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"A Novel Statistical Learning-Based Methodology for Measuring the Goodness of Energy Profiles of Applications Executing on Multicore Computing Platforms",
Energies, vol. 13, issue 15: MDPI, pp. 22, 08/2020.
Download: energies-13-03944.pdf (4.08 MB); supplemental.pdf (188.52 KB)
"A Comparative Study of Methods for Measurement of Energy of Computing",
Energies, vol. 12, issue 11: MDPI, pp. 42, 06/2019.
"Accurate Energy Modelling of Hybrid Parallel Applications on Modern Heterogeneous Computing Platforms using System-Level Measurements",
IEEE Access, vol. 8, pp. 93793 - 93829, 06/2020.
Download: 09094309.pdf (2.89 MB)
"Accurate Component-level Energy Modelling of Parallel Applications on Modern Heterogeneous Hybrid Computing Platforms using System-level Measurements",
School of Computer Science, Dublin, University College Dublin, pp. 198, 12/2020.
Download: thesis-fahad.pdf (3.49 MB)
"Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Dynamic Energy Through Workload Distribution",
17th Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar 2019), Gottingen, Germany, Lecture Notes in Computer Science, vol. 11997, Springer, 08/2019, 2020.
Download: Khaleghzadeh2020_Chapter_OptimizationOfData-ParallelApp.pdf (692.31 KB)
"Bi-Objective Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Performance and Energy Through Workload Distribution",
IEEE Transactions on Parallel and Distributed Systems, vol. 32, issue 3: IEEE, pp. 543-560, 03/2021.
Download: tpds-2021-32-3-09207974.pdf (1.58 MB)
"A novel data partitioning algorithm for dynamic energy optimization on heterogeneous high-performance computing platforms",
Concurrency and Computation: Practice and Experience, vol. 33, issue 21: Wiley, pp. e5928, 07/2020.
Download: CCPE-2020-dynamic-energy.pdf (1.34 MB)
"How Pre-multicore Methods and Algorithms Perform in Multicore Era",
High Performance Computing. ISC High Performance 2018. Lecture Notes in Computer Science, vol 11203, Frankfurt, Springer Nature, pp. 527-539, 24-26 June, 2018, 2019.
Download: nesus-isc-paper.pdf (574.34 KB)
"Improving the accuracy of energy predictive models for multicore CPUs by combining utilization and performance events model variables",
Journal of Parallel and Distributed Computing, vol. 151: Elsevier, pp. 38-51, 05/2021.
Download: jpdc-2021-151.pdf (1.4 MB)
"Energy Predictive Models of Computing: Theory, Practical Implications and Experimental Analysis on Multicore Processors",
IEEE Access, vol. 9: IEEE, pp. 63149 - 63172, 04/2021.
Download: IEEE_Access_2021_Energy_theory.pdf (2.11 MB)
"A Comparative Study of Techniques for Energy Predictive Modeling Using Performance Monitoring Counters on Modern Multicore CPUs",
IEEE Access, vol. 8: IEEE, pp. 143306 - 143332, 08/2020.
Download: IEEE-Access-09154439.pdf (2.37 MB)
"Additivity: A Selection Criterion for Performance Events for Reliable Energy Predictive Modeling",
Supercomputing Frontiers and Innovations, vol. 4, issue 4, pp. 50-65, 12/2017.
Abstract
Download: 153-992-1-PB.pdf (666.73 KB)
"Improving the Accuracy of Energy Predictive Models for Multicore CPUs Using Additivity of Performance Monitoring Counters",
15th International Conference on Parallel Computing Technologies (PaCT-2019), Almaty, Kazakhstan, Lecture Notes in Computer Science 11657, Springer, pp. 51-66, 08/2019.
Download: PaCT2019.pdf (370.4 KB)
