. Although new, dedicated ET...
The ATLAS experiment relies on the PanDA workload management system to handle its analysis and production tasks across the Worldwide LHC Computing Grid (WLCG). In response to a request from the ATLAS Sustainability Forum, we've introduced a new feature: simple, informative estimates of the carbon emissions generated by each job.
To achieve this, we calculate CO₂ emissions by retrieving...
The goal of this thesis is to develop an optimized task allocation algorithm for the Workload Management System (WMS) in DiracX, aimed at reducing energy consumption and maximizing the utilization of renewable energy sources. To achieve this, a combination of advanced techniques—including numerical optimization, clustering, and artificial intelligence (e.g., reinforcement learning)—will be...
The HEP Benchmark Suite provides a comprehensive framework for evaluating the performance and power consumption of computing resources within the Worldwide LHC Computing Grid (WLCG), supporting its sustainability objectives. This presentation will outline the toolkit's capabilities and present examples where the suite has successfully identified opportunities to improve both energy efficiency...
During the HL-HLC era the WLCG, according to the current estimates, will be requested to provide millions of CPU years of computation annually. The largest single computing loads are particle tracking, hard scatter event generation and calorimetry simulation. Improving the computational performance of these loads is a very active research area that includes creation of GPU based codes and...
The rapid advancement of artificial intelligence (AI) technologies is driving transformative changes across various sectors, including High Energy Physics (HEP). While the energy consumption associated with AI systems poses a challenge to sustainability, the integration of AI within HEP offers significant benefits in terms of efficiency and modernization of the HEP computing model. This talk...
The CMS FlashSim simulation framework is an end-to-end ML based simulation that can speed up the time for production of analysis samples of several orders of magnitude with a limited loss of accuracy. Detailed event simulation at the LHC is taking a large fraction of computing budget. As the CMS experiment is adopting a common analysis level format, the NANOAOD, for a larger number of...
For HL-LHC, recent studies have shown that around 20% of the total computing resources will be used for Monte-Carlo simulations. Without efficiency improvements the computing needs of the experiments will not be met by the available resources. Motivating research avenues in the realm of GPU acceleration.
In this talk, we will present the current status of the GPU and vectorised version of the...
Improvements in algorithmic efficiency are, in principle, the ‘free-est’ sources of energy-efficiency gains, as reducing CPU time at a constant power clearly reduces total energy. However, it is not clear a priori that the same applies to porting parts of a code to special purpose accelerators such as GPUs.
We investigated this case for the Celeritas project’s GPU offloading for Geant4’s EM...
In order to achieve the higher performance year on year required by the 2030s for future LHC upgrades at a sustainable carbon cost to the environment, it is essential to start with accurate measurements of the state of play. Whilst there have been a number of studies of the carbon cost of compute for WLCG workloads published, rather less has been said on the topic of storage, both nearline and...
The current capacity of the CERN's data storage tape infrastructure is around 1 EB.
The talk will first explain the 3 building blocks of this technology (automation, tape drives and media), their lifecycle and different resource requirements.
By using data compiled by IBM and Spectra Logic we will then outline the environmental and sustainability impacts of CERN's configuration in terms...
In the push for sustainable solutions in High Energy Physics (HEP) computing, our WLCG Tier2 site at ScotGrid Glasgow has adopted ARM-based servers, achieving full production integration with increasingly positive results. Today we run significant workloads on ARM, including ATLAS production tasks, and our findings indicate a measurable reduction in energy consumption compared to traditional...
A model for computing the total life cycle emissions for compute nodes, based on providing a certain level of scientific computing over long time.
This takes real-world data from data centers, electricity generation, and vendor server information and simulates different replacement scenarios (from replacing it as soon as possible to keeping it a long time) to be able to optimize for minimal...
Data center sustainability, a phenomenon that has grown in focus due to the continuing evolution of Artificial intelligence (AI)/High Performance Computing (HPC) and High Throughput Computing (HTC) systems; furthermore, the rampant increase in carbon emissions resulted due to unprecedented rise in Thermal Design Power (TDP) of the computer chips. With the exponential increase of demand towards...
