TY  - JOUR
AU  - Villarrubia Elvira, Jorge
AU  - Costero Valero, Luis María
AU  - Igual Peña, Francisco Daniel
AU  - Olcoz Herrero, Katzalin
PY  - 2026
DO  - 10.1016/j.future.2025.108145
SN  - 0167-739X
UR  - https://hdl.handle.net/20.500.14352/126143
T2  - Future Generation Computer Systems
AB  - Recent advances in dynamic GPU partitioning, such as NVIDIA's Multi-Instance GPU (MIG) technology, have enhanced resource utilization by enabling task co-execution without contention. However, existing MIG schedulers remain limited to static or...
LA  - eng
M2  - 108145-1
PB  - Elsevier
KW  - Multi-Instance GPU (MIG)
KW  - Moldable resource management
KW  - Deep reinforcement learning
KW  - Task scheduling
TI  - Solving the task scheduling and GPU reconfiguration problem on MIG devices via deep reinforcement learning
TY  - journal article
VL  - 176
ER  -