ProFess: A Probabilistic Hybrid Main Memory Management Framework for High Performance and Fairness
Paper in proceedings, 2018

Non-Volatile Memory (NVM) technologies enable cost-effective hybrid main memories with two partitions: M1 (DRAM) and slower but larger M2 (NVM). This paper considers a flat migrating organization of hybrid memories. A challenging and open issue of managing such memories is to allocate M1 among co-running programs such that high fairness is achieved at the same time as high performance. This paper introduces ProFess: a Probabilistic hybrid main memory management Framework for high performance and fairness. It comprises: i) a Relative-Slowdown Monitor (RSM) that enables fair management by indicating which program suffers the most from competition for M1; and ii) a probabilistic Migration-Decision Mechanism (MDM) that unlocks high performance by realizing cost-benefit analysis that is individual for each pair of data blocks considered for migration. Within ProFess, RSM guides MDM towards high fairness. We show that for the multiprogrammed workloads evaluated, ProFess improves fairness by 15% (avg.; up to 29%), compared to the state-of-the-art, while outperforming it by 12% (avg.; up to 29%).


Flat migrating organization

Hybrid main memory




Dmitry Knyaginin

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Vasileios Papaefstathiou

Foundation for Research and Technology Hellas (FORTH)

Per Stenström

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Proceedings - International Symposium on High-Performance Computer Architecture

15300897 (ISSN)

Vol. 2018-February 143-155

24th IEEE International Symposium on High Performance Computer Architecture, HPCA 2018
Vienna, Austria,

Subject Categories

Computer Engineering

Computer Science

Computer Systems

Areas of Advance

Information and Communication Technology



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