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Nuriyev, E., "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)
Malik, T., and A. Lastovetsky, "Optimal Matrix Partitioning for Data Parallel Computing on Hybrid Heterogeneous Platforms", 19th International Symposium on Parallel and Distributed Computing (ISPDC), Warsaw, Poland, IEEE, 5-8 July, 2020.  Download: ispdc2020.pdf (367.16 KB)
Lastovetsky, A., M. Fahad, H. Khaleghzadeh, S. Khokhriakov, R. Reddy, A. Shahid, L. Szustak, and R. Wyrzykowski, "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)
Patton, S., H. Khaleghzadeh, R. Reddy, and A. Lastovetsky, "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)
Shahid, A., M. Fahad, R. Reddy, and A. Lastovetsky, "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)