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DTSTAMP:20260605T154542Z
LOCATION:Bldg. 6 - Room 102
DTSTART;TZID=Europe/Stockholm:20260629T133000
DTEND;TZID=Europe/Stockholm:20260629T153000
UID:submissions.pasc-conference.org_PASC26_sess106@linklings.com
SUMMARY:MS1D - 2nd Sustainable Computing for AI and Data-Intensive Infrast
 ructures
DESCRIPTION:Organizer(s): Denisa-Andreea Constantinescu (EPFL), Florina Ci
 orba (University of Basel), and Can Hankendi (Boston University)\n\nArtifi
 cial Intelligence (AI) has become a primary driver of compute demand and e
 nergy consumption, with workloads such as large language models and AI-pow
 ered computational science applications requiring sustained, infrastructur
 e-scale resources. At the same time, modern data centers operate under inc
 reasingly tight power, carbon, and power grid constraints, particularly as
  they integrate variable renewable energy sources. Together, these trends 
 highlight the growing tension between performance scalability, energy avai
 lability, and environmental impact. Addressing these challenges requires i
 ntegrated efforts from component-level optimization to co-designing comput
 ing infrastructures, workloads, and energy systems. This minisymposium exa
 mines how sustainability can be embedded by design across AI and data-inte
 nsive computing infrastructures. Topics include (1) datacenter-power grid 
 co-design to enable load flexibility under renewable integration, (2) infr
 astructure-level optimization of AI and AI-powered workloads for improved 
 energy efficiency, (3) hardware-software co-design approaches that explore
  accelerator design trade-offs for AI and scientific computing, and (4) me
 thods, metrics, and lifecycle assessment tools. The session also highlight
 s the economic and environmental tensions between cost-optimal and emissio
 ns-optimal system configurations. By bringing together researchers and pra
 ctitioners working on architectures, systems, and infrastructure design, t
 his session aims to foster a shared understanding of the design principles
  needed to support sustainable growth in AI and data-intensive computing.\
 n\nModelling the Environmental Footprint of Future AI and HPC Datacenters:
  Enabling Hardware-Software Codesign Including Life Cycle Assessment\n\nAr
 tificial intelligence (AI) has emerged as a pivotal force shaping the futu
 re of scientific discovery and technological innovation in day-to-day life
 . It has become a key enabler for future scientific research and developme
 nt of new applications. As data centers dedicated to these workloads exper
 ie...\n\n\nNitish Satya Murthy, Vincent Schellekens, and Timon Evenblij (I
 MEC)\n---------------------\nTowards Green AI: Reducing the Environmental 
 Footprint of LLM Workloads\n\nContemporary large-scale computing systems a
 re becoming increasingly heterogeneous, complex, and decentralized, driven
  by growing digitization demands. This transformation is most evident in t
 he rapid rise of Generative AI applications, which have fueled the expansi
 on of hyperscale data centers, now...\n\n\nShashikant Ilager (University o
 f Amsterdam) and Ivona Brandic (TU Wien)\n---------------------\nMiddlebox
 : Resolving the Datacenter-Grid tension and Decarbonizing Both\n\nDatacent
 er’s (DCs) constant power requirement is difficult to balance with variabl
 e solar and wind generation.  DC load flexibility is the key to solving th
 e problem, but it conflicts stable capacity requirements.\n\nWe propose ``
 power Middlebox'', a new system architecture, as a bridge. Middleb...\n\n\
 nAndrew Chien (Univ of Chicago, Argonne National Laboratory)\n------------
 ---------\nHow Design Choices Shape Sustainable Computing: A Hardware Acce
 lerator Perspective\n\nData centers are experiencing rapidly rising energy
  consumption and associated greenhouse-gas emissions. Today, GPUs are the 
 dominant accelerator in many data centers, yet they are not necessarily th
 e most efficient choice for every application domain because they remain r
 elatively general-purpose. ...\n\n\nRuben Rodriguez Alvarez and Denisa-And
 reea Constantinescu (EPFL)\n\nDomain: Engineering, Computational Methods a
 nd Applied Mathematics\n\nSession Chairs: Denisa-Andreea Constantinescu (E
 PFL) and Florina Ciorba (University of Basel)
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