Cache-Aware Memory Manager for Optimistic Simulations

Parallel Discrete Event Simulation is a well known technique for executing complex general-purpose simulations where models are described as objects the interaction of which is expressed through the generation of impulsive events. In particular, Optimistic Simulation allows full exploitation of the available computational power, avoiding the need to compute safety properties for the events to be executed. Optimistic Simulation platforms internally rely on several data structures, which are meant to support operations aimed at ensuring correctness, inter-kernel communication and/or event scheduling. These housekeeping and management operations access them according to complex patterns, commonly suffering from misuse of memory caching architectures. In particular, operations like log/restore access data structures on a periodic basis, producing the replacement of in-cache buffers related to the actual working set of the application logic, producing a non-negligible performance drop. In this work we propose generally-applicable design principles for a new memory management subsystem targeted at Optimistic Simulation platforms which can face this issue by wisely allocating memory buffers depending on their actual future access patterns, in order to enhance event-execution memory locality. Additionally, an application-transparent implementation within ROOT-Sim, an open-source generalpurpose optimistic simulation platform, is presented along with experimental results testing our proposal

Realistic Traffic Generation for Web Robots

Critical to evaluating the capacity, scalability, and availability of web systems are realistic web traffic generators. Web traffic generation is a classic research problem, no generator accounts for the characteristics of web robots or crawlers that are now the dominant source of traffic to a web server. Administrators are thus unable to test, stress, and evaluate how their systems perform in the face of ever increasing levels of web robot traffic. To resolve this problem, this paper introduces a novel approach to generate synthetic web robot traffic with high fidelity. It generates traffic that accounts for both the temporal and behavioral qualities of robot traffic by statistical and Bayesian models that are fitted to the properties of robot traffic seen in web logs from North America and Europe. We evaluate our traffic generator by comparing the characteristics of generated traffic to those of the original data. We look at session arrival rates, inter-arrival times and session lengths, comparing and contrasting them between generated and real traffic. Finally, we show that our generated traffic affects cache performance similarly to actual traffic, using the common LRU and LFU eviction policies.Comment: 8 page

Bridging the Gap between Enumerative and Symbolic Model Checkers

We present a method to perform symbolic state space generation for languages with existing enumerative state generators. The method is largely independent from the chosen modelling language. We validated this on three different types of languages and tools: state-based languages (PROMELA), action-based process algebras (muCRL, mCRL2), and discrete abstractions of ODEs (Maple).\ud Only little information about the combinatorial structure of the\ud underlying model checking problem need to be provided. The key enabling data structure is the "PINS" dependency matrix. Moreover, it can be provided gradually (more precise information yield better results).\ud \ud Second, in addition to symbolic reachability, the same PINS matrix contains enough information to enable new optimizations in state space generation (transition caching), again independent from the chosen modelling language. We have also based existing optimizations, like (recursive) state collapsing, on top of PINS and hint at how to support partial order reduction techniques.\ud \ud Third, PINS allows interfacing of existing state generators to, e.g., distributed reachability tools. Thus, besides the stated novelties, the method we propose also significantly reduces the complexity of building modular yet still efficient model checking tools.\ud \ud Our experiments show that we can match or even outperform existing tools by reusing their own state generators, which we have linked into an implementation of our ideas

Obvious: a meta-toolkit to encapsulate information visualization toolkits. One toolkit to bind them all

This article describes “Obvious”: a meta-toolkit that abstracts and encapsulates information visualization toolkits implemented in the Java language. It intends to unify their use and postpone the choice of which concrete toolkit(s) to use later-on in the development of visual analytics applications. We also report on the lessons we have learned when wrapping popular toolkits with Obvious, namely Prefuse, the InfoVis Toolkit, partly Improvise, JUNG and other data management libraries. We show several examples on the uses of Obvious, how the different toolkits can be combined, for instance sharing their data models. We also show how Weka and RapidMiner, two popular machine-learning toolkits, have been wrapped with Obvious and can be used directly with all the other wrapped toolkits. We expect Obvious to start a co-evolution process: Obvious is meant to evolve when more components of Information Visualization systems will become consensual. It is also designed to help information visualization systems adhere to the best practices to provide a higher level of interoperability and leverage the domain of visual analytics

EbbRT: a customizable operating system for cloud applications

Efficient use of hardware requires operating system components be customized to the application workload. Our general purpose operating systems are ill-suited for this task. We present Genesis, a new operating system that enables per-application customizations for cloud applications. Genesis achieves this through a novel heterogeneous distributed structure, a partitioned object model, and an event-driven execution environment. This paper describes the design and prototype implementation of Genesis, and evaluates its ability to improve the performance of common cloud applications. The evaluation of the Genesis prototype demonstrates memcached, run within a VM, can outperform memcached run on an unvirtualized Linux. The prototype evaluation also demonstrates an 14% performance improvement of a V8 JavaScript engine benchmark, and a node.js webserver that achieves a 50% reduction in 99th percentile latency compared to it run on Linux