Reference counting is not naturally suitable for running on multiprocessors. The update of pointers and reference counts requires atomic and synchronized operations. We present a novel reference counting algorithm suitable for a multiprocessor that does not require any synchronized operation in its write barrier (not even a compare-and-swap type of synchronization). The algorithm is efficient and may compete with any tracing algorithm.

Java uses garbage collection (GC) for the automatic reclamation of computer memory no longer required by a running application. GC implementations for Java Virtual Machines (JVM) are typically designed for single processor machines, and do not necessarily perform well for a server program with many threads running on a multiprocessor. We designed and implemented an on-the-fly GC, based on the algorithm of Doligez, Leroy and Gonthier [13, 12] (DLG), for Java in this environment. An on-the-fly collector, a collector that does not stop the program threads, allows all processors to be utilized during collection and provides uniform response times. We extended and adapted DLG for Java (e.g., adding support for weak references) and for modern multiprocessors without sequential consistency, and added performance improvements (e.g., to keep track of the objects remaining to be traced). We compared the performance of our implementation with stop-the-world mark-sweep GC. Our measurements show th...

Purely functional programs should run well on parallel hardware because of the absence of side effects, but it has proved hard to realise this potential in practice. Plenty of papers describe promising ideas, but vastly fewer describe real implementations with good wall-clock performance. We describe just such an implementation, and quantitatively explore some of the complex design tradeoffs that make such implementations hard to build. Our measurements are necessarily detailed and specific, but they are reproducible, and we believe that they offer some general insights. 1.

. Larchant-RDOSS is a distributed shared memory that persists on reliable storage across process lifetimes. Memory management is automatic: caching of data and of locks, coherence, collecting objects unreachable from the persistent root, writing reachable objects to disk, and reducing store fragmentation. Memory management is based on a novel garbage collection algorithm, that (i) approximates a global trace by a series of partial traces within dynamically determined subsets of the memory, (ii) causes no extra I/O or locking traffic, and (iii) needs no extra synchronization between the collector and the application processes. This results in a simple programming model, and expected minimal added application latency. The algorithm is designed for the most unfavorable environment (uncontrolled programming language, reference by pointers, non-coherent shared memory) and should work well also in more favorable settings. 1 Introduction The Reliable Distributed Object Storage System (Larcha...

Many concurrent garbage collection (GC) algorithms have been devised, but few have been implemented and evaluated, particularly for the Java programming language. Sapphire is an algorithm we have devised for concurrent copying GC. Sapphire stresses minimizing the amount of time any given application thread may need to block to support the collector. In particular, Sapphire is intended to work well in the presence of a large number of application threads, on small- to medium-scale shared memory multiprocessors. A specific problem that Sapphire addresses is not stopping all threads while thread stacks are adjusted to account for copied objects (in GC parlance, the “flip ” to the new copies). Sapphire extends previous algorithms, and is most closely related to replicating copying collection, a GC technique in which

Caching and persistence support efficient, convenient and transparent distributed data sharing. The most natural model of persistence is persistence by reachability, managed automatically by a garbage collector (GC). We propose a very general model of such a system (based on distributed shared memory) and a scalable, asynchronous distributed GC algorithm. Within this model, we show sufficient and widely applicable correctness conditions for the interactions between applications, store, memory, coherence, and GC.

With concurrent and garbage collected languages like Java and C# becoming popular, the need for a suitable non-intrusive, efficient, and concurrent multiprocessor garbage collector has become acute. We propose a novel mark and sweep on-the-fly algorithm based on the sliding views mechanism of Levanoni and Petrank. We have implemented our collector on the Jikes Java Virtual Machine running on a Netfinity multiprocessor and compared it to the concurrent algorithm and to the stop-the-world collector supplied with Jikes JVM. The maximum pause time that we measured with our benchmarks over all runs was 2ms. In all runs, the pause times were smaller than those of the stop-the-world collector by two orders of magnitude and they were also always shorter than the pauses of the Jikes concurrent collector. Throughput measurements of the new garbage collector show that it outperforms the Jikes concurrent collector by up to 60%. As expected, the stop-the-world does better than the on-the-fly collectors with results showing about 10% difference. On top of being

The trend in microprocessor design toward multicore and manycore processors means that future performance gains in software will largely come from harnessing parallelism. To realize such gains, we need languages and implementations that can enable parallelism at many different levels. For example, an application might use both explicit threads to implement course-grain parallelism for independent tasks and implicit threads for fine-grain data-parallel computation over a large array. An important aspect of this requirement is supporting a wide range of different scheduling mechanisms for parallel computation. In this paper, we describe the scheduling framework that we have designed and implemented for Manticore, a strict parallel functional language. We take a micro-kernel approach in our design: the compiler and runtime support a small collection of scheduling primitives upon which complex scheduling policies can be implemented. This framework is extremely flexible and can support a wide range of different scheduling policies. It also supports the nesting of schedulers, which is key to both supporting multiple scheduling policies in the same application and to hierarchies of speculative parallel computations. In addition to describing our framework, we also illustrate its expressiveness with several popular scheduling techniques. We present a (mostly) modular approach to extending our schedulers to support cancellation. This mechanism is essential for implementing eager and speculative parallelism. We finally evaluate our framework with a series of benchmarks and an analysis.

Most implementations of critical Internet protocols are written in type-unsafe languages such as C or C++ and are regularly vulnerable to serious security and reliability problems. Type-safe languages eliminate many errors but are not used to due to the perceived performance overheads. We combine two techniques to eliminate this performance penalty in a practical fashion: strong static typing and generative metaprogramming. Static typing eliminates run-time type information by checking safety at compile-time and minimises dynamic checks. Meta-programming uses a single specification to abstract the lowlevel code required to transmit and receive packets. Our domain-specific language, MPL, describes Internet packet protocols and compiles into fast, zero-copy code for both parsing and creating these packets. MPL is designed for implementing quirky Internet protocols ranging from the low-level: Ethernet, IPv4, ICMP and TCP; to the complex application-level: SSH, DNS and BGP; and even file-system protocols such as 9P. We report on fully-featured SSH and DNS servers constructed using MPL and our OCaml framework MELANGE, and measure greater throughput, lower latency, better flexibility and more succinct source code than their C equivalents OpenSSH and BIND. Our quantitative analysis shows that the benefits of MPL-generated code overcomes the additional overheads of automatic garbage collection and dynamic bounds checking. Qualitatively, the flexibility of our approach shows that dramatic optimisations are easily possible. 1.

Standard ML is an established programming language with a well-understood semantics. Several projects have enriched the language with primitives or constructions for concurrency, among them Poly/ML and LCS. We describe first the previous run-time systems for Poly/ML and LCS and then the development of a new memory management system, LEMMA, which allows parallel programs to be run on networks of workstations. LEMMA provides a distributed shared virtual memory with global garbage collection, and in addition allows each machine to run independent local collections. LEMMA is written as a separate layer from the run-time systems of Poly/ML and LCS and is independent of the object representations and process management schemes used in the languages. We give a description of LEMMA and the results of the execution of some preliminary test programs. Key Words: Distributed shared virtual memory, garbage collection, Standard ML. 1 Introduction Standard ML is an established programmin...