2,773 research outputs found
Creating a Distributed Programming System Using the DSS: A Case Study of OzDSS
This technical report describes the integration of the Distribution Subsystem (DSS) to the programming system Mozart. The result, OzDSS, is described in detail. Essential when coupling a programming system to the DSS is how the internal model of threads and language entities are mapped to the abstract entities of the DSS. The model of threads and language entities of Mozart is described at a detailed level to explain the design choices made when developing the code that couples the DSS to Mozart. To show the challenges associated with different thread implementations, the C++DSS system is introduced. C++DSS is a C++ library which uses the DSS to implement different types of distributed language entities in the form of C++ classes. Mozart emulates threads, thus there is no risk of multiple threads accessing the DSS simultaneously. C++DSS, on the other hand, makes use of POSIX threads, thus simultaneous access to the DSS from multiple POSIX threads can happen. The fundamental differences in how threads are treated in a system that emulates threads (Mozart) to a system that make use of native-threads~(C++DSS) is discussed. The paper is concluded by a performance comparison between the OzDSS system and other distributed programming systems. We see that the OzDSS system outperforms ``industry grade'' Java-RMI and Java-CORBA implementations
Garbage collection auto-tuning for Java MapReduce on Multi-Cores
MapReduce has been widely accepted as a simple programming pattern that can form the basis for efficient, large-scale, distributed data processing. The success of the MapReduce pattern has led to a variety of implementations for different computational scenarios. In this paper we present MRJ, a MapReduce Java framework for multi-core architectures. We evaluate its scalability on a four-core, hyperthreaded Intel Core i7 processor, using a set of standard MapReduce benchmarks. We investigate the significant impact that Java runtime garbage collection has on the performance and scalability of MRJ. We propose the use of memory management auto-tuning techniques based on machine learning. With our auto-tuning approach, we are able to achieve MRJ performance within 10% of optimal on 75% of our benchmark tests
Lock-free atom garbage collection for multithreaded Prolog
The runtime system of dynamic languages such as Prolog or Lisp and their
derivatives contain a symbol table, in Prolog often called the atom table. A
simple dynamically resizing hash-table used to be an adequate way to implement
this table. As Prolog becomes fashionable for 24x7 server processes we need to
deal with atom garbage collection and concurrent access to the atom table.
Classical lock-based implementations to ensure consistency of the atom table
scale poorly and a stop-the-world approach to implement atom garbage collection
quickly becomes a bottle-neck, making Prolog unsuitable for soft real-time
applications. In this article we describe a novel implementation for the atom
table using lock-free techniques where the atom-table remains accessible even
during atom garbage collection. Relying only on CAS (Compare And Swap) and not
on external libraries, the implementation is straightforward and portable.
Under consideration for acceptance in TPLP.Comment: Paper presented at the 32nd International Conference on Logic
Programming (ICLP 2016), New York City, USA, 16-21 October 2016, 14 pages,
LaTeX, 4 PDF figure
Garbage Collection for Java Distributed Objects
We present a distributed garbage collection algorithm for Java distributed objects using the object model provided by the Java Support for Distributed Objects (JSDA) object model and using weak references in Java. The algorithm can also be used for any other Java based distributed object models that use the stub-skeleton paradigm. Furthermore, the solution could also be applied to any language that supports weak references as a mean of interaction with the local garbage collector. We also give a formal definition and a proof of correctness for the proposed algorithm
- ā¦