9,292 research outputs found
On a multiscale strategy and its optimization for the simulation of combined delamination and buckling
This paper investigates a computational strategy for studying the
interactions between multiple through-the-width delaminations and global or
local buckling in composite laminates taking into account possible contact
between the delaminated surfaces. In order to achieve an accurate prediction of
the quasi-static response, a very refined discretization of the structure is
required, leading to the resolution of very large and highly nonlinear
numerical problems. In this paper, a nonlinear finite element formulation along
with a parallel iterative scheme based on a multiscale domain decomposition are
used for the computation of 3D mesoscale models. Previous works by the authors
already dealt with the simulation of multiscale delamination assuming small
perturbations. This paper presents the formulation used to include geometric
nonlinearities into this existing multiscale framework and discusses the
adaptations that need to be made to the iterative process in order to ensure
the rapid convergence and the scalability of the method in the presence of
buckling and delamination. These various adaptations are illustrated by
simulations involving large numbers of DOFs
PYDAC: A DISTRIBUTED RUNTIME SYSTEM AND PROGRAMMING MODEL FOR A HETEROGENEOUS MANY-CORE ARCHITECTURE
Heterogeneous many-core architectures that consist of big, fast cores and small, energy-efficient cores are very promising for future high-performance computing (HPC) systems. These architectures offer a good balance between single-threaded perfor- mance and multithreaded throughput. Such systems impose challenges on the design of programming model and runtime system. Specifically, these challenges include (a) how to fully utilize the chip’s performance, (b) how to manage heterogeneous, un- reliable hardware resources, and (c) how to generate and manage a large amount of parallel tasks.
This dissertation proposes and evaluates a Python-based programming framework called PyDac. PyDac supports a two-level programming model. At the high level, a programmer creates a very large number of tasks, using the divide-and-conquer strategy. At the low level, tasks are written in imperative programming style. The runtime system seamlessly manages the parallel tasks, system resilience, and inter- task communication with architecture support. PyDac has been implemented on both an field-programmable gate array (FPGA) emulation of an unconventional het- erogeneous architecture and a conventional multicore microprocessor. To evaluate the performance, resilience, and programmability of the proposed system, several micro-benchmarks were developed. We found that (a) the PyDac abstracts away task communication and achieves programmability, (b) the micro-benchmarks are scalable on the hardware prototype, but (predictably) serial operation limits some micro-benchmarks, and (c) the degree of protection versus speed could be varied in redundant threading that is transparent to programmers
Automatic Music Composition using Answer Set Programming
Music composition used to be a pen and paper activity. These these days music
is often composed with the aid of computer software, even to the point where
the computer compose parts of the score autonomously. The composition of most
styles of music is governed by rules. We show that by approaching the
automation, analysis and verification of composition as a knowledge
representation task and formalising these rules in a suitable logical language,
powerful and expressive intelligent composition tools can be easily built. This
application paper describes the use of answer set programming to construct an
automated system, named ANTON, that can compose melodic, harmonic and rhythmic
music, diagnose errors in human compositions and serve as a computer-aided
composition tool. The combination of harmonic, rhythmic and melodic composition
in a single framework makes ANTON unique in the growing area of algorithmic
composition. With near real-time composition, ANTON reaches the point where it
can not only be used as a component in an interactive composition tool but also
has the potential for live performances and concerts or automatically generated
background music in a variety of applications. With the use of a fully
declarative language and an "off-the-shelf" reasoning engine, ANTON provides
the human composer a tool which is significantly simpler, more compact and more
versatile than other existing systems. This paper has been accepted for
publication in Theory and Practice of Logic Programming (TPLP).Comment: 31 pages, 10 figures. Extended version of our ICLP2008 paper.
Formatted following TPLP guideline
Instruction-Level Execution Migration
We introduce the Execution Migration Machine (EM²), a novel data-centric multicore memory system architecture based on computation migration. Unlike traditional distributed memory multicores, which rely on complex cache coherence protocols to move the data to the core where the computation is taking place, our scheme always moves the computation to the core where the data resides. By doing away with the cache coherence protocol, we are able to boost the effectiveness of per-core caches while drastically reducing hardware complexity. To evaluate the potential of EM² architectures, we developed a series of PIN/Graphite-based models of an EM² multicore with 64 x86 cores and, under some simplifying assumptions (a timing model restricted to data memory performance, no instruction cache modeling, high-bandwidth fixed-latency interconnect allowing concurrent migrations), compared them against corresponding directory-based cache-coherent architecture models. We justify our assumptions and show that our conclusions are valid even if our assumptions are removed. Experimental results on a range of SPLASH-2 and PARSEC benchmarks indicate that EM2 can significantly improve per-core cache performance, decreasing overall miss rates by as much as 84% and reducing average memory latency by up to 58%
Power system applications of fiber optics
Power system applications of optical systems, primarily using fiber optics, are reviewed. The first section reviews fibers as components of communication systems. The second section deals with fiber sensors for power systems, reviewing the many ways light sources and fibers can be combined to make measurements. Methods of measuring electric field gradient are discussed. Optical data processing is the subject of the third section, which begins by reviewing some widely different examples and concludes by outlining some potential applications in power systems: fault location in transformers, optical switching for light fired thyristors and fault detection based on the inherent symmetry of most power apparatus. The fourth and final section is concerned with using optical fibers to transmit power to electric equipment in a high voltage situation, potentially replacing expensive high voltage low power transformers. JPL has designed small photodiodes specifically for this purpose, and fabricated and tested several samples. This work is described
Providing structural modules with self-integrity monitoring
With the advent of complex space structures (i.e., U.S. Space Station), the need for methods for remotely detecting structural damage will become greater. Some of these structures will have hundreds of individual structural elements (i.e., strut members). Should some of them become damaged, it could be virtually impossible to detect it using visual or similar inspection techniques. The damage of only a few individual members may or may not be a serious problem. However, should a significant number of the members be damaged, a significant problem could be created. The implementation of an appropriate remote damage detection scheme would greatly reduce the likelihood of a serious problem related to structural damage ever occurring. This report presents the results of the research conducted on remote structural damage detection approaches and the related mathematical algorithms. The research was conducted for the Small Business Innovation and Research (SBIR) Phase 2 National Aeronautics and Space Administration (NASA) Contract NAS7-961
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