On GPU’s viability as a middleware accelerator

Today Graphics Processing Units (GPUs) are a largely underexploited resource on existing desktops and a possible cost-effective enhancement to high-performance systems. To date, most applications that exploit GPUs are specialized scientific applications. Little attention has been paid to harnessing these highly-parallel devices to support more generic functionality at the operating system or middleware level. This study starts from the hypothesis that generic middleware-level techniques that improve distributed system reliability or performance (such as content addressing, erasure coding, or data similarity detection) can be significantly accelerated using GPU support. We take a first step towards validating this hypothesis and we design StoreGPU, a library that accelerates a number of hashing-based middleware primitives popular in distributed storage system implementations. Our evaluation shows that StoreGPU enables up twenty five fold performance gains on synthetic benchmarks as well as on a high-level application: the online similarity detection between large data files.

Hierarchical analysis of piecewise affine models of gene regulatory networks

A key point in the analysis of dynamical models of biological systems is to handle systems of relatively high dimensions. In the present paper we propose a method to hierarchically organize a certain type of piecewise affine (PWA) differential systems. This specific class of systems has been extensively studied for the past few years, as it provides a good framework to model gene regulatory networks. The method, shown on several examples, allows a qualitative analysis of the asymptotic behavior of a PWA system, decomposing it into several smaller subsystems. This technique, based on the well-known strongly connected components decomposition, is not new. However, its adaptation to the non-smooth PWA differential equations turns out to be quite relevant because of the strong discrete structure underlying these equations. Its biological relevance is shown on a 7-dimensional PWA system modeling the gene network responsible for the carbon starvation response in Escherichia coli.

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Individual variability of behavioural responses by Wandering Albatrosses (Diomedea exulans) to human disturbance

Sub-Antarctic Marion Island has had a permanent research station for 50 years and the islands Wandering Albatrosses have been intensively studied for 20 years. The reactions of breeding birds to approaches by a human on foot were recorded. Three response variables were calculated: intensity of vocal reaction (IVR), intensity of non-vocal reaction (INR) and overall response index (ORI). At 5 m from the nest, twice as many birds stood and/or vocalised as at 15 m. Nearest neighbour distance, age and gender did not explain individual variability of responses. Study colony birds had higher IVR scores than non-study colony birds; birds at colonies closest to the station had the highest ORI scores. A better breeding record was associated with lower IVR and ORI scores, but a causative relationship remains to be demonstrated. A minimum viewing distance of 25 m is recommended for breeding Wandering Albatrosses.

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A framework for characterizing overlap of communication and computation in parallel applications

Effective overlap of computation and communication is a well understood technique for latency hiding and can yield significant performance gains for applications on high-end computers. In this paper, we propose an instrumentation framework for message-passing systems to characterize the degree of overlap of communication with computation in the execution of parallel applications. The inability to obtain precise time-stamps for pertinent communication events is a significant problem, and is addressed by generation of minimum and maximum bounds on achieved overlap. The overlap measures can aid application developers and system designers in investigating scalability issues. The approach has been used to instrument two MPI implementations as well as the ARMCI system. The implementation resides entirely within the communication library and thus integrates well with existing approaches that operate outside the library. The utility of the framework is demonstrated by analyzing communication-computation overlap for micro-benchmarks and the NAS benchmarks, and the insights obtained are used to modify the NAS SP benchmark, resulting in improved overlap.

How ubiquitous is adaptation? A critique of the epiphenomenist program

It is important to distinguish adaptation per se (adaptedness, or being adapted) from the more specific concept of adaptation for some function. Commonly used criteria for adaptation in either sense have limited applicability. There are, however, a number of widely applicable criteria for adaptation per se, such as several kinds of cost, low variation, the maintenance of integration, and the fitness distribution of mutations. Application of these criteria leads to the conclusion that adaptation is overwhelmingly prevalent for features of organisms. Neither the presence nor the absence of adaptation has a privileged status in inference. Effectively neutral evolution can occur on adaptive buttes while maintaining the same degree of adaptation, but it is likely to be relatively minor.

