Common envelope evolution on a moving mesh
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Explore the source record for details and available documents.
Abstract not provided.
OpenSHMEM is an effort to standardize the well-known SHMEM parallel programming library. The project aims to produce an open-source and portable SHMEM API and is led by ORNL and UH. In this paper, we optimize the current OpenSHMEM reference implementa- tion, based on GASNet, to achieve higher performance characteristics. To achieve these desired performance characteristics, we have redesigned an important component of the OpenSHMEM implementation, the network layer, to leverage a low-level communication library designed for imple- menting parallel programming models called UCCS. In particular, UCCS provides an interface and semantics such as native atomic operations and remote memory operations to better support PGAS programming models, including OpenSHMEM. Through the use of microbenchmarks, we evaluate this new OpenSHMEM implementation on various network metrics, including the latency of point-to-point and collective operations. Furthermore, we compare the performance of our OpenSHMEM imple- mentation with the state-of-the-art SGI SHMEM. Our results show that the atomic operations of our OpenSHMEM implementation outperform SGI s SHMEM implementation by 3%. Its RMA operations outperform both SGI s SHMEM and the original OpenSHMEM reference implemen- tation by as much as 18% and 12% for gets, and as much as 83% and 53% for puts.
Abstract not provided.
Atomic physics and hadronic physics are both governed by the Yang Mills gauge theory Lagrangian; in fact, Abelian quantum electrodynamics can be regarded as the zero-color limit of quantum chromodynamics. I review a number of areas where the techniques of atomic physics can provide important insight into hadronic eigenstates in QCD. For example, the Dirac-Coulomb equation, which predicts the spectroscopy and structure of hydrogenic atoms, has an analog in hadron physics in the form of frame-independent light-front relativistic equations of motion consistent with light-front holography which give a remarkable first approximation to the spectroscopy, dynamics, and structure of light hadrons. The production of antihydrogen in flight can provide important insight into the dynamics of hadron production in QCD at the amplitude level. The renormalization scale for the running coupling is unambiguously set in QED; an analogous procedure sets the renormalization scales in QCD, leading to scheme-independent scale-fixed predictions. Conversely, many techniques which have been developed for hadron physics, such as scaling laws, evolution equations, the quark-interchange process and light-front quantization have important applicants for atomic physics and photon science, especially in the relativistic domain.
Developers and security analysts have been using static analysis for a long time to analyze programs for defects and vulnerabilities with some success. Generally a static analysis tool is run on the source code for a given program, flagging areas of code that need to be further inspected by a human analyst. These areas may be obvious bugs like potential bu er over flows, information leakage flaws, or the use of uninitialized variables. These tools tend to work fairly well - every year they find many important bugs. These tools are more impressive considering the fact that they only examine the source code, which may be very complex. Now consider the amount of data available that these tools do not analyze. There are many pieces of information that would prove invaluable for finding bugs in code, things such as a history of bug reports, a history of all changes to the code, information about committers, etc. By leveraging all this additional data, it is possible to nd more bugs with less user interaction, as well as track useful metrics such as number and type of defects injected by committer. This dissertation provides a method for leveraging development metadata to find bugs that would otherwise be difficult to find using standard static analysis tools. We showcase two case studies that demonstrate the ability to find 0day vulnerabilities in large and small software projects by finding new vulnerabilities in the cpython and Roundup open source projects.