How Pre-multicore Methods and Algorithms Perform in Multicore Era. - Alexey L. Lastovetsky; Muhammad Fahad 002; Hamidreza Khaleghzadeh; Semyon Khokhriakov; Ravi Reddy; Arsalan Shahid; Lukasz Szustak; Roman Wyrzykowski (ISC Workshops, 2018)

libhclooc: Software Library Facilitating Out-of-core Implementations of Accelerator Kernels on Hybrid Computing Platforms. - Daniel Hanlon; Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (CoRR, 2018)

Hierarchical multicore thread mapping via estimation of remote communication. - Hamidreza Khaleghzadeh; Hossein Deldari; Ravi Reddy; Alexey L. Lastovetsky (J. Supercomput., 2018)

Out-of-core implementation for accelerator kernels on heterogeneous clouds. - Hamidreza Khaleghzadeh; Ziming Zhong; Ravi Reddy; Alexey L. Lastovetsky (J. Supercomput., 2018)

A Novel Data-Partitioning Algorithm for Performance Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms. - Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Trans. Parallel Distributed Syst., 2018)

Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Dynamic Energy Through Workload Distribution. - Hamidreza Khaleghzadeh; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (Euro-Par Workshops, 2019)

SummaGen: Parallel Matrix-Matrix Multiplication Based on Non-rectangular Partitions for Heterogeneous HPC Platforms. - Stephen Patton; Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IPDPS Workshops, 2019)

Bi-objective Optimisation of Data-parallel Applications on Heterogeneous Platforms for Performance and Energy via Workload Distribution. - Hamidreza Khaleghzadeh; Muhammad Fahad 002; Arsalan Shahid; Ravi Reddy Manumachu; Alexey L. Lastovetsky (CoRR, 2019)

A Hierarchical Data-Partitioning Algorithm for Performance Optimization of Data-Parallel Applications on Heterogeneous Multi-Accelerator NUMA Nodes. - Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Access, 2020)

A novel data partitioning algorithm for dynamic energy optimization on heterogeneous high-performance computing platforms. - Hamidreza Khaleghzadeh; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (Concurr. Comput. Pract. Exp., 2020)

The gem5 Simulator: Version 20.0+. - Jason Lowe-Power; Abdul Mutaal Ahmad; Ayaz Akram; Mohammad Alian; Rico Amslinger; Matteo Andreozzi; Adrià Armejach; Nils Asmussen; Srikant Bharadwaj; Gabe Black; Gedare Bloom; Bobby R. Bruce; et al. (CoRR, 2020)

Loan Default Prediction Using Spark Machine Learning Algorithms. - Aiman Muhammad Uwais; Hamidreza Khaleghzadeh (AICS, 2021)

A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Performance and Linear Energy Profiles on Heterogeneous HPC Platforms. - Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (Euro-Par Workshops, 2021)

FOCT: Fast Overlapping Clustering for Textual Data. - Atefeh Khazaei; Hamidreza Khaleghzadeh; Mohammad Ghasemzadeh 001 (IEEE Access, 2021)

Bi-Objective Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Performance and Energy Through Workload Distribution. - Hamidreza Khaleghzadeh; Muhammad Fahad 002; Arsalan Shahid; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Trans. Parallel Distributed Syst., 2021)

Novel bi-objective optimization algorithms minimizing the max and sum of vectors of functions. - Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (CoRR, 2022)

Acceleration of Bi-Objective Optimization of Data-Parallel Applications for Performance and Energy on Heterogeneous Hybrid Platforms. - Ravi Reddy Manumachu; Hamidreza Khaleghzadeh; Alexey L. Lastovetsky (IEEE Access, 2023)

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. - Hamidreza Khaleghzadeh; Ravi Reddy Manumachu; Alexey L. Lastovetsky (Concurr. Comput. Pract. Exp., 2023)