3,647 research outputs found
Asynchronous Graph Pattern Matching on Multiprocessor Systems
Pattern matching on large graphs is the foundation for a variety of
application domains. Strict latency requirements and continuously increasing
graph sizes demand the usage of highly parallel in-memory graph processing
engines that need to consider non-uniform memory access (NUMA) and concurrency
issues to scale up on modern multiprocessor systems. To tackle these aspects,
graph partitioning becomes increasingly important. Hence, we present a
technique to process graph pattern matching on NUMA systems in this paper. As a
scalable pattern matching processing infrastructure, we leverage a
data-oriented architecture that preserves data locality and minimizes
concurrency-related bottlenecks on NUMA systems. We show in detail, how graph
pattern matching can be asynchronously processed on a multiprocessor system.Comment: 14 Pages, Extended version for ADBIS 201
GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA
This work presents an updated and extended guide on methods of a proper
acceleration of the Monte Carlo integration of stochastic differential
equations with the commonly available NVIDIA Graphics Processing Units using
the CUDA programming environment. We outline the general aspects of the
scientific computing on graphics cards and demonstrate them with two models of
a well known phenomenon of the noise induced transport of Brownian motors in
periodic structures. As a source of fluctuations in the considered systems we
selected the three most commonly occurring noises: the Gaussian white noise,
the white Poissonian noise and the dichotomous process also known as a random
telegraph signal. The detailed discussion on various aspects of the applied
numerical schemes is also presented. The measured speedup can be of the
astonishing order of about 3000 when compared to a typical CPU. This number
significantly expands the range of problems solvable by use of stochastic
simulations, allowing even an interactive research in some cases.Comment: 21 pages, 5 figures; Comput. Phys. Commun., accepted, 201
Exploring Task Mappings on Heterogeneous MPSoCs using a Bias-Elitist Genetic Algorithm
Exploration of task mappings plays a crucial role in achieving high
performance in heterogeneous multi-processor system-on-chip (MPSoC) platforms.
The problem of optimally mapping a set of tasks onto a set of given
heterogeneous processors for maximal throughput has been known, in general, to
be NP-complete. The problem is further exacerbated when multiple applications
(i.e., bigger task sets) and the communication between tasks are also
considered. Previous research has shown that Genetic Algorithms (GA) typically
are a good choice to solve this problem when the solution space is relatively
small. However, when the size of the problem space increases, classic genetic
algorithms still suffer from the problem of long evolution times. To address
this problem, this paper proposes a novel bias-elitist genetic algorithm that
is guided by domain-specific heuristics to speed up the evolution process.
Experimental results reveal that our proposed algorithm is able to handle large
scale task mapping problems and produces high-quality mapping solutions in only
a short time period.Comment: 9 pages, 11 figures, uses algorithm2e.st
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Methods for Performance Evaluation of Parallel Computer Systems
Although parallel computers have existed for many years, recently there has been a surge of academic, industrial and governmental interest in parallel computing. Commercially manufactured parallel computers have started to become available. Many new experimental parallel architectures are reported in the literature every year. Software for many types of applications, from scientific number crunching to artificial intelligence, is being written to run on parallel machines. Performance is an essential consideration both in the design of new systems and the deployment of existing systems. Users of computers wish to utilize their hardware and software systems as efficiently as possible. Over the years, a field known as computer performance evaluation has arisen to address the problem of quantifying and predicting computer performance. Methods exist that can determine how efficiently a system's resources are being used. These can help track down the probable causes of performance problems
System configuration and executive requirements specifications for reusable shuttle and space station/base
System configuration and executive requirements specifications for reusable shuttle and space station/bas
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