95,223 research outputs found
Abstract State Machines 1988-1998: Commented ASM Bibliography
An annotated bibliography of papers which deal with or use Abstract State
Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm
Havens: Explicit Reliable Memory Regions for HPC Applications
Supporting error resilience in future exascale-class supercomputing systems
is a critical challenge. Due to transistor scaling trends and increasing memory
density, scientific simulations are expected to experience more interruptions
caused by transient errors in the system memory. Existing hardware-based
detection and recovery techniques will be inadequate to manage the presence of
high memory fault rates.
In this paper we propose a partial memory protection scheme based on
region-based memory management. We define the concept of regions called havens
that provide fault protection for program objects. We provide reliability for
the regions through a software-based parity protection mechanism. Our approach
enables critical program objects to be placed in these havens. The fault
coverage provided by our approach is application agnostic, unlike
algorithm-based fault tolerance techniques.Comment: 2016 IEEE High Performance Extreme Computing Conference (HPEC '16),
September 2016, Waltham, MA, US
On-stack replacement, distilled
On-stack replacement (OSR) is essential technology for adaptive optimization, allowing changes to code actively executing in a managed runtime. The engineering aspects of OSR are well-known among VM architects, with several implementations available to date. However, OSR is yet to be explored as a general means to transfer execution between related program versions, which can pave the road to unprecedented applications that stretch beyond VMs. We aim at filling this gap with a constructive and provably correct OSR framework, allowing a class of general-purpose transformation functions to yield a special-purpose replacement. We describe and evaluate an implementation of our technique in LLVM. As a novel application of OSR, we present a feasibility study on debugging of optimized code, showing how our techniques can be used to fix variables holding incorrect values at breakpoints due to optimizations
Dynamic Modelling and Optimisation of Large-Scale Cryogenic Separation Processes
In this work, the open loop dynamic optimisation of a large-scale natural gas processing plant is performed. A rigorous differential-algebraic equation (DAE) model has been formulated to represent main plant units, such as shell and tube heat exchangers, highpressure separator and demethanizing column. In the shell and tube heat exchangers, the hot stream partially condenses and equations to consider the partial condensation of the fluids have been included. A rigorous index one model for the demethanizing column has been developed. The DAE optimisation problem is solved with a simultaneous approach, in which both state and control variables are discretised and the original DAE optimisation model is transformed into a large-scale nonlinear problem (NLP), which is solved using Sequential Quadratic Programming (SQP) methods. Optimal profiles have been obtained for main operating variables to achieve an enhanced product recovery.Fil: Rodriguez, Mariela Alejandra. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - BahĂa Blanca. Planta Piloto de IngenierĂa QuĂmica. Universidad Nacional del Sur. Planta Piloto de IngenierĂa QuĂmica; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - BahĂa Blanca. Planta Piloto de IngenierĂa QuĂmica. Universidad Nacional del Sur. Planta Piloto de IngenierĂa QuĂmica; ArgentinaFil: DĂaz, MarĂa Soledad. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - BahĂa Blanca. Planta Piloto de IngenierĂa QuĂmica. Universidad Nacional del Sur. Planta Piloto de IngenierĂa QuĂmica; Argentin
New directions in water resources management: The role of water pricing policies
Water resources will face increasing competition and higher environmental concerns during this century. To meet these challenges, the new Water Framework Directive has drawn up an integrated framework and established the basic principles for a sustainable water policy in the European Union. The introduction of water prices reflecting the true cost of irrigation is one of its most innovative components. In this paper, a positive mathematical programming model is developed to assess the environmental and socio-economic impacts of water pricing policies in Spanish irrigated lands. The model interface allows friendly use and easy replication in a large number of irrigation districts, selected throughout the Spanish territory. The model results show the impact on environmental indicators, water consumption, cropping patterns, technology adoption, labor, farmers' income, and the water agency revenues when different scenarios of cost recovery are considered. It is argued that this modeling approach may be used as a management tool to assist in the implementation of the cost recovery approach of the new Water Framework Directive
Determining optimal disassembly and recovery strategies
We present a stochastic dynamic programming algorithm fordetermining the optimal disassembly and recovery strategy, giventhe disassembly tree, the process dependent quality distributionsof assemblies, and the quality dependent recovery options andassociated profits for assemblies. This algorithm generalizes theone proposed by Krikke et al. \\cite{Krikke98} in two ways. First,there can be multiple disassembly processes. Second, partialdisassembly is allowed. Both generalizations are important forpractise.
Tolerating Correlated Failures in Massively Parallel Stream Processing Engines
Fault-tolerance techniques for stream processing engines can be categorized
into passive and active approaches. A typical passive approach periodically
checkpoints a processing task's runtime states and can recover a failed task by
restoring its runtime state using its latest checkpoint. On the other hand, an
active approach usually employs backup nodes to run replicated tasks. Upon
failure, the active replica can take over the processing of the failed task
with minimal latency. However, both approaches have their own inadequacies in
Massively Parallel Stream Processing Engines (MPSPE). The passive approach
incurs a long recovery latency especially when a number of correlated nodes
fail simultaneously, while the active approach requires extra replication
resources. In this paper, we propose a new fault-tolerance framework, which is
Passive and Partially Active (PPA). In a PPA scheme, the passive approach is
applied to all tasks while only a selected set of tasks will be actively
replicated. The number of actively replicated tasks depends on the available
resources. If tasks without active replicas fail, tentative outputs will be
generated before the completion of the recovery process. We also propose
effective and efficient algorithms to optimize a partially active replication
plan to maximize the quality of tentative outputs. We implemented PPA on top of
Storm, an open-source MPSPE and conducted extensive experiments using both real
and synthetic datasets to verify the effectiveness of our approach
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