Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer. - Boram Yoon; Chia-Cheng Chang; Garrett T. Kenyon; Nga T. T. Nguyen; Ermal Rrapaj (CoRR, 2021)

Comparing Power Signatures of HPC Workloads: Machine Learning vs Simulation. - Anish Govind; Sridutt Bhalachandra; Zhengji Zhao; Ermal Rrapaj; Brian Austin; Hai Ah Nam (SC Workshops, 2023)

Power Analysis of NERSC Production Workloads. - Zhengji Zhao; Ermal Rrapaj; Sridutt Bhalachandra; Brian Austin; Hai Ah Nam; Nicholas J. Wright (SC Workshops, 2023)

Less is More! A slim architecture for optimal language translation. - Luca Herranz-Celotti; Ermal Rrapaj (CoRR, 2023)

Comprehensive Performance Modeling and System Design Insights for Foundation Models. - Shashank Subramanian; Ermal Rrapaj; Peter Harrington; Smeet Chheda; Steven Farrell; Brian Austin; Samuel Williams 001; Nicholas J. Wright; Wahid Bhimji (SC Workshops, 2024)

Understanding VASP Power Profiles on NVIDIA A100 GPUs. - Zhengji Zhao; Brian Austin; Ermal Rrapaj; Nicholas J. Wright (SC Workshops, 2024)

Evaluation of the Classical Hardware Requirements for Large-Scale Quantum Computations. - Daan Camps; Ermal Rrapaj; Katherine Klymko; Brian Austin; Nicholas J. Wright (ISC, 2024)

Power Consumption Trends in Supercomputers: A Study of NERSC's Cori and Perlmutter Machines. - Ermal Rrapaj; Sridutt Bhalachandra; Zhengji Zhao; Brian Austin; Hai Ah Nam; Nicholas J. Wright (ISC, 2024)

Ternary Tree Fermion-to-Qubit Mapping with Hamiltonian Aware Optimization. - Yuhao Liu; Kevin Yao; Jonathan Hong; Julien Froustey; Yunong Shi; Ermal Rrapaj; Costin Iancu; Gushu Li (CoRR, 2024)

Classical optimization with imaginary time block encoding on quantum computers: The MaxCut problem. - Dawei Zhong; Akhil Francis; Ermal Rrapaj (CoRR, 2024)

HATT: Hamiltonian Adaptive Ternary Tree for Optimizing Fermion-to-Qubit Mapping. - Yuhao Liu; Kevin Yao; Jonathan Hong; Julien Froustey; Ermal Rrapaj; Costin Iancu; Gushu Li; Yunong Shi (HPCA, 2025)