9,771 research outputs found
A fast analysis for thread-local garbage collection with dynamic class loading
Long-running, heavily multi-threaded, Java server applications make stringent demands of garbage collector (GC) performance. Synchronisation of all application threads before garbage collection is a significant bottleneck for JVMs that use native threads. We present a new static analysis and a novel GC framework designed to address this issue by allowing independent collection of thread-local heaps. In contrast to previous work, our solution safely classifies objects even in the presence of dynamic class loading, requires neither write-barriers that may do unbounded work, nor synchronisation, nor locks during thread-local collections; our analysis is sufficiently fast to permit its integration into a high-performance, production-quality virtual machine
Adaptive Lock-Free Data Structures in Haskell: A General Method for Concurrent Implementation Swapping
A key part of implementing high-level languages is providing built-in and
default data structures. Yet selecting good defaults is hard. A mutable data
structure's workload is not known in advance, and it may shift over its
lifetime - e.g., between read-heavy and write-heavy, or from heavy contention
by multiple threads to single-threaded or low-frequency use. One idea is to
switch implementations adaptively, but it is nontrivial to switch the
implementation of a concurrent data structure at runtime. Performing the
transition requires a concurrent snapshot of data structure contents, which
normally demands special engineering in the data structure's design. However,
in this paper we identify and formalize an relevant property of lock-free
algorithms. Namely, lock-freedom is sufficient to guarantee that freezing
memory locations in an arbitrary order will result in a valid snapshot. Several
functional languages have data structures that freeze and thaw, transitioning
between mutable and immutable, such as Haskell vectors and Clojure transients,
but these enable only single-threaded writers. We generalize this approach to
augment an arbitrary lock-free data structure with the ability to gradually
freeze and optionally transition to a new representation. This augmentation
doesn't require changing the algorithm or code for the data structure, only
replacing its datatype for mutable references with a freezable variant. In this
paper, we present an algorithm for lifting plain to adaptive data and prove
that the resulting hybrid data structure is itself lock-free, linearizable, and
simulates the original. We also perform an empirical case study in the context
of heating up and cooling down concurrent maps.Comment: To be published in ACM SIGPLAN Haskell Symposium 201
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