Does Off-Farm Work Discourage Soil Conservation? Incentives and Disincentives Throughout Two Honduran Hillside Communities

   Soil conservation is widely regarded a critical component of sustainable livelihood strategies for the hillsides of Honduras. However, neoliberal polices have reduced economic incentives for agricultural intensification. Recent studies indicate off-farm work opportunities address poverty in a way conservation and development efforts do not. Yet off-farm work may discourage poor farmers from practicing soil conservation. A middle ground is needed. This study indicates micro-credit can substitute for off-farm work and encourage soil conservation practice. Many regions throughout Honduras have had extensive contact with soil conservation programs and would benefit more from credit services than redundant technological extension.

Leitlinien zur molekulargenetischen Diagnostik: Fragiles-X und Fragiles-X assoziiertes Tremor/Ataxie Syndrom

Ohne Zusammenfassung

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Middleware for enterprise scale data stream management using utility-driven self-adaptive information flows

We consider enterprise-wide information flows that are responsible for acquiring, processing and delivering operational information across the business units. Middleware that enables such aggregation of data-streams must not only support scalable and efficient self-management to deal with changes in the operating conditions, but should also have an embedded business-sense to appreciate the business critical nature of some updates. In this paper, we present a novel self-adaptation algorithm that has been designed to scale efficiently for thousands of streams and aims to maximize the overall business utility attained from running middleware-based applications. The outcome is that the middleware not only deals with changing network conditions or resource requirements, but also responds appropriately to changes in business policies. An important feature of the algorithm is a hierarchical node-partitioning scheme that decentralizes reconfiguration and suitably localizes its impact. Extensive simulation experiments and benchmarks attained with actual enterprise operational data corroborate this paper’s claims.

A finite volume method for stochastic integrate-and-fire models

The stochastic integrate and fire neuron is one of the most commonly used stochastic models in neuroscience. Although some cases are analytically tractable, a full analysis typically calls for numerical simulations. We present a fast and accurate finite volume method to approximate the solution of the associated Fokker-Planck equation. The discretization of the boundary conditions offers a particular challenge, as standard operator splitting approaches cannot be applied without modification. We demonstrate the method using stationary and time dependent inputs, and compare them with Monte Carlo simulations. Such simulations are relatively easy to implement, but can suffer from convergence difficulties and long run times. In comparison, our method offers improved accuracy, and decreases computation times by several orders of magnitude. The method can easily be extended to two and three dimensional Fokker-Planck equations.

Causal Explanation of Indonesian Forest Fires: Concepts, Applications, and Research Priorities

Problems with studies, claims, and assumptions that have been made about the causes of fires in Indonesia's tropical moist forests are identified, and the kinds of concepts, methods, prioritizing, and data needed to resolve the problems are discussed. Separate sections are devoted to studying ignitions, studying fire susceptibility and fire behavior, and using the goal of causal explanation to guide interdisciplinary research.

Malleable applications for scalable high performance computing

Iterative applications are known to run as slow as their slowest computational component. This paper introduces malleability, a new dynamic reconfiguration strategy to overcome this limitation. Malleability is the ability to dynamically change the data size and number of computational entities in an application. Malleability can be used by middleware to autonomously reconfigure an application in response to dynamic changes in resource availability in an architecture-aware manner, allowing applications to optimize the use of multiple processors and diverse memory hierarchies in heterogeneous environments. The modular Internet Operating System (IOS) was extended to reconfigure applications autonomously using malleability. Two different iterative applications were made malleable. The first is used in astronomical modeling, and representative of maximum-likelihood applications was made malleable in the SALSA programming language. The second models the diffusion of heat over a two dimensional object, and is representative of applications such as partial differential equations and some types of distributed simulations. Versions of the heat application were made malleable both in SALSA and MPI. Algorithms for concurrent data redistribution are given for each type of application. Results show that using malleability for reconfiguration is 10 to 100 times faster on the tested environments. The algorithms are also shown to be highly scalable with respect to the quantity of data involved. While previous work has shown the utility of dynamically reconfigurable applications using only computational component migration, malleability is shown to provide up to a 15% speedup over component migration alone on a dynamic cluster environment. This work is part of an ongoing research effort to enable applications to be highly reconfigurable and autonomously modifiable by middleware in order to efficiently utilize distributed environments. Grid computing environments are becoming increasingly heterogeneous and dynamic, placing new demands on applications’ adaptive behavior. This work shows that malleability is a key aspect in enabling effective dynamic reconfiguration of iterative applications in these environments.

