71 resultados para fault-tolerant


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As the complexity of computing systems grows, reliability and energy are two crucial challenges asking for holistic solutions. In this paper, we investigate the interplay among concurrency, power dissipation, energy consumption and voltage-frequency scaling for a key numerical kernel for the solution of sparse linear systems. Concretely, we leverage a task-parallel implementation of the Conjugate Gradient method, equipped with an state-of-the-art pre-conditioner embedded in the ILUPACK software, and target a low-power multi core processor from ARM.In addition, we perform a theoretical analysis on the impact of a technique like Near Threshold Voltage Computing (NTVC) from the points of view of increased hardware concurrency and error rate.

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Phytochelatins (PCs) are required for arsenic (As) detoxification in nontolerant plants. In addition, a role for PCs in arsenate tolerance has recently been proven, with tolerant plants able to accumulate significantly higher concentrations of As-PC complexes at equivalent levels of stress than nontolerant plants. The relationship between arsenate influx and PC production in tolerant and non-tolerant Holcus lanatus plants was determined in this study, along with an investigation of the effect of inhibition of PC synthesis by buthionine sulfoximine (BSO) on arsenate tolerance. A strong correlation between PC production and arsenate influx was demonstrated in arsenate-tolerant plants. In addition, inhibition of PC synthesis by BSO in tolerant plants increased arsenate sensitivity to that of the nontolerant clone. This dramatic reduction in tolerance proves that PC production is an essential component of the arsenate tolerance mechanism in H. lanatus. This study proposes that while there is a single major gene for arsenate tolerance, hypostatic modifiers are also in operation, affecting the expression of the tolerance character. © New Phytologist (2002).

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Velvetgrass (Holcus lanatus L.), also known as Yorkshire fog grass, has evolved tolerance to high levels of arsenate, and this adaptation involves reduced accumulation of arsenate through the suppression of the high affinity phosphate-arsenate uptake system. To determine the role of P nutrition in arsenate tolerance, inhibition kinetics of arsenate influx by phosphate were determined. The concentration of inhibitor required to reduce maximum influx (V(max)) by 50%, K1, of phosphate inhibition of arsenate influx was 0.02 mol m-3 in both tolerant and nontolerant clones. This was compared with the concentration where influx is 50% of maximum, a K(m), for arsenate influx of 0.6 mol m-3 for tolerants and 0.025 mol m-3 for nontolerants and, therefore, phosphate was much more effective at inhibiting arsenate influx in tolerant genotypes. The high affinity phosphate uptake system is inducible under low plant phosphate status, this increasing plant phosphate status should increase tolerance by decreasing arsenate influx. Root extension in arsenate solutions of tolerant and nontolerant tillers grown under differing phosphate nutritional regimes showed that indeed, increased plant P status increased the tolerance to arsenate of both tolerant and nontolerant clones. That plant P status increased tolerance again argues that P nutrition has a critical role in arsenate tolerance. To determine if short term flux and solution culture studies were relevant to As and P accumulation in soils, soil and plant material from a range of As contaminated sites were analyzed. As predicted from the short-term competition studies, P was accumulated preferentially to As in arsenate tolerant clones growing on mine spoil soils even when acid extractable arsenate in the soils was much greater than acid extractable phosphate. Though phosphate was much more efficient at competing with arsenate for uptake, plants growing on arsenate contaminated land still accumulated considerable amounts of As. Plants from the differing habitats showed large variation in plant phosphate status, pasture plants having much higher P levels than plants growing on the most contaminated mine spoil soils. The selectivity of the phosphate-arsenate uptake system for phosphate compared with arsenate, coupled with the suppression of this uptake system enabled tolerant clones of the grass velvetgrass to grow on soils that were highly contaminated with arsenate and deficient in phosphate.

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The end of Dennard scaling has promoted low power consumption into a firstorder concern for computing systems. However, conventional power conservation schemes such as voltage and frequency scaling are reaching their limits when used in performance-constrained environments. New technologies are required to break the power wall while sustaining performance on future processors. Low-power embedded processors and near-threshold voltage computing (NTVC) have been proposed as viable solutions to tackle the power wall in future computing systems. Unfortunately, these technologies may also compromise per-core performance and, in the case of NTVC, xreliability. These limitations would make them unsuitable for HPC systems and datacenters. In order to demonstrate that emerging low-power processing technologies can effectively replace conventional technologies, this study relies on ARM’s big.LITTLE processors as both an actual and emulation platform, and state-of-the-art implementations of the CG solver. For NTVC in particular, the paper describes how efficient algorithm-based fault tolerance schemes preserve the power and energy benefits of very low voltage operation.

