Accelerating Transactional Memory by Exploiting Platform Specificity

Transactional Memory (TM) is one of the most promising alternatives to lock-based concurrency, but there still remain obstacles that keep TM from being utilized in the real world. Performance, in terms of high scalability and low latency, is always one of the most important keys to general purpose usage. While most of the research in this area focuses on improving a specific single TM implementation and some default platform (a certain operating system, compiler and/or processor), little has been conducted on improving performance more generally, and across platforms.We found that by utilizing platform specificity, we could gain tremendous performance improvement and avoid unnecessary costs due to false assumptions of platform properties, on not only a single TM implementation, but many. In this dissertation, we will present our findings in four sections: 1) we discover and quantify hidden costs from inappropriate compiler instrumentations, and provide sug- gestions and solutions; 2) we boost a set of mainstream timestamp-based TM implementations with the x86-specific hardware cycle counter; 3) we explore compiler opportunities to reduce the transaction abort rate, by reordering read-modify-write operations — the whole technique can be applied to all TM implementations, and could be more effective with some help from compilers; and 4) we coordinate the state-of-the-art Intel Haswell TSX hardware TM with a software TM “Cohorts”, and develop a safe and flexible Hybrid TM, “HyCo”, to be our final performance boost in this dissertation.The impact of our research extends beyond Transactional Memory, to broad areas of concurrent programming. Some of our solutions and discussions, such as the synchronization between accesses of the hardware cycle counter and memory loads and stores, can be utilized to boost concurrent data structures and many timestamp-based systems and applications. Others, such as discussions of compiler instrumentation costs and reordering opportunities, provide additional insights to compiler designers. Our findings show that platform specificity must be taken into consideration to achieve peak performance

On the Relationship Between Delaying Operators and Language-Level Semantics *

Abstract The notion of "atomicity" implies that it is safe to rearrange memory accesses within a transaction. In this paper, we sketch a mechanism for postponing contentious transactional operations until commit time, where they become impervious to aborts. We then contemplate the interplay between such a mechanism and languagelevel semantics. Though preliminary, our algorithms and recommendations should prove useful to designers of transactional compilers and languages

Understanding tourists’ protection motivations when faced with overseas travel after COVID-19: The case of South Koreans travelling to China

COVID-19, as a global public health crisis, represents a major concern for international tourism. This study aims to explore the influence of COVID-19 on international tourists’ self-protection motivations, and the role of mass media in this process. Protection motivation theory (PMT) was adopted as the guiding theoretical framework, and mass media coverage was integrated into the model as a moderating construct. Online survey data were collected to explain and predict the protection motivation of potential tourists from South Korea travelling to China under the threat of the COVID-19 pandemic. Structural equation modelling (SEM) was performed to examine the significant factors that could evoke self-protection motivation. Results indicate that respondents’ perceptions of the severity of the pandemic and self-efficacy as a coping strategy have the greatest impact on self-protection motivations. Furthermore, positive mass media coverage moderates the relationship between self-efficacy and self-protection motivation, while negative mass media coverage moderates the relationship between vulnerability and self-protection motivation. Theoretical and practical implications on how to encourage travel in a post-pandemic period are discussed

Right ventricle segmentation from cardiac MRI: A collation study

© 2014 Elsevier B.V. Magnetic Resonance Imaging (MRI), a reference examination for cardiac morphology and function in humans, allows to image the cardiac right ventricle (RV) with high spatial resolution. The segmentation of the RV is a difficult task due to the variable shape of the RV and its ill-defined borders in these images. The aim of this paper is to evaluate several RV segmentation algorithms on common data. More precisely, we report here the results of the Right Ventricle Segmentation Challenge (RVSC), concretized during the MICCAI\u2712 Conference with an on-site competition. Seven automated and semi-automated methods have been considered, along them three atlas-based methods, two prior based methods, and two prior-free, image-driven methods that make use of cardiac motion. The obtained contours were compared against a manual tracing by an expert cardiac radiologist, taken as a reference, using Dice metric and Hausdorff distance. We herein describe the cardiac data composed of 48 patients, the evaluation protocol and the results. Best results show that an average 80% Dice accuracy and a 1. cm Hausdorff distance can be expected from semi-automated algorithms for this challenging task on the datasets, and that an automated algorithm can reach similar performance, at the expense of a high computational burden. Data are now publicly available and the website remains open for new submissions (http://www.litislab.eu/rvsc/)