1 citations · 1 across the 5 of their papers we have counts for
5 papers
When More Cores Hurts: The Vector Database Scaling Paradox in HPC
Seth Ockerman, Song Young Oh, Amal Gueroudji +12
Vector databases have been designed and optimized for cloud environments; however, emerging scientific AI workloads (e.g., molecular search, meteorological trajectory detection, an…
Offline Reinforcement-Learning-Based Power Control for Application-Agnostic Energy Efficiency
Akhilesh Raj, Swann Perarnau, Aniruddha Gokhale +1
Energy efficiency has become an integral aspect of modern computing infrastructure design, impacting the performance, cost, scalability, and durability of production systems. The i…
THAPI: Tracing Heterogeneous APIs
Solomon Bekele, Aurelio Vivas, Thomas Applencourt +5
As we reach exascale, production High Performance Computing (HPC) systems are increasing in complexity. These systems now comprise multiple heterogeneous computing components (CPUs…
A Reinforcement Learning Approach for Performance-aware Reduction in Power Consumption of Data Center Compute Nodes
Akhilesh Raj, Swann Perarnau, Aniruddha Gokhale
As Exascale computing becomes a reality, the energy needs of compute nodes in cloud data centers will continue to grow. A common approach to reducing this energy demand is to limit…
Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach
Eric Rutten, Sophie Cerf, Raphaël Bleuse +2
Production high-performance computing systems continue to grow in complexity and size. As applications struggle to make use of increasingly heterogeneous compute nodes, maintaining…