Nascent persistent memory (PM) technologies promise the performance of DRAM with the durability of disk, but how best to integrate them into programming systems remains an open question. Recent work extends language memory models with a persistency model prescribing semantics for updates to PM. These semantics enable programmers to design data structures in PM that are accessed like memory and yet are recoverable upon crash or failure. Alas, we find the semantics and performance of existing approaches unsatisfying. Existing approaches require high-overhead mechanisms, are restricted to certain synchronization constructs, provide incomplete semantics, and/or may recover to state that cannot arise in fault-free execution.
We propose persistency semantics that guarantee failure atomicity of synchronization-free regions (SFRs) - program regions delimited by synchronization operations. Our approach provides clear semantics for the PM state recovery code may observe and extends C++11's "sequential consistency for data-race-free" guarantee to post-failure recovery code. We investigate two designs for failure-atomic SFRs that vary in performance and the degree to which commit of persistent state may lag execution. We demonstrate both approaches in LLVM v3.6.0 and compare to a state-of-the-art baseline to show performance improvement up to 87.5% (65.5% avg).
Wed 20 JunDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:15 | Emerging HardwarePLDI Research Papers at Grand Ballroom CD Chair(s): Ryan R. Newton Indiana University | ||
11:00 25mTalk | Persistency for Synchronization-Free Regions PLDI Research Papers Vaibhav Gogte University of Michigan, USA, Stephan Diestelhorst ARM Research, UK, William Wang Arm Research, UK, Satish Narayanasamy University of Michigan, Peter M. Chen University of Michigan, USA, Thomas F. Wenisch University of Michigan, USA Media Attached | ||
11:25 25mTalk | Write-Rationing Garbage Collection for Hybrid Memories PLDI Research Papers Shoaib Akram Ghent University, Jennifer B. Sartor Vrije Universiteit Brussel, Kathryn S McKinley Google, Lieven Eeckhout Ghent University, Belgium Media Attached | ||
11:50 25mTalk | Mapping Spiking Neural Networks onto a Manycore Neuromorphic Architecture PLDI Research Papers Chit-Kwan Lin Intel Labs, n.n., Andreas Wild Intel Labs, n.n., Tsung-Han Lin Intel Labs, n.n., Gautham N. Chinya Intel Labs, n.n., Mike Davies Intel Labs, n.n., Hong Wang Intel Labs, n.n. Media Attached |