arXiv subjects

Cheng Liu

Publications and source records attributed to Cheng Liu.

At least 181 records · Page 10Linked to original sources

arXiv2020

Structure and magnetism of a new hexagonal polymorph of Ba$_3$Tb(BO$_3$)$_3$ with a quasi-2D triangular lattice

This article reports the structural and magnetic characterisation of a new hexagonal ($P6_3cm$) low-temperature phase of Ba$_3$Tb(BO$_3$)$_3$, isostructural with the heavier lanthanide borates with formula Ba$_3$Ln(BO$_3$)$_3$ (Ln = Dy-Lu). The crystal structure contains a quasi-two-dimensional (2D) triangular lattice of Tb$^{3+}$ ions and is predicted to display unusual magnetic behaviour as a result of the low dimensionality. Magnetic susceptibility $χ(T)$ shows antiferromagnetic interactions ($θ_{CW} = -7.15$ K) and no sharp ordering transition at $T \geq 2$ K, but analysis of $χ'(T)$, isothermal magnetisation and heat capacity suggests the possibility of short-range ordering at $T \approx 10$ K. The material exhibits an inverse magnetocaloric effect at $T < 4$ K.

cond-mat.str-el↗

arXiv2020

Accelerating Generative Neural Networks on Unmodified Deep Learning Processors -- A Software Approach

Generative neural network is a new category of neural networks and it has been widely utilized in applications such as content generation, unsupervised learning, segmentation and pose estimation. It typically involves massive computing-intensive deconvolution operations that cannot be fitted to conventional neural network processors directly. However, prior works mainly investigated specialized hardware architectures through intensive hardware modifications to the existing deep learning processors to accelerate deconvolution together with the convolution. In contrast, this work proposes a novel deconvolution implementation with a software approach and enables fast and efficient deconvolution execution on the legacy deep learning processors. Our proposed method reorganizes the computation of deconvolution and allows the deep learning processors to treat it as the standard convolution by splitting the original deconvolution filters into multiple small filters. Compared to prior acceleration schemes, the implemented acceleration scheme achieves 2.41x - 4.34x performance speedup and reduces the energy consumption by 27.7% - 54.5% on a set of realistic benchmarks. In addition, we also applied the deconvolution computing approach to the off-the-shelf commodity deep learning processors. The performance of deconvolution also exhibits significant performance speedup over prior deconvolution implementations.

cs.LG↗

arXiv2020

EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph Neural Networks

Graph neural networks (GNNs) emerge as a powerful approach to process non-euclidean data structures and have been proved powerful in various application domains such as social networks and e-commerce. While such graph data maintained in real-world systems can be extremely large and sparse, thus employing GNNs to deal with them requires substantial computational and memory overhead, which induces considerable energy and resource cost on CPUs and GPUs. In this work, we present a specialized accelerator architecture, EnGN, to enable high-throughput and energy-efficient processing of large-scale GNNs. The proposed EnGN is designed to accelerate the three key stages of GNN propagation, which is abstracted as common computing patterns shared by typical GNNs. To support the key stages simultaneously, we propose the ring-edge-reduce(RER) dataflow that tames the poor locality of sparsely-and-randomly connected vertices, and the RER PE-array to practice RER dataflow. In addition, we utilize a graph tiling strategy to fit large graphs into EnGN and make good use of the hierarchical on-chip buffers through adaptive computation reordering and tile scheduling. Overall, EnGN achieves performance speedup by 1802.9X, 19.75X, and 2.97X and energy efficiency by 1326.35X, 304.43X, and 6.2X on average compared to CPU, GPU, and a state-of-the-art GCN accelerator HyGCN, respectively.

cs.DC↗

arXiv2020

SquidLab -- a user-friendly program for background subtraction and fitting of magnetization data