An autonomic provisioning framework for outsourcing data center based on virtual appliances

As outsourcing data centers emerge to host applications and services from many different organizations, it is critical for data center owners to isolate different applications while dynamically and optimally allocate sharable resources among them. To address this issue, we propose a virtual-appliance-based autonomic resource provisioning framework for large virtualized data centers. We present the architecture of the data center with enriched autonomic features. We define a non-linear constrained optimization model for dynamic resource provisioning and present a novel analytic solution. Key factors, including virtualization overhead and reconfiguration delay, are incorporated into the model. Experimental results based on a prototype demonstrate that the system-level performance has been greatly improved by taking advantage of fine-grained server consolidation, and the whole system exhibits flexible adaptation in failure scenarios. Experiments with the impact of switching delay also show the efficiency of the framework due to significantly reduced provisioning time.

A self-managing wide-area data streaming service

Efficient and robust data streaming services are a critical requirement of emerging Grid applications, which are based on seamless interactions and coupling between geographically distributed application components. Furthermore the dynamism of Grid environments and applications requires that these services be able to continually manage and optimize their operation based on system state and application requirements. This paper presents a design and implementation of such a self-managing data-streaming service based on online control strategies. A Grid-based fusion workflow scenario is used to evaluate the service and demonstrate its feasibility and performance.

1000 islands: an integrated approach to resource management for virtualized data centers

Recent advances in hardware and software virtualization offer unprecedented management capabilities for the mapping of virtual resources to physical resources. It is highly desirable to further create a “service hosting abstraction” that allows application owners to focus on service level objectives (SLOs) for their applications. This calls for a resource management solution that achieves the SLOs for many applications in response to changing data center conditions and hides the complexity from both application owners and data center operators. In this paper, we describe an automated capacity and workload management system that integrates multiple resource controllers at three different scopes and time scales. Simulation and experimental results confirm that such an integrated solution ensures efficient and effective use of data center resources while reducing service level violations for high priority applications.

Adaptationism and the adaptive landscape

Debates over adaptationism can be clarified and partially resolved by careful consideration of the ‘grain’ at which evolutionary processes are described. The framework of ‘adaptive landscapes’ can be used to illustrate and facilitate this investigation. We argue that natural selection may have special status at an intermediate grain of analysis of evolutionary processes. The cases of sickle-cell disease and genomic imprinting are used as case studies.

Scheduling mixed-parallel applications with advance reservations

This paper investigates the scheduling of mixed-parallel applications, which exhibit both task and data parallelism, in advance reservations settings. Both the problem of minimizing application turn-around time and that of meeting a deadline are studied. For each several scheduling algorithms are proposed, some of which borrow ideas from previously published work in non-reservation settings. Algorithms are compared in simulation over a wide range of application and reservation scenarios. The main finding is that schedules computed using the previously published CPA algorithm can be adapted to advance reservation settings, notably resulting in low resource consumption and thus high efficiency.

Hennigian Phylogenetic Systematics and the ‘Groundplan’ vs. ‘Post-Groundplan’ Approaches: A Reply to Kukalová-Peck

The recent contribution by Jarmila Kukalová-Peck on Hennigian phylogenetics and hexapod limb evolution is critically evaluated.

Time-sharing parallel applications through performance-targeted feedback-controlled real-time scheduling

Most parallel machines, such as clusters, are space-shared in order to isolate batch parallel applications from each other and optimize their performance. However, this leads to low utilization or potentially long waiting times. We propose a self-adaptive approach to time-sharing such machines that provides isolation and allows the execution rate of an application to be tightly controlled by the administrator. Our approach combines a periodic real-time scheduler on each node with a global feedback-based control system that governs the local schedulers. We have developed an online system that implements our approach. The system takes as input a target execution rate for each application, and automatically and continuously adjusts the applications’ real-time schedules to achieve those rates with proportional CPU utilization. Target rates can be dynamically adjusted. Applications are performance-isolated from each other and from other work that is not using our system. We present an extensive evaluation that shows that the system remains stable with low response times, and that our focus on CPU isolation and control does not come at the significant expense of network I/O, disk I/O, or memory isolation.