Blogs (2) >>
ISMM 2017
Sun 18 Jun 2017 Barcelona, Spain
co-located with PLDI 2017
Sun 18 Jun 2017 09:30 - 10:00 at Aula Master - Session 1: Garbage Collection Chair(s): Hannes Payer

Big Data applications suffer from unpredictable and unacceptably high pause times due to Garbage Collection (GC). This is the case in latency-sensitive applications such as on-line credit-card fraud detection, graph-based computing for analysis on social networks, etc. Such pauses compromise latency requirements of the whole application stack and result from applications’ aggressive buffering/caching of data, exposing an ill-suited GC design, which assumes that most objects will die young and does not consider that applications hold large amounts of middle-lived data in memory.

To avoid such pauses, we propose NG2C, a new GC algorithm that combines pretenuring with user-defined dynamic generations. By being able to allocate objects into different generations, NG2C is able to group objects with similar lifetime profiles in the same generation. By allocating objects with similar lifetime profiles close to each other, i.e. in the same generation, we avoid object promotion (copying between generations) and heap fragmentation (which leads to heap compactions) both responsible for most of the duration of HotSpot GC pause times.

NG2C is implemented for the OpenJDK 8 HotSpot Java Virtual Machine, as an extension of the Garbage First GC. We evaluate NG2C using Cassandra, Lucene, and GraphChi with three different GCs: Garbage First (G1), Concurrent Mark Sweep (CMS), and NG2C. Results show that NG2C decreases the worst observable GC pause time by up to 94.8% for Cassandra, 85.0% for Lucene and 96.45% for GraphChi, when compared to current collectors (G1 and CMS). In addition, NG2C has no negative impact on application throughput or memory usage.

Sun 18 Jun

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

09:30 - 10:30
Session 1: Garbage CollectionISMM 2017 at Aula Master
Chair(s): Hannes Payer Google
NG2C: Pretenuring Garbage Collection with Dynamic Generations for HotSpot Big Data Applications
ISMM 2017
Rodrigo Bruno INESC-ID / Instituto Superior Técnico, University of Lisbon, Luís Picciochi Oliveira Feedzai, A: Paulo Ferreira INESC-ID / Instituto Superior Técnico, University of Lisbon
Type-Assisted Automatic Garbage Collection for Lock-Free Data Structures
ISMM 2017