Postdoctoral researcher in the Efficient Computing and Storage Group
Johannes Gutenberg – Universität Mainz
55128 Mainz, Germany
Phone: +49 6131 3925128
Fax: +49 6131 3926407
Reza Salkhordeh is a postdoctoral researcher at the Johannes Gutenberg-Universität Mainz since Nov. 2018. He received his B.Sc. from Ferdowsi University of Mashhad in 2011, M.Sc and Ph.D. from Sharif University of Technology (SUT) in 2013 and 2018, respectively. During his Ph.D., he mentored four M.Sc. and six B.Sc theses. His Ph.D. thesis is titled "Optimization of Operating System to Employ Emerging Memory Technologies". He was a member of PPoPP'18 artifact evaluation committee and a reviewer for Elsevier Microprocessors and Microsystems (2016) and Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018). He was a member of Iran’s National Elites Foundation. His research interests are storage systems design, solid-state drives, non-volatile memories, operating systems design, and caching architectures.
R. Salkhordeh, O. Mutlu, and H. Asadi, "An Analytical Model for Performance and Lifetime Estimation of Hybrid DRAM-NVM Main Memories," IEEE Transactions on Computers (TC), In Press, 2019.
Reza Salkhordeh, Mostada Hadizadeh, Hossein Asadi. "An Efficient Hybrid I/O Caching Scheme using Heterogeneous SSDs," IEEE Transactions on Parallel and Distributed Systems (TPDS), 2018.
Saba Ahmadian, Reza Salkhordeh, Hossein Asadi. "LBICA: A Load Balancer for I/O Cache Architectures," Design, Automation Test in Europe Conference Exhibition (DATE), 2018.
Reza Salkhordeh, Shahriar Ebrahimi, Hossein Asadi. "ReCA: an Efficient Reconfigurable Cache Architecture for Storage Systems with Online Workload Characterization," IEEE Transactions on Parallel and Distributed Systems (TPDS), 2018.
Reza Salkhordeh, Hossein Asadi. "An Operating System level data migration scheme in hybrid DRAM-NVM memory architecture," Design, Automation Test in Europe Conference Exhibition (DATE), 2016.
Reza Salkhordeh, Hossein Asadi, Shahriar Ebrahimi. "Operating system level data tiering using online workload characterization," The Journal of Supercomputing, 2015.