Prompt Application-Transparent Transaction Revalidation in Software Transactional Memory

Software Transactional Memory (STM) allows encapsulating shared-data accesses within transactions, executed with atomicity and isolation guarantees. The assessment of the consistency of a running transaction is performed by the STM layer at specific points of its execution, such as when a read or write access to a shared object occurs, or upon a commit attempt. However, performance and energy efficiency issues may arise when no shared-data read/write operation occurs for a while along a thread running a transaction. In this scenario, the STM layer may not regain control for a considerable amount of time, thus not being able to early detect if such transaction has become inconsistent in the meantime. To tackle this problem we present an STM architecture that, thanks to a lightweight operating system support, is able to perform a fine-grain periodic (hence prompt) revalidation of running transactions. Our proposal targets Linux and x86 systems and has been integrated with the open source TinySTM package. Experimental results with a port of the TPC-C benchmark to STM environments show the effectiveness of our solution

Process-Oriented Collective Operations

Distributing process-oriented programs across a cluster of machines requires careful attention to the effects of network latency. The MPI standard, widely used for cluster computation, defines a number of collective operations: efficient, reusable algorithms for performing operations among a group of machines in the cluster. In this paper, we describe our techniques for implementing MPI communication patterns in process-oriented languages, and how we have used them to implement collective operations in PyCSP and occam-pi on top of an asynchronous messaging framework. We show how to make use of collective operations in distributed processoriented applications. We also show how the process-oriented model can be used to increase concurrency in existing collective operation algorithms

Analysis of source code metrics from ns-2 and ns-3 network simulators

Ns-2 and its successor ns-3 are discrete-event simulators which are closely related to each other as they share common background, concepts and similar aims. Ns-3 is still under development, but it offers some interesting characteristics for developers while ns-2 still has a large user base. While other studies have compared different network simulators, focusing on performance measurements, in this paper we adopted a different approach by focusing on technical characteristics and using software metrics to obtain useful conclusions. We chose ns-2 and ns-3 for our case study because of the popularity of the former in research and the increasing use of the latter. This reflects the current situation where ns-3 has emerged as a viable alternative to ns-2 due to its features and design. The paper assesses the current state of both projects and their respective evolution supported by the measurements obtained from a broad set of software metrics. By considering other qualitative characteristics we obtained a summary of technical features of both simulators including, architectural design, software dependencies or documentation policies.Ministerio de Ciencia e Innovación TEC2009-10639-C04-0

RootJS: Node.js Bindings for ROOT 6

We present rootJS, an interface making it possible to seamlessly integrate ROOT 6 into applications written for Node.js, the JavaScript runtime platform increasingly commonly used to create high-performance Web applications. ROOT features can be called both directly from Node.js code and by JIT-compiling C++ macros. All rootJS methods are invoked asynchronously and support callback functions, allowing non-blocking operation of Node.js applications using them. Last but not least, our bindings have been designed to platform-independent and should therefore work on all systems supporting both ROOT 6 and Node.js. Thanks to rootJS it is now possible to create ROOT-aware Web applications taking full advantage of the high performance and extensive capabilities of Node.js. Examples include platforms for the quality assurance of acquired, reconstructed or simulated data, book-keeping and e-log systems, and even Web browser-based data visualisation and analysis.Comment: 7 pages, 1 figure. To appear in the Proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2016