A Practical Two-Stage Framework for GPU Resource and Power Prediction in Heterogeneous HPC Systems
Efficient utilization of GPU resources and power has become critical with the growing demand for GPUs in high-performance computing (HPC). In this paper, we analyze GPU utilization and GPU memory utilization, as well as the power consumption of the Vienna ab initio Simulation Package (VASP), using the Slurm workload manager historical logs and GPU performance metrics collected by NVIDIA's Data Center GPU Manager (DCGM). VASP is a widely used materials science application on Perlmutter at NERSC, an HPE Cray EX system based on NVIDIA A100 GPUs. Using our insights from the resource utilization analysis of VASP applications, we propose a resource prediction framework to predict the average GP...
| Authors | Beste Oztop, Dhruva Kulkarni, Zhengji Zhao et al. |
|---|---|
| Primary category | cs.DC |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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