On-the-fly Garbage Collectors (GCs) are the state-of-the-art concurrent GC algorithms today. Everything is done concurrently, but phases are separated by blocking handshakes. Hence, progress relies on the scheduler to let application threads (mutators) run into GC checkpoints to reply to the handshakes. For a non-blocking GC, these blocking handshakes need to be addressed. Therefore, we propose a new non-blocking handshake to replace previous blocking handshakes. It guarantees schedulingindependent operation level progress without blocking. It is scheduling independent but requires some other OS support. It allows bounded waiting for threads that are currently running on a processor, regardless of threads that are not running on a processor. We discuss this non-blocking handshake in two GC algorithms for stack scanning and copying objects. They pave way for a future completely non-blocking GC by solving hard open theory problems when OS support is permitted. The GC algorithms were integrated to the G1 GC of OpenJDK for Java. GC pause times were reduced to 12.5% compared to the original G1 on average in DaCapo. For a memory intense benchmark, latencies were reduced from 174 ms to 0.67 ms for the 99.99% percentile. The improved latency comes at a cost of 15% lower throughput.

On-the-fly Garbage Collectors (GCs) are the state-of-the-art concurrent GC algorithms today. Everything is done concurrently, but phases are separated by blocking handshakes. Hence, progress relies on the scheduler to let application threads (mutators) run into GC checkpoints to reply to the handshakes. For a non-blocking GC, these blocking handshakes need to be addressed. Therefore, we propose a new non-blocking handshake to replace previous blocking handshakes. It guarantees schedulingindependent operation level progress without blocking. It is scheduling independent but requires some other OS support. It allows bounded waiting for threads that are currently running on a processor, regardless of threads that are not running on a processor. We discuss this non-blocking handshake in two GC algorithms for stack scanning and copying objects. They pave way for a future completely non-blocking GC by solving hard open theory problems when OS support is permitted. The GC algorithms were integrated to the G1 GC of OpenJDK for Java. GC pause times were reduced to 12.5% compared to the original G1 on average in DaCapo. For a memory intense benchmark, latencies were reduced from 174 ms to 0.67 ms for the 99.99% percentile. The improved latency comes at a cost of 15% lower throughput.

Compaction of memory in long running systems has always been important. The latency of compaction increases in today’s systems with high memory demands and large heaps. To deal with this problem, we present a lock-free protocol allowing for copying concurrent with the application running, which reduces the latencies of compaction radically. It pro- vides theoretical progress guarantees for copying and appli- cation threads without making it practically infeasible, with performance overheads of 20% on average. The algorithm paves way for a future lock-free Garbage Collector. 

Sometimes components are conservatively implemented as thread-safe, while during the actual execution they are only accessed from one thread. In these scenarios, overly conservative assumptions lead to suboptimal performance.

The contribution of this paper is a component architecture that combines the benefits of different synchronization mechanisms to implement thread-safe concurrent components. Based on the thread contention monitored at runtime, context-aware composition and optimization select the appropriate mechanism. On changing contention, it revises this decision automatically and transforms the components accordingly. We implemented this architecture for concurrent queues, sets, and ordered sets. In all three cases, experimental evaluation shows close to optimal performance regardless of the actual contention.

As a consequence, programmers can focus on the semantics of their systems and, e.g., conservatively use thread-safe components to assure consistency of their data, while deferring implementation and optimization decisions to contention-context-aware composition at runtime.

The contribution of this study is a Field Pinning garbage collector (GC) without handshakes in the compaction phase. It is one step towards guaranteeing wait-free GC. It compacts memory concurrently and guarantees that fragmentation is bounded. Mutator heap accesses and computations are wait-free. The compaction algorithm does not need handshakes, but may use them for increased performance. The solution is evaluated experimentally in a prototype VM for Java. The GC progress is not wait-free, but impeded only by stack scanning and marking which was outside the scope of this study. The compaction algorithm does not impair global GC progress. 

Fine-tuning which data structure implementation to use for a given problem is sometimes tedious work since the optimum solution depends on the context, i.e., on the operation sequences, actual parameters as well as on the hardware available at run time. Sometimes a data structure with higher asymptotic time complexity performs better in certain contexts because of lower constants. The optimal solution may not even be possible to determine at compile time.We introduce transformation data structures that dynamically change their internal representation variant based on a possibly changing context. The most suitable variant is selected at run time rather than at compile time.We demonstrate the effect on performance with a transformation ArrayList data structure using an array variant and a linked hash bag variant as alternative internal representations. Using our transformation ArrayList, the standard DaCapo benchmark suite shows a performance gain of 5.19% in average.

Parallelization and other optimizations often depend on static dependence analysis. This approach requires methods to be independent regardless of the input data, which is not always the case.

Our contribution is a dynamic analysis "guessing" if methods are pure, i. e., if they do not change state. The analysis is piggybacking on a garbage collector, more specifically, a concurrent, replicating garbage collector. It guesses whether objects are immutable by looking at actual mutations observed by the garbage collector. The analysis is essentially for free. In fact, our concurrent garbage collector including analysis outperforms Boehm's stop-the-world collector (without any analysis), as we show in experiments. Moreover, false guesses can be rolled back efficiently.

The results can be used for just-in-time parallelization allowing an automatic parallelization of methods that are pure over certain periods of time. Hence, compared to parallelization based on static dependence analysis, more programs potentially benefit from parallelization.