Nature of System Calls in CPU-centric Computing Paradigm

Modern operating systems are typically POSIX-compliant with major system calls specified decades ago. The next generation of non-volatile memory (NVM) technologies raise concerns about the efficiency of the traditional POSIX-based systems. As one step toward building high performance NVM systems, we explore the potential dependencies between system call performance and major hardware components (e.g., CPU, memory, storage) under typical user cases (e.g., software compilation, installation, web browser, office suite) in this paper. We build histograms for the most frequent and time-consuming system calls with the goal to understand the nature of distribution on different platforms. We find that there is a strong dependency between the system call performance and the CPU architecture. On the other hand, the type of persistent storage plays a less important role in affecting the performance

Family of attainable geometric quantum speed limits

We propose a quantum state distance and develop a family of geometrical quantum speed limits (QSLs) for open and closed systems. The QSL time includes an alternative function by which we derive three QSL times with particularly chosen functions. It indicates that two QSL times are exactly the ones presented in Ref. [1] and [2], respectively, and the third one can provide a unified QSL time for both open and closed systems. The three QSL times are attainable for any given initial state in the sense that there exists a dynamics driving the initial state to evolve along the geodesic. We numerically compare the tightness of the three QSL times, which typically promises a tighter QSL time if optimizing the alternative function

Communicative Message Passing for Inductive Relation Reasoning

Relation prediction for knowledge graphs aims at predicting missing relationships between entities. Despite the importance of inductive relation prediction, most previous works are limited to a transductive setting and cannot process previously unseen entities. The recent proposed subgraph-based relation reasoning models provided alternatives to predict links from the subgraph structure surrounding a candidate triplet inductively. However, we observe that these methods often neglect the directed nature of the extracted subgraph and weaken the role of relation information in the subgraph modeling. As a result, they fail to effectively handle the asymmetric/anti-symmetric triplets and produce insufficient embeddings for the target triplets. To this end, we introduce a \textbf{C}\textbf{o}mmunicative \textbf{M}essage \textbf{P}assing neural network for \textbf{I}nductive re\textbf{L}ation r\textbf{E}asoning, \textbf{CoMPILE}, that reasons over local directed subgraph structures and has a vigorous inductive bias to process entity-independent semantic relations. In contrast to existing models, CoMPILE strengthens the message interactions between edges and entitles through a communicative kernel and enables a sufficient flow of relation information. Moreover, we demonstrate that CoMPILE can naturally handle asymmetric/anti-symmetric relations without the need for explosively increasing the number of model parameters by extracting the directed enclosing subgraphs. Extensive experiments show substantial performance gains in comparison to state-of-the-art methods on commonly used benchmark datasets with variant inductive settings.Comment: Accepted by AAAI-202

Understanding Persistent-Memory Related Issues in the Linux Kernel

Persistent memory (PM) technologies have inspired a wide range of PM-based system optimizations. However, building correct PM-based systems is difficult due to the unique characteristics of PM hardware. To better understand the challenges as well as the opportunities to address them, this paper presents a comprehensive study of PM-related issues in the Linux kernel. By analyzing 1,553 PM-related kernel patches in-depth and conducting experiments on reproducibility and tool extension, we derive multiple insights in terms of PM patch categories, PM bug patterns, consequences, fix strategies, triggering conditions, and remedy solutions. We hope our results could contribute to the development of robust PM-based storage systemsComment: ACM TRANSACTIONS ON STORAGE(TOS'23

Needle δ13C and mobile carbohydrates in Pinus koraiensis in relation to decreased temperature and increased moisture along an elevational gradient in NE China

A tree's crown interacts with atmospheric variables such as CO2, temperature, and humidity. Physioecology of leaves/needles (e.g. δ13C, mobile carbohydrates, and nitrogen) is, therefore, strongly affected by microclimate in and surrounding a tree crown. To understand the physiological responses of leaves to changes in air temperature and moisture, we measured δ13C, soluble sugars, starch, and total nitrogen (N) concentrations in current year and 1-yr-old needles of Pinus koraiensis trees, and compared the growing season air temperature and relative humidity within and outside P. koraiensis crowns along an elevational gradient from 760 to 1,420ma.s.l. on Changbai Mountain, NE China. Our results indicated that needle N and mobile carbohydrates concentrations, as well as needle δ13C values changed continuously with increasing elevation, corresponding to a continuous decrease in air temperature and an increase in relative humidity. Needle carbon and nitrogen status is highly significantly negatively correlated with temperature, but positively correlated with relative humidity. These results indicate that increases in air temperature in combination with decreases in relative humidity may result in lower levels of N and mobile carbohydrates in P. koraiensis trees, suggesting that future climate changes such as global warming and changes in precipitation patterns will directly influence the N and carbon physiology at P. koraiensis individual level, and indirectly affect the competitive ability, species composition, productivity and functioning at the stand and ecosystem level in NE China. Due to the relatively limited range of the transect (760-1,420m) studied, further research is needed to explain whether the present results are applicable to scales across large elevational gradient

A symmetric integrated radial basis function method for solving differential equations

In this article, integrated radial basis functions (IRBFs) are used for Hermite interpolation in the solution of differential equations, resulting in a new meshless symmetric RBF method. Both global and local approximation-based schemes are derived. For the latter, the focus is on the construction of compact approximation stencils, where a sparse system matrix and a high-order accuracy can be achieved together. Cartesian-grid-based stencils are possible for problems defined on nonrectangular domains. Furthermore, the effects of the RBF width on the solution accuracy for a given grid size are fully explored with a reasonable computational cost. The proposed schemes are numerically verified in some elliptic boundary-value problems governed by the Poisson and convection-diffusion equations. High levels of the solution accuracy are obtained using relatively coarse discretisations