We present an open-source program free to download for academic use with full user-friendly graphical interface for performing flexible and robust background subtraction and dipole fitting on magnetization data. For magnetic samples with small moment sizes or sample environments with large or asymmetric magnetic backgrounds, it can become necessary to separate background and sample contributions to each measured raw voltage measurement before fitting the dipole signal to extract magnetic moments. Originally designed for use with pressure cells on a Quantum Design MPMS3 SQUID magnetometer, SquidLab is a modular object-oriented platform implemented in Matlab with a range of importers for different widely-available magnetometer systems (including MPMS, MPMS-XL, MPMS-IQuantum, MPMS3 and S700X models), and has been tested with a broad variety of background and signal types. The software allows background subtraction of baseline signals, signal preprocessing, and performing fits to dipole data using Levenberg-Marquadt non-linear least squares, or a singular value decomposition linear algebra algorithm which excels at picking out noisy or weak dipole signals. A plugin system allows users to easily extend the built-in functionality with their own importers, processes or fitting algorithms. SquidLab can be downloaded, under Academic License, from the University of Warwick depository (wrap.warwick.ac.uk/129665).

physics.data-an↗

arXiv2019

On the Secrecy Performance of Random VLC Networks with Imperfect CSI and Protected Zone

This paper investigates the physical-layer security for a random indoor visible light communication (VLC) network with imperfect channel state information (CSI) and a protected zone. The VLC network consists of three nodes, i.e., a transmitter (Alice), a legitimate receiver (Bob), and an eavesdropper (Eve). Alice is fixed in the center of the ceiling, and the emitted signal at Alice satisfies the non-negativity and the dimmable average optical intensity constraint. Bob and Eve are randomly deployed on the receiver plane. By employing the protected zone and considering the imperfect CSI, the stochastic characteristics of the channel gains for both the main and the eavesdropping channels is first analyzed. After that, the closed-form expressions of the average secrecy capacity and the lower bound of secrecy outage probability are derived, respectively. Finally, Monte-Carlo simulations are provided to verify the accuracy of the derived theoretical expressions. Moreover, the impacts of the nominal optical intensity, the dimming target, the protected zone and the imperfect CSI on secrecy performance are discussed, respectively.

cs.IT↗

arXiv2019

A Survey on Graph Processing Accelerators: Challenges and Opportunities

Graph is a well known data structure to represent the associated relationships in a variety of applications, e.g., data science and machine learning. Despite a wealth of existing efforts on developing graph processing systems for improving the performance and/or energy efficiency on traditional architectures, dedicated hardware solutions, also referred to as graph processing accelerators, are essential and emerging to provide the benefits significantly beyond those pure software solutions can offer. In this paper, we conduct a systematical survey regarding the design and implementation of graph processing accelerator. Specifically, we review the relevant techniques in three core components toward a graph processing accelerator: preprocessing, parallel graph computation and runtime scheduling. We also examine the benchmarks and results in existing studies for evaluating a graph processing accelerator. Interestingly, we find that there is not an absolute winner for all three aspects in graph acceleration due to the diverse characteristics of graph processing and complexity of hardware configurations. We finially present to discuss several challenges in details, and to further explore the opportunities for the future research.

cs.DC↗

arXiv2019

Bulk properties of van-der-Waals hard ferromagnet VI3

We present comprehensive measurements of the structural, magnetic and electronic properties of layered van-der-Waals ferromagnet VI$_3$ down to low temperatures. Despite belonging to a well studied family of transition metal trihalides, this material has received very little attention. We outline, from high-resolution powder x-ray diffraction measurements, a corrected room-temperature crystal structure to that previously proposed and uncover a structural transition at 79 K, also seen in the heat capacity. Magnetization measurements confirm VI$_3$ to be a hard ferromagnet (9.1 kOe coercive field at 2 K) with a high degree of anisotropy, and the pressure dependence of the magnetic properties provide evidence for the two-dimensional nature of the magnetic order. Optical and electrical transport measurements show this material to be an insulator with an optical band gap of 0.67 eV - the previous theoretical predictions of d-band metallicity then lead us to believe VI$_3$ to be a correlated Mott insulator. Our latest band structure calculations support this picture and show good agreement with the experimental data. We suggest VI$_3$ to host great potential in the thriving field of low-dimensional magnetism and functional materials, together with opportunities to study and make use of low-dimensional Mott physics.