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Methane-derived authigenic carbonate (MDAC) mound features at the Codling Fault Zone (CFZ), located in shallow waters (50-120m) of the western Irish Sea were investigated and provide a comparison to deep sea MDAC settings. Carbonates consisted of aragonite as the major mineral phase, with δ13C depletion to -50‰ and δ18O enrichment to~2‰. These isotope signatures, together with the co-precipitation of framboidal pyrite confirm that anaerobic oxidation of methane (AOM) is an important process mediating methane release to the water column and the atmosphere in this region. 18O-enrichment could be a result of MDAC precipitation with seawater in colder than present day conditions, or precipitation with 18O-enriched water transported from deep petroleum sources. The 13C depletion of bulk carbonate and sampled gas (-70‰) suggests a biogenic source, but significant mixing of thermogenic gas and depletion of the original isotope signature cannot be ruled out. Active seepage was recorded from one mound and together with extensive areas of reduced sediment, confirms that seepage is ongoing. The mounds appear to be composed of stacked pavements that are largely covered by sand and extensively eroded. The CFZ mounds are colonized by abundant Sabellaria polychaetes and possible Nemertesia hydroids, which benefit indirectly from available hard substrate. In contrast to deep sea MDAC settings where seep-related macrofauna are commonly reported, seep-specialist fauna appear to be lacking at the CFZ. In addition, unlike MDAC in deep waters where organic carbon input from photosynthesis is limited, lipid biomarkers and isotope signatures related to marine planktonic production (e.g. sterols, alkanols) were most abundant. Evidence for microbes involved in AOM was limited from samples taken; possibly due to this dilution effect from organic matter derived from the photic zone, and will require further investigation. 

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Electric vehicles (EVs) and hybrid electric vehicles (HEVs) can reduce greenhouse gas emissions while switched reluctance motor (SRM) is one of the promising motor for such applications. This paper presents a novel SRM fault-diagnosis and fault-tolerance operation solution. Based on the traditional asymmetric half-bridge topology for the SRM driving, the central tapped winding of the SRM in modular half-bridge configuration are introduced to provide fault-diagnosis and fault-tolerance functions, which are set idle in normal conditions. The fault diagnosis can be achieved by detecting the characteristic of the excitation and demagnetization currents. An SRM fault-tolerance operation strategy is also realized by the proposed topology, which compensates for the missing phase torque under the open-circuit fault, and reduces the unbalanced phase current under the short-circuit fault due to the uncontrolled faulty phase. Furthermore, the current sensor placement strategy is also discussed to give two placement methods for low cost or modular structure. Simulation results in MATLAB/Simulink and experiments on a 750-W SRM validate the effectiveness of the proposed strategy, which may have significant implications and improve the reliability of EVs/HEVs.

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Background: Large-scale biological jobs on high-performance computing systems require manual intervention if one or more computing cores on which they execute fail. This places not only a cost on the maintenance of the job, but also a cost on the time taken for reinstating the job and the risk of losing data and execution accomplished by the job before it failed. Approaches which can proactively detect computing core failures and take action to relocate the computing core's job onto reliable cores can make a significant step towards automating fault tolerance. Method: This paper describes an experimental investigation into the use of multi-agent approaches for fault tolerance. Two approaches are studied, the first at the job level and the second at the core level. The approaches are investigated for single core failure scenarios that can occur in the execution of parallel reduction algorithms on computer clusters. A third approach is proposed that incorporates multi-agent technology both at the job and core level. Experiments are pursued in the context of genome searching, a popular computational biology application. Result: The key conclusion is that the approaches proposed are feasible for automating fault tolerance in high-performance computing systems with minimal human intervention. In a typical experiment in which the fault tolerance is studied, centralised and decentralised checkpointing approaches on an average add 90% to the actual time for executing the job. On the other hand, in the same experiment the multi-agent approaches add only 10% to the overall execution time