3 papers
cs.DC2026
Optimizing Teacher-Student Partitioning for Scalable Knowledge Distillation on HPC Systems
Adrian P. Dieguez, Victor Conchello Vendrell, Alex Batlle +3
Knowledge Distillation (KD) enables training smaller student models under the guidance of larger teacher models, and the widely adopted TRL library implements it. Yet, TRL treats b…
cs.DC2024
Cost-Effective Methodology for Complex Tuning Searches in HPC: Navigating Interdependencies and Dimensionality
Adrian Perez Dieguez, Min Choi, Mahmut Okyay +3
Tuning searches are pivotal in High-Performance Computing (HPC), addressing complex optimization challenges in computational applications. The complexity arises not only from finel…
cs.DC2023
Performance Tuning for GPU-Embedded Systems: Machine-Learning-based and Analytical Model-driven Tuning Methodologies
Adrian Perez Dieguez, Margarita Amor Lopez
GPU-embedded systems have gained popularity across various domains due to their efficient power consumption. However, in order to meet the demands of real-time or time-consuming ap…