Muhammad Fahad
"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)
"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)
"Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Dynamic Energy Through Workload Distribution",
Euro-Par 2019 Workshops, Lecture Notes in Computer Science, vol. 11997, Gottingen, Germany, Springer, 08/2019, 2020.
Download: Khaleghzadeh2020_Chapter_OptimizationOfData-ParallelApp.pdf (692.31 KB)
"A novel data partitioning algorithm for dynamic energy optimization on heterogeneous high-performance computing platforms",
Concurrency and Computation: Practice and Experience: Wiley, pp. 18, 07/2020.
Download: CCPE-2020-dynamic-energy.pdf (1.34 MB)
"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)
"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 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)
"A Comparative Study of Methods for Measurement of Energy of Computing",
Energies, vol. 12, issue 11: MDPI, pp. 42, 06/2019.
"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)
