CLEI Eletronic Journal (CLEIej)

Many problems, in diverse areas of science and engineering, involve the solution of largescale sparse systems of linear equations. In most of these scenarios, they are also a computational bottleneck, and therefore their efficient solution on parallel architectureshas motivated a tremendous volume of research.This dissertation targets the use of GPUs to enhance the performance of the solution of sparse linear systems using iterative methods complemented with state-of-the-art preconditioned techniques. In particular, we study ILUPACK, a package for the solution of sparse linear systems via Krylov subspace methods that relies on a modern inverse-based multilevel ILU (incomplete LU) preconditioning technique.We present new data-parallel versions of the preconditioner and the most important solvers contained in the package that significantly improve its performance without affecting its accuracy. Additionally we enhance existing task-parallel versions of ILUPACK for shared- and distributed-memory systems with the inclusion of GPU acceleration. The results obtained show a sensible reduction in the runtime of the methods, as well as the possibility of addressing large-scale problems efficiently.

Ernesto Dufrechou

CLEI electronic journal

Accelerating advanced preconditioning methods on hybrid architectures

加速混合架构上的高级预处理方法

Neural networks are currently the state-of-the-art for many tasks.Invariance and same-equivariance are two fundamental properties to characterize how a model reacts to transformation: equivariance is the generalization of both. Equivariance to transformations of the inputs can be necessary properties of the network for certain tasks. Data augmentation and specially designed layers provide a way for these properties to be learned by networks. However, the mechanisms by which networks encode them is not well understood.We propose several transformational measures to quantify the invariance and same-equivariance of individual activations of a network. Analysis of these results can yield insights into the encoding and distribution of invariance in all layers of a network. The measures are simple to understand and efficient to run, and have been implemented in an open-source library. We perform experiments to validate the measures and understand their properties, showing their stability and effectiveness. Afterwards, we use the measures to characterize common network architectures in terms of these properties, using affine transformations. Our results show, for example, that the distribution of invariance across the layers of a network has well a defined structure that is dependent only on the network design and not on the training process.

Facundo Manuel Quiroga

Invariance and Same-Equivariance Measures for Convolutional Neural Networks

卷积神经网络的不变性和相同等变性度量

Energy-efficient management is key to reduce operational cost and environmental contamination in modern data centers. Energy management and renewable energy utilization are strategies to optimize energy consumption in high-performance computing. In any case, understanding the power consumption behavior of physical servers in datacenter is fundamental to implement energy-aware policies effectively. These policies should deal with possible performance degradation of applications to ensure quality of service. This manuscript presents an empirical evaluation of power consumption for scientific computing applications in multicore systems. Three types of applications are studied, in single and combined executions on Intel and AMD servers, for evaluating the overall power consumption of each application. The main results indicate that power consumption behavior has a strong dependency with the type of application. Additional performance analysis shows that the best load of the server regarding energy efficiency depends on the type of the applications, with efficiency decreasing in heavily loaded situations. These results allow formulating models to characterize applications according to power consumption, efficiency, and resource sharing, which provide useful information for resource management and scheduling policies. Several scheduling strategies are evaluated using the proposed energy model over realistic scientific computing workloads. