2,232 research outputs found
A Hamiltonian Krylov-Schur-type method based on the symplectic Lanczos process
We discuss a Krylov-Schur like restarting technique applied within the symplectic Lanczos algorithm for the Hamiltonian eigenvalue problem. This allows to easily implement a purging and locking strategy in order to improve the convergence properties of the symplectic Lanczos algorithm. The Krylov-Schur-like restarting is based on the SR algorithm. Some ingredients of the latter need to be adapted to the structure of the symplectic Lanczos recursion. We demonstrate the efficiency of the new method for several Hamiltonian eigenproblems
Coexistence in locally regulated competing populations and survival of branching annihilating random walk
We propose two models of the evolution of a pair of competing populations.
Both are lattice based. The first is a compromise between fully spatial models,
which do not appear amenable to analytic results, and interacting particle
system models, which do not, at present, incorporate all of the competitive
strategies that a population might adopt. The second is a simplification of the
first, in which competition is only supposed to act within lattice sites and
the total population size within each lattice point is a constant. In a special
case, this second model is dual to a branching annihilating random walk. For
each model, using a comparison with oriented percolation, we show that for
certain parameter values, both populations will coexist for all time with
positive probability. As a corollary, we deduce survival for all time of
branching annihilating random walk for sufficiently large branching rates. We
also present a number of conjectures relating to the r\^{o}le of space in the
survival probabilities for the two populations.Comment: Published in at http://dx.doi.org/10.1214/105051607000000267 the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
CRAFT: A library for easier application-level Checkpoint/Restart and Automatic Fault Tolerance
In order to efficiently use the future generations of supercomputers, fault
tolerance and power consumption are two of the prime challenges anticipated by
the High Performance Computing (HPC) community. Checkpoint/Restart (CR) has
been and still is the most widely used technique to deal with hard failures.
Application-level CR is the most effective CR technique in terms of overhead
efficiency but it takes a lot of implementation effort. This work presents the
implementation of our C++ based library CRAFT (Checkpoint-Restart and Automatic
Fault Tolerance), which serves two purposes. First, it provides an extendable
library that significantly eases the implementation of application-level
checkpointing. The most basic and frequently used checkpoint data types are
already part of CRAFT and can be directly used out of the box. The library can
be easily extended to add more data types. As means of overhead reduction, the
library offers a build-in asynchronous checkpointing mechanism and also
supports the Scalable Checkpoint/Restart (SCR) library for node level
checkpointing. Second, CRAFT provides an easier interface for User-Level
Failure Mitigation (ULFM) based dynamic process recovery, which significantly
reduces the complexity and effort of failure detection and communication
recovery mechanism. By utilizing both functionalities together, applications
can write application-level checkpoints and recover dynamically from process
failures with very limited programming effort. This work presents the design
and use of our library in detail. The associated overheads are thoroughly
analyzed using several benchmarks
Enhancing Energy Production with Exascale HPC Methods
High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose
processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale
simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of
Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and
from the Brazilian Ministry of Science, Technology and Innovation through Rede
Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the
Intel Corporation, which enabled us to obtain the presented experimental results in
uncertainty quantification in seismic imagingPostprint (author's final draft
Tomographic Study of Internal Erosion of Particle Flows in Porous Media
In particle-laden flows through porous media, porosity and permeability are
significantly affected by the deposition and erosion of particles. Experiments
show that the permeability evolution of a porous medium with respect to a
particle suspension is not smooth, but rather exhibits significant jumps
followed by longer periods of continuous permeability decrease. Their origin
seems to be related to internal flow path reorganization by avalanches of
deposited material due to erosion inside the porous medium. We apply neutron
tomography to resolve the spatio-temporal evolution of the pore space during
clogging and unclogging to prove the hypothesis of flow path reorganization
behind the permeability jumps. This mechanistic understanding of clogging
phenomena is relevant for a number of applications from oil production to
filters or suffosion as the mechanisms behind sinkhole formation.Comment: 18 pages, 9 figure
A Generic Checkpoint-Restart Mechanism for Virtual Machines
It is common today to deploy complex software inside a virtual machine (VM).
Snapshots provide rapid deployment, migration between hosts, dependability
(fault tolerance), and security (insulating a guest VM from the host). Yet, for
each virtual machine, the code for snapshots is laboriously developed on a
per-VM basis. This work demonstrates a generic checkpoint-restart mechanism for
virtual machines. The mechanism is based on a plugin on top of an unmodified
user-space checkpoint-restart package, DMTCP. Checkpoint-restart is
demonstrated for three virtual machines: Lguest, user-space QEMU, and KVM/QEMU.
The plugins for Lguest and KVM/QEMU require just 200 lines of code. The Lguest
kernel driver API is augmented by 40 lines of code. DMTCP checkpoints
user-space QEMU without any new code. KVM/QEMU, user-space QEMU, and DMTCP need
no modification. The design benefits from other DMTCP features and plugins.
Experiments demonstrate checkpoint and restart in 0.2 seconds using forked
checkpointing, mmap-based fast-restart, and incremental Btrfs-based snapshots
Cloud Index Tracking: Enabling Predictable Costs in Cloud Spot Markets
Cloud spot markets rent VMs for a variable price that is typically much lower
than the price of on-demand VMs, which makes them attractive for a wide range
of large-scale applications. However, applications that run on spot VMs suffer
from cost uncertainty, since spot prices fluctuate, in part, based on supply,
demand, or both. The difficulty in predicting spot prices affects users and
applications: the former cannot effectively plan their IT expenditures, while
the latter cannot infer the availability and performance of spot VMs, which are
a function of their variable price. To address the problem, we use properties
of cloud infrastructure and workloads to show that prices become more stable
and predictable as they are aggregated together. We leverage this observation
to define an aggregate index price for spot VMs that serves as a reference for
what users should expect to pay. We show that, even when the spot prices for
individual VMs are volatile, the index price remains stable and predictable. We
then introduce cloud index tracking: a migration policy that tracks the index
price to ensure applications running on spot VMs incur a predictable cost by
migrating to a new spot VM if the current VM's price significantly deviates
from the index price.Comment: ACM Symposium on Cloud Computing 201
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