cond-mat.str-el↗

arXiv2018

Corrosion of Si, C, and SiC in molten salt

Corrosion of Si, C, and SiC in fluoride salt has been studied by ab initio molecular dynamics. The standard dissolution potential for Si is found to be smaller (easier to corrode) than that of C. The dissolved Si attracts F- ions and forms SiF62-, whereas the dissolved C species forms neutral CF4 molecules. A swapping mechanism is identified for the initial corrosion stage, where Si first comes to the surface and then is dissolved, leaving behind chain- and ring-like C structures. A strategy to suppress SiC corrosion is also discussed based on Be doping, including avoiding Be2C formation.

physics.comp-ph↗

arXiv2018

Physical-layer Security for Indoor Visible Light Communications: Secrecy Capacity Analysis

This paper investigates the physical-layer security for an indoor visible light communication (VLC) network consisting of a transmitter, a legitimate receiver and an eavesdropper. Both the main channel and the wiretapping channel have nonnegative inputs, which are corrupted by additive white Gaussian noises. Considering the illumination requirement and the physical characteristics of lighting source, the input is also constrained in both its average and peak optical intensities. Two scenarios are investigated: one is only with an average optical intensity constraint, and the other is with both average and peak optical intensity constraints. Based on information theory, closed-form expressions of the upper and lower bounds on secrecy capacity for the two scenarios are derived. Numerical results show that the upper and lower bounds on secrecy capacity are tight, which validates the derived closed-form expressions. Moreover, the asymptotic behaviors in the high signal-to-noise ratio (SNR) regime are analyzed from the theoretical aspects. At high SNR, when only considering the average optical intensity constraint, a small performance gap exists between the asymptotic upper and lower bounds on secrecy capacity. When considering both average and peak optical intensity constraints, the asymptotic upper and lower bounds on secrecy capacity coincide with each other. These conclusions are also confirmed by numerical results.

cs.IT↗

arXiv2017

Compensation for the setup instability in ptychographic imaging

The high-frequency vibration of the imaging system degrades the quality of the reconstruction of ptychography by acting as a low-pass filter on ideal diffraction patterns. In this study, we demonstrate that by subtracting the deliberately blurred diffraction patterns from the recorded patterns and adding the properly amplified subtraction to the original data, the high-frequency components lost by the vibration of the setup can be recovered, and thus the image quality can be distinctly improved. Because no prior knowledge regarding the vibrating properties of the imaging system is needed, the proposed method is general and simple and has applications in several research fields.

physics.ins-det↗

arXiv2016

Shrinkage estimation of covariance matrix for portfolio choice with high frequency data

This paper examines the usefulness of high frequency data in estimating the covariance matrix for portfolio choice when the portfolio size is large. A computationally convenient nonlinear shrinkage estimator for the integrated covariance (ICV) matrix of financial assets is developed in two steps. The eigenvectors of the ICV are first constructed from a designed time variation adjusted realized covariance matrix of noise-free log-returns of relatively low frequency data. Then the regularized eigenvalues of the ICV are estimated by quasi-maximum likelihood based on high frequency data. The estimator is always positive definite and its inverse is the estimator of the inverse of ICV. It minimizes the limit of the out-of-sample variance of portfolio returns within the class of rotation-equivalent estimators. It works when the number of underlying assets is larger than the number of time series observations in each asset and when the asset price follows a general stochastic process. Our theoretical results are derived under the assumption that the number of assets (p) and the sample size (n) satisfy p/n \to y >0 as n goes to infty . The advantages of our proposed estimator are demonstrated using real data.

math.ST↗

arXiv2016

A Soft Processor Overlay with Tightly-coupled FPGA Accelerator

FPGA overlays are commonly implemented as coarse-grained reconfigurable architectures with a goal to improve designers' productivity through balancing flexibility and ease of configuration of the underlying fabric. To truly facilitate full application acceleration, it is often necessary to also include a highly efficient processor that integrates and collaborates with the accelerators while maintaining the benefits of being implemented within the same overlay framework. This paper presents an open-source soft processor that is designed to tightly-couple with FPGA accelerators as part of an overlay framework. RISC-V is chosen as the instruction set for its openness and portability, and the soft processor is designed as a 4-stage pipeline to balance resource consumption and performance when implemented on FPGAs. The processor is generically implemented so as to promote design portability and compatibility across different FPGA platforms. Experimental results show that integrated software-hardware applications using the proposed tightly-coupled architecture achieve comparable performance as hardware-only accelerators while the proposed architecture provides additional run-time flexibility. The processor has been synthesized to both low-end and high-performance FPGA families from different vendors, achieving the highest frequency of 268.67MHz and resource consumption comparable to existing RISC-V designs.

cs.AR↗

arXiv2015

Automatic Nested Loop Acceleration on FPGAs Using Soft CGRA Overlay

Offloading compute intensive nested loops to execute on FPGA accelerators have been demonstrated by numerous researchers as an effective performance enhancement technique across numerous application domains. To construct such accelerators with high design productivity, researchers have increasingly turned to the use of overlay architectures as an intermediate generation target built on top of off-the-shelf FPGAs. However, achieving the desired performance-overhead trade-off remains a major productivity challenge as complex application-specific customizations over a large design space covering multiple architectural parameters are needed. In this work, an automatic nested loop acceleration framework utilizing a regular soft coarse-grained reconfigurable array (SCGRA) overlay is presented. Given high-level resource constraints, the framework automatically customizes the overlay architectural design parameters, high-level compilation options as well as communication between the accelerator and the host processor for optimized performance specifically to the given application. In our experiments, at a cost of 10 to 20 minutes additional tools run time, the proposed customization process resulted in up to 5 times additional speedup over a baseline accelerator generated by the same framework without customization. Overall, when compared to the equivalent software running on the host ARM processor alone on the Zedboard, the resulting accelerators achieved up to 10 times speedup.

cs.AR↗

arXiv2015

High performance solar cells based on graphene-GaAs heterostructures

The honeycomb connection of carbon atoms by covalent bonds in a macroscopic two-dimensional scale leads to fascinating graphene and solar cell based on graphene/silicon Schottky diode has been widely studied. For solar cell applications, GaAs is superior to silicon as it has a direct band gap of 1.42 eV and its electron mobility is six times of that of silicon. However, graphene/GaAs solar cell has been rarely explored. Herein, we report graphene/GaAs solar cells with conversion efficiency (Eta) of 10.4% and 15.5% without and with anti-reflection layer on graphene, respectively. The Eta of 15.5% is higher than the state of art efficiency for graphene/Si system (14.5%). Furthermore, our calculation points out Eta of 25.8% can be reached by reasonably optimizing the open circuit voltage, junction ideality factor, resistance of graphene and metal/graphene contact. This research strongly support graphene/GaAs hetero-structure solar cell have great potential for practical applications.

cond-mat.mes-hall↗

arXiv2014

Hybrid model of GeV-TeV gamma ray emission from Galactic Center

The observations of high energy $γ$-ray emission from the Galactic center (GC) by HESS, and recently by Fermi, suggest the cosmic ray acceleration in the GC and possibly around the supermassive black hole. In this work we propose a lepton-hadron hybrid model to explain simultaneously the GeV-TeV $γ$-ray emission. Both electrons and hadronic cosmic rays were accelerated during the past activity of the GC. Then these particles would diffuse outwards and interact with the interstellar gas and background radiation field. The collisions between hadronic cosmic rays with gas is responsible to the TeV $γ$-ray emission detected by HESS. With fast cooling in the strong radiation field, the electrons would cool down and radiate GeV photons through inverse Compton scattering off the soft background photons. This scenario provides a natural explanation of the observed GeV-TeV spectral shape of $γ$-rays.

astro-ph.HE↗

arXiv2014

Monetary Cost Optimizations for Hosting Workflow-as-a-Service in IaaS Clouds

Recently, we have witnessed workflows from science and other data-intensive applications emerging on Infrastructure-asa-Service (IaaS) clouds, and many workflow service providers offering workflow as a service (WaaS). The major concern of WaaS providers is to minimize the monetary cost of executing workflows in the IaaS cloud. While there have been previous studies on this concern, most of them assume static task execution time and static pricing scheme, and have the QoS notion of satisfying a deterministic deadline. However, cloud environment is dynamic, with performance dynamics caused by the interference from concurrent executions and price dynamics like spot prices offered by Amazon EC2. Therefore, we argue that WaaS providers should have the notion of offering probabilistic performance guarantees for individual workflows on IaaS clouds. We develop a probabilistic scheduling framework called Dyna to minimize the monetary cost while offering probabilistic deadline guarantees. The framework includes an A*-based instance configuration method for performance dynamics, and a hybrid instance configuration refinement for utilizing spot instances. Experimental results with three real-world scientific workflow applications on Amazon EC2 demonstrate (1) the accuracy of our framework on satisfying the probabilistic deadline guarantees required by the users; (2) the effectiveness of our framework on reducing monetary cost in comparison with the existing approaches.

cs.DC↗

arXiv2013

On the Galactic Center Being the Main Source of Galactic Cosmic Rays as Evidenced by Recent Cosmic Ray and Gamma Ray Observations

We revisit the idea that the Galactic center (GC) is the dominant source of Galactic cosmic rays (GCRs), based on a series of new observational evidence. A unified model is proposed to explain the new phenomena of GCRs and $γ$-rays simultaneously. The GCRs are thought to be accelerated during past activities of the GC. The pair production process of GCRs in the strong radiation field due to the GC activity is responsible for the knee structure of the cosmic ray spectra. A f raction of $e^+e^-$ produced by pair production interactions, can be reaccelerated in the induced bipolar jets and be transported into the halo, leaving the Fermi $γ$-ray bubbles and WMAP microwave haze as the remnant signal. Finally, the CRs diffuse in the bulge could further interact with the interstellar medium to produce low energy $e^+e^-$. After cooling down, these positrons may annihilate to produce the 511 keV line emission as discovered by INTEGRAL.

astro-ph.HE↗

arXiv2012

Anisotropy as a Probe of the Galactic Cosmic Ray Propagation and the Galactic Halo Magnetic Field

The anisotropy of cosmic rays (CRs) in the solar vicinity is generally at- tributed to the CR streaming due to the discrete distribution of CR sources or local magnetic field modulation. Recently, the two dimensional large scale CR anisotropy has been measured by many experiments in TeV-PeV energy range in both hemispheres. The tail-in excess along the tangential direction of the local spiral arm and the loss cone deficit pointing to the north Galactic pole direction agree with what have been obtained in tens to hundreds of GeV. The persistence of the two large scale anisotropy structures in such a wide range of energy suggests that the anisotropy might be due to a global streaming of the Galactic CRs (GCRs). This work tries to extend the observed CR anisotropy picture from solar system to the whole galaxy. In such a case, we can find a new interesting signature, a loop of GCR streaming, of the GCR propagation. We further calculate the overall GCR streaming induced magnetic field, and find a qualitative consistence with the observed structure of the halo magnetic field.

astro-ph.GA↗