Secure Virtualization and Multicore Platforms State-of-the-Art report

SVaM

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007

A Survey on Security Aspects of Server Virtualization in Cloud Computing

Significant exploitation and utilization of cloud computing in industry is come with and in the identical time vulnerable by unease regarding protection of data hold by cloud computing providers. One of the penalties of moving data processing and storage off business site is that organizations have fewer controls over their infrastructure. seeing that, cloud service (CS) providers must hope that the CS provider is capable to protect their data and infrastructure from both exterior and domestic attacks. Presently however, such hope can only rely on organizational procedures stated by the CS provider and cannot be remotely verified and validated by an external party. The central distinction between cloud computing and conventional enterprise internal Information Technology services is that the proprietor and the consumer of cloud Information Technology infrastructures are separated in cloud. This transform requires a safety responsibility severance in cloud computing. Cloud service providers (CSP) should safe the services they propose and cannot surpass the customers’ authorities. Virtualization is a buildup utterance in the Information Technology world. With the assure to reduce the ever mounting infrastructure inside data centers connected to other important apprehensions such as ease of use and scalability, virtualization technology has been in advance recognition not only with IT experts yet also among administrators and executives as well. The progressively more growing rate of the approval of this technology has exposed these systems to new protection concerns which in recent history have been unnoticed or merely overlooked. This paper presents an in depth state of art gaze at  present most old server virtualization explanations, as well as a writing study on different security matters found inside this virtualization technology. These problems can be practical to all the existing virtualization technologies accessible with no spotlight on a specific answer. Nevertheless, we do susceptibility investigation of two of the mainstream recognized virtualization answers: VMware ESX and Xen. to conclude, we illustrate some clarifications on how to progress the security of online banking and electronic commerce, using virtualization

Benchmarking the Parallel 1D Heat Equation Solver in Chapel, Charm++, C++, HPX, Go, Julia, Python, Rust, Swift, and Java

Many scientific high performance codes that simulate e.g. black holes, coastal waves, climate and weather, etc. rely on block-structured meshes and use finite differencing methods to iteratively solve the appropriate systems of differential equations. In this paper we investigate implementations of an extremely simple simulation of this type using various programming systems and languages. We focus on a shared memory, parallelized algorithm that simulates a 1D heat diffusion using asynchronous queues for the ghost zone exchange. We discuss the advantages of the various platforms and explore the performance of this model code on different computing architectures: Intel, AMD, and ARM64FX. As a result, Python was the slowest of the set we compared. Java, Go, Swift, and Julia were the intermediate performers. The higher performing platforms were C++, Rust, Chapel, Charm++, and HPX