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"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)
"Efficient and accurate selection of optimal MPI collective algorithms using analytical performance modelling",
School of Computer Science, Dublin, University College Dublin, pp. 130, 06/2021.
Download: thesis.pdf (2.21 MB)
"Novel Data-Partitioning Algorithms for Performance and Energy Optimization of Data-Parallel Applications on Modern Heterogeneous HPC Platforms",
School of Computer Science, Dublin, University College Dublin, pp. 264, 03/2019.
Download: thesis-hamid.pdf (5.9 MB)
"Optimization of Multithreaded Data-parallel Applications on Modern Multicore CPUs For Performance and Energy Using Application-level Decision Variables",
School of Computer Science, Dublin, University College Dublin, pp. 181, 09/2019.
Download: PhD_Thesis_Semyon_Khokhriakov.pdf (8.7 MB); thesis-summary.pdf (621.98 KB)
"The 27th International Heterogeneity in Computing Workshop and the 16th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms",
Concurrency and Computation: Practice and Experience, vol. 32, issue 15: Wiley, pp. 3, 03/2020.
Download: cpe.5736.pdf (169.99 KB)
"Acceleration of Bi-Objective Optimization of Data-Parallel Applications for Performance and Energy on Heterogeneous Hybrid Platforms",
IEEE Access, vol. 11: IEEE, pp. 27226-27245, 03/2023.
Download: Access-2023-acceleration.pdf (1.28 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)
"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 Comparative Study of Methods for Measurement of Energy of Computing",
Energies, vol. 12, issue 11: MDPI, pp. 42, 06/2019.
"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)
"Design of self-adaptable data parallel applications on multicore clusters automatically optimized for performance and energy through load distribution",
Concurrency and Computation: Practice and Experience, vol. 31, issue 4: Wiley, 02/2019.
Download: ccpe2018ravi.pdf (1.67 MB)
"Efficient and Accurate Selection of Optimal Collective Communication Algorithms Using Analytical Performance Modeling",
IEEE Access, vol. 9: IEEE, pp. 109355 - 109373, 07/2021.
Download: Efficient_and_Accurate_Selection_of_Optimal_Collective_Communication_Algorithms_Using_Analytical_Performance_Modeling.pdf (6.95 MB)
"Efficient exact algorithms for continuous bi-objective performance-energy optimization of applications with linear energy and monotonically increasing performance profiles on heterogeneous high performance computing platforms",
Concurrency and Computation: Practice and Experience: Wiley, pp. 1--19, 09/2022.
Download: Concurrency and Computation - 2022 - Khaleghzadeh - Efficient exact algorithms for continuous bi‐objective.pdf (1.58 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)
"Energy-Efficient Parallel Computing: Challenges to Scaling",
Information, vol. 14, issue 4, pp. 1--29, 04/2023.
Download: information-14-00248.pdf (1.53 MB)
"A Hierarchical Data-Partitioning Algorithm for Performance Optimization of Data-Parallel Applications on Heterogeneous Multi-Accelerator NUMA Nodes",
IEEE Access, vol. 8: IEEE, pp. 7861 - 7876, 01/2020.
Download: 08933138.pdf (3.4 MB)
"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)
"Model-based selection of optimal MPI broadcast algorithms for multi-core clusters",
Journal of Parallel and Distributed Computing, vol. 165: Elsevier, pp. 1-16, 07/2022.
Download: 1-s2.0-S0743731522000697-main.pdf (988.38 KB)
"Multicore processor computing is not energy proportional: An opportunity for bi-objective optimization for energy and performance",
Applied Energy, vol. 268, pp. 18, 06/2020.
Download: paper_r2.pdf (1.38 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)
"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)
"Parallel Data Partitioning Algorithms for Optimization of Data-Parallel Applications on Modern Extreme-Scale Multicore Platforms for Performance and Energy",
IEEE Access, vol. 6: IEEE, pp. 69075-69106, 11/2018.
Download: IEEEAccess2018PDPA.pdf (3.04 MB)
"Performance Optimization of Multithreaded 2D Fast Fourier Transform on Multicore Processors Using Load Imbalancing Parallel Computing Method",
IEEE Access, vol. 6: IEEE, pp. 64202-64224, 10/2018.
Download: ACCESS2878271.pdf (2.78 MB)
"A Survey of Communication Performance Models for High-Performance Computing",
ACM Computing Surveys, vol. 51, issue 6: ACM, 01/2019.
"A tool to assess the communication cost of parallel kernels on heterogeneous platforms",
The Journal of Supercomputing, vol. 76: Springer, pp. 4629–4644, 06/2020.
