303 Hits in 3.3 sec

Software Engineering for Serverless Computing [article]

Jinfeng Wen, Zhenpeng Chen, Xuanzhe Liu
2022 arXiv   pre-print
Serverless computing is an emerging cloud computing paradigm that has been applied to various domains, including machine learning, scientific computing, video processing, etc. To develop serverless computing-based software applications (a.k.a., serverless applications), developers follow the new cloud-based software architecture, where they develop event-driven applications without the need for complex and error-prone server management. The great demand for developing serverless applications
more » ... es unique challenges to software developers. However, Software Engineering (SE) has not yet wholeheartedly tackled these challenges. In this paper, we outline a vision for how SE can facilitate the development of serverless applications and call for actions by the SE research community to reify this vision. Specifically, we discuss possible directions in which researchers and cloud providers can facilitate serverless computing from the SE perspective, including configuration management, data security, application migration, performance, testing and debugging, etc.
arXiv:2207.13263v1 fatcat:vevigvrgunhbxo5x4z7gw4gg3e

The Spatiotemporal Evolution of Temperature During Transient Heating of Nanoparticle Arrays [article]

Chen Xie, Zhenpeng Qin
2021 arXiv   pre-print
Nanoparticle (NP) are promising agents to absorb external energy excitation and generate heat. Cluster of NPs or NP array heating have found essential roles for biomedical applications, diagnostic techniques and chemical catalysis. Various studies have shed light on the heat transfer of nanostructures and greatly advanced our understanding of NP array heating. However, there is a lack of analytical tools and dimensionless parameters to describe the transient heating of NP arrays. Here we
more » ... rate a comprehensive analysis of the transient NP array heating. Firstly, we developed analytical solution for the NP array heating and provide a useful mathematical description of the spatial-temporal evolution of temperature for 2D, 3D and spherical NP array heating. Based on this, we proposed the idea of thermal resolution that quantifies the relationship between minimal heating time, NP array size, energy intensity and target temperature. Lastly, we define a dimensionless parameter that characterize the transition from confined heating to delocalized heating. This study advances the in-depth understanding of nanomaterials heating and provides guidance for rationally designing innovative approaches for NP array heating.
arXiv:2109.01215v1 fatcat:nr7glr3iy5felb3x2wdpjhdhey

Computational investigation of protein photoinactivation by molecular hyperthermia [article]

Peiyuan Kang, Chen Xie, Oumar Fall, Jaona Randrianalisoa, Zhenpeng Qin
2020 bioRxiv   pre-print
Chen et al. estimated the thermal conductivity for 3 nm AuNS to be 24.14 W m -1 K -1 , an order magnitude lower than bulk gold.  ... 
doi:10.1101/2020.07.22.216069 fatcat:7dq743hihnayrlvr2zmhbt4vfy

Sample preparation

Yi Chen, Zhenpeng Guo, Xiaoyu Wang, Changgui Qiu
2008 Journal of Chromatography A  
"Dynamic pH junction", first mentioned by Britz-Mckibbin and Chen [388] , makes analytes focus at the moving boundary of H + /OH − .  ... 
doi:10.1016/j.chroma.2007.10.026 pmid:17991475 fatcat:dmzo2n53xze5jn2jdh25ybh6tm

Learning point embedding for 3D data processing [article]

Zhenpeng Chen, Yuan li
2021 arXiv   pre-print
Among 2D convolutional networks on point clouds, point-based approaches consume point clouds of fixed size directly. By analysis of PointNet, a pioneer in introducing deep learning into point sets, we reveal that current point-based methods are essentially spatial relationship processing networks. In this paper, we take a different approach. Our architecture, named PE-Net, learns the representation of point clouds in high-dimensional space, and encodes the unordered input points to feature
more » ... rs, which standard 2D CNNs can be applied to. The recommended network can adapt to changes in the number of input points which is the limit of current methods. Experiments show that in the tasks of classification and part segmentation, PE-Net achieves the state-of-the-art performance in multiple challenging datasets, such as ModelNet and ShapeNetPart.
arXiv:2107.08565v2 fatcat:xzbuezc6jrabfddfncixtqziuy

