343,599 research outputs found
Explicit linear kernels via dynamic programming
Several algorithmic meta-theorems on kernelization have appeared in the last
years, starting with the result of Bodlaender et al. [FOCS 2009] on graphs of
bounded genus, then generalized by Fomin et al. [SODA 2010] to graphs excluding
a fixed minor, and by Kim et al. [ICALP 2013] to graphs excluding a fixed
topological minor. Typically, these results guarantee the existence of linear
or polynomial kernels on sparse graph classes for problems satisfying some
generic conditions but, mainly due to their generality, it is not clear how to
derive from them constructive kernels with explicit constants. In this paper we
make a step toward a fully constructive meta-kernelization theory on sparse
graphs. Our approach is based on a more explicit protrusion replacement
machinery that, instead of expressibility in CMSO logic, uses dynamic
programming, which allows us to find an explicit upper bound on the size of the
derived kernels. We demonstrate the usefulness of our techniques by providing
the first explicit linear kernels for -Dominating Set and -Scattered Set
on apex-minor-free graphs, and for Planar-\mathcal{F}-Deletion on graphs
excluding a fixed (topological) minor in the case where all the graphs in
\mathcal{F} are connected.Comment: 32 page
Load-Sharing Policies in Parallel Simulation of Agent-Based Demographic Models
Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs’ interactions.
We present a performance study conducted on a synthetic test case, representative of a class of agent-based models
Hybrid-parallel sparse matrix-vector multiplication with explicit communication overlap on current multicore-based systems
We evaluate optimized parallel sparse matrix-vector operations for several
representative application areas on widespread multicore-based cluster
configurations. First the single-socket baseline performance is analyzed and
modeled with respect to basic architectural properties of standard multicore
chips. Beyond the single node, the performance of parallel sparse matrix-vector
operations is often limited by communication overhead. Starting from the
observation that nonblocking MPI is not able to hide communication cost using
standard MPI implementations, we demonstrate that explicit overlap of
communication and computation can be achieved by using a dedicated
communication thread, which may run on a virtual core. Moreover we identify
performance benefits of hybrid MPI/OpenMP programming due to improved load
balancing even without explicit communication overlap. We compare performance
results for pure MPI, the widely used "vector-like" hybrid programming
strategies, and explicit overlap on a modern multicore-based cluster and a Cray
XE6 system.Comment: 16 pages, 10 figure
Explicit Parallel Programming: System Description
The implementation of the Explicit Parallel Programming (EPP) system is described. EPP is a prototype implementation of a language for writing parallel programs for shared memory multiprocessors. EPP may be viewed as a coordination language, since it is used to define the sequencing or ordering of various tasks, while the tasks themselves are defined in some other compilable language. The two main components of the EPP system---a compiler and an executive---are described in this report. An appendix is included which contains the grammar defining the EPP language as well as templates used by the compiler in code generation
Verification theorem and construction of epsilon-optimal controls for control of abstract evolution equations
We study several aspects of the dynamic programming approach to optimal control of abstract evolution equations, including a class of semilinear partial differential equations. We introduce and prove a verification theorem which provides a sufficient condition for optimality. Moreover we prove sub- and superoptimality principles of dynamic programming and give an explicit construction of -optimal controls.optimal control of PDE; verification theorem; dynamic programming; -optimal controls; Hamilton-Jacobi-Bellman equations
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