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"On Energy Nonproportionality of CPUs and GPUs",
31st Heterogeneity in Computing Workshop (HCW 2022), Lyon, France, IEEE, pp. 34-44, 30/05/2022.
Download: On_Energy_Nonproportionality_of_CPUs_and_GPUs.pdf (1.03 MB)
"Accurate and Reliable Energy Measurement and Modelling of Data Transfer Between CPU and GPU in Parallel Applications on Heterogeneous Hybrid Platforms",
IEEE Transactions on Computers, vol. 74, issue 3, pp. 1011--1024, 03/2025.
Download: Accurate_and_Reliable_Energy_Measurement_and_Modelling_of_Data_Transfer_Between_CPU_and_GPU_in_Parallel_Applications_on_Heterogeneous_Hybrid_Platforms.pdf (853.36 KB); supplemental_r2.pdf (2.05 MB)
"Concurrent and Orthogonal Software Power Meters for Accurate Runtime Energy Profiling of Parallel Hybrid Programs on Heterogeneous Hybrid Servers",
IEEE Transactions on Parallel and Distributed Systems, vol. 37, issue 2: IEEE, pp. 322-339, 02/2026.
Download: Concurrent_and_Orthogonal_Software_Power_Meters_for_Accurate_Runtime_Energy_Profiling_of_Parallel_Hybrid_Programs_on_Heterogeneous_Hybrid_Servers.pdf (3.44 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)
"A New Model-Based Approach to Performance Comparison of MPI Collective Algorithms",
16th International Conference on Parallel Computing Technologies (PaCT 2021), Kaliningrad, Russia, Lecture Notes in Computer Science 12942, Springer, pp. 11-25, 09/2021.
Download: Nuriyev-Lastovetsky2021_Chapter_ANewModel-BasedApproachToPerfo.pdf (623.78 KB)
"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)
"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)
"SUARA: A scalable universal allreduce communication algorithm for acceleration of parallel deep learning applications",
Journal of Parallel and Distributed Computing, vol. 183, pp. 15, 01/2024.
Download: jpdc-suara.pdf (2.46 MB)
"Energy aware ultrascale systems",
Ultrascale computing systems: IET, 03/2019.
Download: chap5.pdf (3.2 MB)
"SummaGen: Parallel Matrix-Matrix Multiplication Based on Non-rectangular Partitions for Heterogeneous HPC Platforms",
28th Heterogeneity in Computing Workshop (HCW 2019), Rio de Janeiro, Brazil, IEEE, 20/05/2019.
Download: hcw2019.pdf (673.25 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)
"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)
"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.
"A Survey of Communication Performance Models for High-Performance Computing",
ACM Computing Surveys, vol. 51, issue 6: ACM, 01/2019.
"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)
"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)
"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)