LambdaLite: Application-Level Optimization for Cold Start Latency in Serverless Computing [article]

Jinfeng Wen, Zhenpeng Chen, Ding Li, Junkai Chen, Yi Liu, Haoyu Wang, Xin Jin, Xuanzhe Liu
2022 arXiv   pre-print
Serverless computing is an emerging cloud computing paradigm that frees developers from server management. However, existing studies report that software applications developed in serverless fashion (named serverless applications) severely suffer from cold start latency. We propose an application-level performance optimization approach called LambdaLite, for accelerating the cold start for serverless applications. We first conduct a measurement study to investigate the possible root cause of
more » ... cold start problem and find that application code loading latency is the dominant overhead. Therefore, loading only indispensable code from serverless applications can be an adequate solution. Based on this insight, we identify code related to application functionalities by constructing the function-level call graph, and separate other code (optional code) from the serverless application. The separated optional code can be loaded on demand to avoid the inaccurate identification of indispensable code causing application failure. In practice, LambdaLite can be seamlessly deployed on existing serverless platforms without the need to modify the underlying OSes or hypervisors, nor introduce additional manual efforts to developers. Evaluation results on 15 real-world serverless applications show that our approach can significantly reduce the application code loading latency (up to 78.95%, on average 28.78%), thereby reducing the cold start latency. As a result, the total response latency of serverless applications can be decreased by up to 42.05% (on average 19.21%). Compared with the state-of-the-art, our approach achieves a 21.25X improvement on the total response latency of serverless applications.
arXiv:2207.08175v1 fatcat:squhc5us4naqlmsxvbhv5nfa7i

Primary Control Method of Wireless Charging System Based on Load Characteristics

Guodong Chen, Chao Rao, Yue Sun, Zhenxin Chen, Chunsen Tang, Zhenpeng Zhang
2019 Energies  
Aiming at the output control issues of a lithium ion battery wireless charging system, a primary side control method based on load characteristic identification is proposed. The primary side impedance is calculated by detecting the effective value of the primary side voltage and current, and the mapping relationship between the equivalent load and the primary side impedance is established based on the AC impedance model. Using this mapping relation, the output of the secondary side can be
more » ... ted indirectly by controlling the input voltage of the inverter. Compared with the traditional control methods, the proposed control method not only eliminates the communication requirement between the primary side and secondary side, but also simplifies the hardware circuit design, reduces the complexity of the control circuit and also reduces the volume and cost of the system. In the paper, the impedance characteristics of the lithium ion battery at constant current and constant voltage stage are analyzed. The principle of the primary side control method is expounded and the realization method is given. The feasibility of the proposed control method is verified by simulation and experiment.
doi:10.3390/en12071269 fatcat:mii7qpu4zzf7xjno3wg4h2nalu

Experimental Realization of Two-Dimensional Buckled Lieb lattice [article]

Haifeng Feng, Chen Liu, Si Zhou, Nan Gao, Qian Gao, Jincheng Zhuang, Xun Xu, Zhenpeng Hu, Jiaou Wang, Lan Chen, Jijun Zhao, Yi Du
2020 arXiv   pre-print
Two-dimensional (2D) materials with a Lieb lattice can host exotic electronic band structures. Such a system does not exist in nature, and it is also difficult to obtain in the laboratory due to its structural instability. Here, we experimentally realized a 2D system composed of a tin overlayer on an aluminum substrate by molecular beam epitaxy. The specific arrangement of Sn atoms on the Al(100) surface, which benefits from favorable interface interactions, forms a stabilized buckled Lieb
more » ... ce. Our theoretical calculations indicate a partially broken nodal line loop protected by its mirror reflection symmetry and a topologically nontrivial insulating state with a spin-orbital coupling (SOC) effect in the band structure of this Lieb lattice. The electronic structure of this system has also been experimentally characterized by scanning tunnelling spectroscopy and angle-resolved photoemmision spectroscopy. Our work provides an appealing method for constructing 2D quantum materials based on the Lieb lattice.
arXiv:2001.01045v1 fatcat:kbo3q7oqyvbwjj4vipjphkzbpi

