Accelerating Exact Stochastic Simulation of Biochemical Systems

The ability to accurately and efficiently simulate computer models of biochemical systems is of growing importance to the molecular biology and pharmaceutical research communities. Exact stochastic simulation is a popular approach for simulating such systems because it properly represents genetic noise and it accurately represents systems with small populations of chemical species. Unfortunately, the computational demands of exact stochastic simulation often limit its applicability. To enable next-generation whole-cell and multi-cell stochastic modeling, advanced tools and techniques must be developed to increase simulation efficiency. This work assesses the applicability of a variety of hardware and software acceleration approaches for exact stochastic simulation including serial algorithm improvements, parallel computing, reconfigurable computing, and cluster computing. Through this analysis, improved simulation techniques for biological systems are explored and evaluated

Cyber-Virtual Systems: Simulation, Validation & Visualization

We describe our ongoing work and view on simulation, validation and visualization of cyber-physical systems in industrial automation during development, operation and maintenance. System models may represent an existing physical part - for example an existing robot installation - and a software simulated part - for example a possible future extension. We call such systems cyber-virtual systems. In this paper, we present the existing VITELab infrastructure for visualization tasks in industrial automation. The new methodology for simulation and validation motivated in this paper integrates this infrastructure. We are targeting scenarios, where industrial sites which may be in remote locations are modeled and visualized from different sites anywhere in the world. Complementing the visualization work, here, we are also concentrating on software modeling challenges related to cyber-virtual systems and simulation, testing, validation and verification techniques for them. Software models of industrial sites require behavioural models of the components of the industrial sites such as models for tools, robots, workpieces and other machinery as well as communication and sensor facilities. Furthermore, collaboration between sites is an important goal of our work.Comment: Preprint, 9th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2014

Parallelisation strategies for agent based simulation of immune systems

Background In recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeling (ABM), has attracted considerable efforts. The ABM approach is a very common technique in the biological domain due to high demand for a large scale analysis tools for the collection and interpretation of information to solve biological problems. Simulating massive multi-agent systems (i.e. simulations containing a large number of agents/entities) requires major computational effort which is only achievable through the use of parallel computing approaches. Results This paper explores different approaches to parallelising the key component of biological and immune system models within an ABM model: pairwise interactions. The focus of this paper is on the performance and algorithmic design choices of cell interactions in continuous and discrete space where agents/entities are competing to interact with one another within a parallel environment. Conclusions Our performance results demonstrate the applicability of these methods to a broader class of biological systems exhibiting typical cell to cell interactions. The advantage and disadvantage of each implementation is discussed showing each can be used as the basis for developing complete immune system models on parallel hardware

Modeling the Internet of Things: a simulation perspective

This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the heterogeneity of scenarios seriously complicates this task. This imposes the use of sophisticated modeling and simulation techniques. We discuss novel approaches for the provision of scalable simulation scenarios, that enable the real-time execution of massively populated IoT environments. Attention is given to novel hybrid and multi-level simulation techniques that, when combined with agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches, can provide means to perform highly detailed simulations on demand. To support this claim, we detail a use case concerned with the simulation of vehicular transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High Performance Computing and Simulation (HPCS 2017

Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning

In a chip design project, early design planning has a strong impact on the schedule and the cost of design. Power estimation is part of early design planning, and it greatly affects design decisions. Power modeling performed at a high level of abstraction is fast but inaccurate due to lack of circuit switching activity information. By contrast, power modeling performed at a low level of abstraction is more accurate as the synthesized circuit synthesis is known, but this simulation is typically slow. This report explores a power modeling approach performed at register transfer level (RTL). It exploits machine learning models in order to have a fast yet relatively accurate cycle-by-cycle power estimation. The approach is data-dependent, where cycle-specific models are trained based on the switching activity of signals obtained from RTL simulation and cycle-by-cycle power values obtained from a reference gate-level simulation of an existing RTL design. Therefore, if any changes are applied to the RTL design, re-training of models is required. The approach aims at obtaining fast yet accurate power predictions for new invocations of a given trained model using signal activity information collected during simulation of the unmodified RTL. At a low level, the complete visibility of signals in a design unintuitively might cause overtraining the model leading to inaccurate estimation. The suggested model employs automatic feature selection in each cycle. Based on the invocations used to train the cycle-by-cycle models, only signals that may switch during a given cycle will be selected as the features for their respective cycle-specific model. The method was tested on an 8-by-8 DCT design and the power estimates were within 6.5% of those from a commercial power analysis tool. This report also simulates and compares the approach of cycle-specific models to the approach of a single global model for all cycles and show that the cycle-specific approach is twice as accurate.Electrical and Computer Engineerin

Virtual Communication Stack: Towards Building Integrated Simulator of Mobile Ad Hoc Network-based Infrastructure for Disaster Response Scenarios

Responses to disastrous events are a challenging problem, because of possible damages on communication infrastructures. For instance, after a natural disaster, infrastructures might be entirely destroyed. Different network paradigms were proposed in the literature in order to deploy adhoc network, and allow dealing with the lack of communications. However, all these solutions focus only on the performance of the network itself, without taking into account the specificities and heterogeneity of the components which use it. This comes from the difficulty to integrate models with different levels of abstraction. Consequently, verification and validation of adhoc protocols cannot guarantee that the different systems will work as expected in operational conditions. However, the DEVS theory provides some mechanisms to allow integration of models with different natures. This paper proposes an integrated simulation architecture based on DEVS which improves the accuracy of ad hoc infrastructure simulators in the case of disaster response scenarios.Comment: Preprint. Unpublishe

Modeling, Simulation and Emulation of Intelligent Domotic Environments

Intelligent Domotic Environments are a promising approach, based on semantic models and commercially off-the-shelf domotic technologies, to realize new intelligent buildings, but such complexity requires innovative design methodologies and tools for ensuring correctness. Suitable simulation and emulation approaches and tools must be adopted to allow designers to experiment with their ideas and to incrementally verify designed policies in a scenario where the environment is partly emulated and partly composed of real devices. This paper describes a framework, which exploits UML2.0 state diagrams for automatic generation of device simulators from ontology-based descriptions of domotic environments. The DogSim simulator may simulate a complete building automation system in software, or may be integrated in the Dog Gateway, allowing partial simulation of virtual devices alongside with real devices. Experiments on a real home show that the approach is feasible and can easily address both simulation and emulation requirement

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability