Bringing GenAI awareness to workload management
Kavya G, Priyanka Naik, et al.
Middleware 2025
Exponential growth of AI workloads is driving the need for high performance chip packages that cannot be thermally managed by energy- and water-intensive chilled air-cooling solutions implemented in Data Centers today. A two-phase heat transfer system, that utilizes the liquid to vapor phase conversion of a working fluid for transferring the heat to the ambient environment, can provide energy-efficient thermal management of high-performance AI systems while eliminating water consumption and maintaining system reliability in any geographical location. This short tutorial will describe the exemplar computationally manageable high-fidelity components- as well as system-level models that are necessary for the assessment and development of such a cooling system.
Kavya G, Priyanka Naik, et al.
Middleware 2025
Pritish Parida
iTHERM 2023
Corey Liam Lammie, Hadjer Benmeziane, et al.
SOCC 2026
Ka-Ho Chow, Umesh Deshpande, et al.
SIGMOD 2023