A First Look at Emoji Usage on GitHub: An Empirical Study [article]

Xuan Lu, Yanbin Cao, Zhenpeng Chen, Xuanzhe Liu
2018 arXiv   pre-print
Emoji is becoming a ubiquitous language and gaining worldwide popularity in recent years including the field of software engineering (SE). As nonverbal cues, emojis are widely used in user understanding tasks such as sentiment analysis, but few work has been done to study emojis in SE scenarios. This paper presents a large scale empirical study on how GitHub users use emojis in development-related communications. We find that emojis are used by a considerable proportion of GitHub users. In
more » ... rison to Internet users, developers show interesting usage characteristics and have their own interpretation of the meanings of emojis. In addition, the usage of emojis reflects a positive and supportive culture of this community. Through a manual annotation task, we find that sentimental usage is a main intention of using emojis in issues, pull requests, and comments, while emojis are mainly used to emphasize important contents in README. These findings not only deepen our understanding about the culture of SE communities, but also provide implications on how to facilitate SE tasks with emojis such as sentiment analysis.
arXiv:1812.04863v1 fatcat:ybtghv3xlnagvm6qmyo54h3dpi

Single Pulse Heating of Nanoparticle Array for Biological Applications [article]

CHEN XIE, Peiyuan Kang, Johan Cazals, Omar Morales Castelan, Jaona Randrianalisoa, Zhenpeng Qin
2021 bioRxiv   pre-print
With the ability to convert external excitation into heat, nanomaterials play an essential role in many biomedical applications. Two modes of nanoparticle (NP) array heating, nanoscale-confined heating (NCH) and macroscale-collective heating (MCH), have been found and extensively studied. Despite this, the resulting biological response at protein level remains elusive. In this study, we developed a computational model to systematically investigate the single-pulsed heating of NP array and
more » ... ponding protein denaturation/activation. We found that NCH may lead to targeted protein denaturation, however, nanoparticle heating does not lead to nanoscale selective TRPV1 channel activation. The excitation duration and NP concentration are primary factors that determine a window for targeted protein denaturation, and together with heating power, we defined quantified boundaries for targeted protein denaturation. Our results boost our understandings in the NCH and MCH under realistic physical constraints and provide a robust guidance to customize biomedical platforms with desired NP heating.
doi:10.1101/2021.10.21.465356 fatcat:7efkx32ahrbarbyekl5zd4zlwu

A Comprehensive Empirical Study of Bias Mitigation Methods for Software Fairness [article]

Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman
2022 arXiv   pre-print
Software bias is an increasingly important operational concern for software engineers. We present a large-scale, comprehensive empirical evaluation of 17 representative bias mitigation methods, evaluated with 12 Machine Learning (ML) performance metrics, 4 fairness metrics, and 24 types of fairness-performance trade-off assessment, applied to 8 widely-adopted benchmark software decision/prediction tasks. The empirical coverage is comprehensive, covering the largest numbers of bias mitigation
more » ... hods, evaluation metrics, and fairness-performance trade-off measures compared to previous work on this important operational software characteristic. We find that (1) the bias mitigation methods significantly decrease the values reported by all ML performance metrics (including those not considered in previous work) in a large proportion of the scenarios studied (42%~75% according to different ML performance metrics); (2) the bias mitigation methods achieve fairness improvement in only approximately 50% over all scenarios and metrics (ranging between 29%~59% according to the metric used to asses bias/fairness); (3) the bias mitigation methods have a poor fairness-performance trade-off or even lead to decreases in both fairness and ML performance in 37% of the scenarios; (4) the effectiveness of the bias mitigation methods depends on tasks, models, and fairness and ML performance metrics, and there is no 'silver bullet' bias mitigation method demonstrated to be effective for all scenarios studied. The best bias mitigation method that we find outperforms other methods in only 29% of the scenarios. We have made publicly available the scripts and data used in this study in order to allow for future replication and extension of our work.
arXiv:2207.03277v1 fatcat:yuz5p5lsofgq3njgo76pneoevy

A Dissipation Function–Based Method for Calculating the Energy Loss of Intracranial Aneurysms

Xiao Mo, Hongshi Yu, Rong Chen, Zhenpeng Chen, Haiyun Li
2021 Frontiers in Neurology  
Copyright © 2021 Mo, Yu, Chen, Chen and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).  ... 
doi:10.3389/fneur.2021.639690 fatcat:qacmlqc6rvhgrll7w3hyxvlx24

A Literature Review on Serverless Computing [article]

Jinfeng Wen, Zhenpeng Chen, Xuanzhe Liu
2022 arXiv   pre-print
Serverless computing is an emerging cloud computing paradigm. Moreover, it has become an attractive development option for cloud-based applications for software developers. The most significant advantage of serverless computing is to free software developers from the burden of complex underlying management tasks and allow them to focus on only the application logic implementation. Based on its benign characteristics and bright prospect, it has been an increasingly hot topic in various
more » ... such as machine learning, scientific computing, video processing, and the Internet of Things. However, none of the studies focuses on a comprehensive analysis of the current research state of the art of serverless computing from the research scope and depth. To fill this knowledge gap, we present a comprehensive literature review to summarize the current research state of the art of serverless computing. This review is based on selected 164 research papers to answer three key aspects, i.e., research directions (What), existing solutions (How), and platforms and venues (Where). Specifically, first, we construct a taxonomy linked to research directions about the serverless computing literature. Our taxonomy has 18 research categories covering performance optimization, programming framework, application migration, multi-cloud development, cost, testing, debugging, etc. Second, we classify the related studies of each research direction and elaborate on existing solutions. Third, we investigate the distributions of experimental platforms for existing techniques and publication venues for selected research papers. Finally, based on our analysis, we discuss some key challenges and envision promising opportunities for future research on the serverless platform side, serverless application side, and serverless computing community side.
arXiv:2206.12275v3 fatcat:uk5rrpxu5vaixlkudoshyjrq64

Demystifying Developers' Issues in Distributed Training of Deep Learning Software [article]

Diandian Gu, Zhenpeng Chen, Yuanqiang Liu, Zili Zhang, Yun Ma, Xin Jin, Xuanzhe Liu
2021 arXiv   pre-print
Chen et al. [31] studied deployment faults of DL-based mobile applications. Different from previous studies, we focus on a specific domain, i.e., distributed training. Distributed training.  ... 
arXiv:2112.06222v1 fatcat:kmmqsghqgbdu3btozzysmgy664

Understanding Characteristics of Commodity Serverless Computing Platforms [article]

Jinfeng Wen, Yi Liu, Zhenpeng Chen, Yun Ma, Haoyu Wang, Xuanzhe Liu
2021 arXiv   pre-print
Serverless computing becomes the new trending paradigm in cloud computing, allowing developers to focus on the core application logic and rapidly prototype applications. Due to the great prospects of serverless computing, in recent years, most major cloud vendors have rolled out their commodity serverless computing platforms. However, the characteristics of these platforms have not been systematically studied. To fill this knowledge gap, this paper presents a comprehensive study on
more » ... g mainstream commodity serverless computing platforms (i.e., AWS Lambda, Azure Functions, Google Cloud Functions, and Alibaba Cloud Function Compute). First, we qualitatively analyze these platforms from development, deployment, and runtime aspects to form the taxonomy of characteristics. Additionally, we quantitatively evaluate the actual performance of different serverless computing platforms through our designed benchmark platform. Our benchmark platform has two types of benchmarks, i.e., microbenchmarks and macrobenchmarks. Based on the results of qualitative and quantitative analyses, we derive a series of findings and provide insightful implications for both developers and cloud vendors.
arXiv:2012.00992v2 fatcat:l2d6hgaa4vcxnjmfeznvnxygem
« Previous Showing results 1 — 15 out of 303 results