Transparently Mixing Undo Logs and Software Reversibility for State Recovery in Optimistic PDES

The rollback operation is a fundamental building block to support the correct execution of a speculative Time Warp-based Parallel Discrete Event Simulation. In the literature, several solutions to reduce the execution cost of this operation have been proposed, either based on the creation of a checkpoint of previous simulation state images, or on the execution of negative copies of simulation events which are able to undo the updates on the state. In this paper, we explore the practical design and implementation of a state recoverability technique which allows to restore a previous simulation state either relying on checkpointing or on the reverse execution of the state updates occurred while processing events in forward mode. Differently from other proposals, we address the issue of executing backward updates in a fully-transparent and event granularity-independent way, by relying on static software instrumentation (targeting the x86 architecture and Linux systems) to generate at runtime reverse update code blocks (not to be confused with reverse events, proper of the reverse computing approach). These are able to undo the effects of a forward execution while minimizing the cost of the undo operation. We also present experimental results related to our implementation, which is released as free software and fully integrated into the open source ROOT-Sim (ROme OpTimistic Simulator) package. The experimental data support the viability and effectiveness of our proposal

Mixing Hardware and Software Reversibility for Speculative Parallel Discrete Event Simulation

Speculative parallel discrete event simulation requires a support for reversing processed events, also called state recovery, when causal inconsistencies are revealed. In this article we present an approach where state recovery relies on a mix of hardware- and software-based techniques. We exploit the Hardware Transactional Memory (HTM) support, as offered by Intel Haswell CPUs, to process events as in-memory transactions, which are possibly committed only after their causal consistency is verified. At the same time, we exploit an innovative software-based reversibility technique, fully relying on transparent software instrumentation targeting x86/ELF objects, which enables undoing side effects by events with no actual backward re-computation. Each thread within our speculative processing engine dynamically (on a per-event basis) selects which recovery mode to rely on (hardware vs software) depending on varying runtime dynamics. The latter are captured by a lightweight analytic model indicating to what extent the HTM support (not paying any instrumentation cost) is efficient, and after what level of events’ parallelism it starts degrading its performance, e.g., due to excessive data conflicts while manipulating causality meta-data within HTM-based transactions. We released our implementation as open source software and provide experimental results for an assessment of its effectiveness. © Springer International Publishing Switzerland 2016

Process Calculi Abstractions for Biology

Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-

Optimizing simulation on shared-memory platforms: The smart cities case

Modern advancements in computing architectures have been accompanied by new emergent paradigms to run Parallel Discrete Event Simulation models efficiently. Indeed, many new paradigms to effectively use the available underlying hardware have been proposed in the literature. Among these, the Share-Everything paradigm tackles massively-parallel shared-memory machines, in order to support speculative simulation by taking into account the limits and benefits related to this family of architectures. Previous results have shown how this paradigm outperforms traditional speculative strategies (such as data-separated Time Warp systems) whenever the granularity of executed events is small. In this paper, we show performance implications of this simulation-engine organization when the simulation models have a variable granularity. To this end, we have selected a traffic model, tailored for smart cities-oriented simulation. Our assessment illustrates the effects of the various tuning parameters related to the approach, opening to a higher understanding of this innovative paradigm

RAMSES: Reversibility-based agent modeling and simulation environment with speculation-support

This paper presents RAMSES, a framework for easily specifying agent-based discrete event models entailing both environment and agent entities. RAMSES offers parallel execution capabilities based on speculative event processing and an innovative software reversibility technique that copes with state restore in case the run slides along a non-consistent speculative path. Reversibility in RAMSES relies on transparent static software instrumentation, thus allowing the model developer to concentrate on the actual forward-execution logic of the simulation events occurring in the system. An experimental assessment of RAMSES is also presented, which is aimed at determining its run-time effectiveness and its potential for simplifying the development of agent-based models when compared to other (general purpose) speculative frameworks for parallel discrete event simulation

Formal executable descriptions of biological systems

The similarities between systems of living entities and systems of concurrent processes may support biological experiments in silico. Process calculi offer a formal framework to describe biological systems, as well as to analyse their behaviour, both from a qualitative and a quantitative point of view. A couple of little examples help us in showing how this can be done. We mainly focus our attention on the qualitative and quantitative aspects of the considered biological systems, and briefly illustrate which kinds of analysis are possible. We use a known stochastic calculus for the first example. We then present some statistics collected by repeatedly running the specification, that turn out to agree with those obtained by experiments in vivo. Our second example motivates a richer calculus. Its stochastic extension requires a non trivial machinery to faithfully reflect the real dynamic behaviour of biological systems

A Power Cap Oriented Time Warp Architecture

Controlling power usage has become a core objective in modern computing platforms. In this article we present an innovative Time Warp architecture oriented to efficiently run parallel simulations under a power cap. Our architectural organization considers power usage as a foundational design principle, as opposed to classical power-unaware Time Warp design. We provide early experimental results showing the potential of our proposal

Multi-Platform Design of Smartphone Applications

Smartphone application developers should support all the main leading platforms which share the market thus increasing time-to-market and development cost. To solve this problem, the work proposes a design flow based on Model-Driven Design to develop a single version of the smartphone application which can be automatically translated into the main platform-dependent versions. We introduce a UML2 profile to represent the elements of the smartphone application independently of the target platform; the behavior of the application is modeled as a finite-state machine while the graphical user interface is modeled by using classes and objects. A set of translation rules are defined to obtain a platform-depended representation and then the actual code. The methodology has been validated by generating an application for the Android and Windows Phone platforms and by comparing it to the versions written in the traditional way

Virtual Platform-Based Design Space Exploration of Power-Efficient Distributed Embedded Applications

Networked embedded systems are essential building blocks of a broad variety of distributed applications ranging from agriculture to industrial automation to healthcare and more. These often require specific energy optimizations to increase the battery lifetime or to operate using energy harvested from the environment. Since a dominant portion of power consumption is determined and managed by software, the software development process must have access to the sophisticated power management mechanisms provided by state-of-the-art hardware platforms to achieve the best tradeoff between system availability and reactivity. Furthermore, internode communications must be considered to properly assess the energy consumption. This article describes a design flow based on a SystemC virtual platform including both accurate power models of the hardware components and a fast abstract model of the wireless network. The platform allows both model-driven design of the application and the exploration of power and network management alternatives. These can be evaluated in different network scenarios, allowing one to exploit power optimization strategies without requiring expensive field trials. The effectiveness of the approach is demonstrated via experiments on a wireless body area network application

Osteopontin at the Crossroads of Inflammation and Tumor Progression.

Complex interactions between tumor and host cells regulate systemic tumor dissemination, a process that begins early at the primary tumor site and goes on until tumor cells detach themselves from the tumor mass and start migrating into blood or lymphatic vessels. Metastatic cells colonize target organs and are capable of surviving and growing at distant sites. In this context, osteopontin (OPN) appears to be a key determinant of the cross-talk between cancer cells and the host microenvironment, which in turn modulates immune evasion. OPN is overexpressed in several human carcinomas and has been implicated in inflammation, tumor progression, and metastasis. Thus, it represents one of the most attracting targets for cancer therapy. Within the tumor mass, OPN is secreted in various forms either by the tumor itself or by stroma cells, and it can exert either pro- or anti-tumorigenic effects according to cell type and tumor microenvironment. Thus, targeting OPN for therapeutic purposes needs to take into account the heterogeneous functions of the multiple OPN forms with regard to cancer formation and progression. In this review, we will describe the role of systemic, tumor-derived, and stroma-derived OPN, highlighting its pivotal role at the crossroads of inflammation and tumor progression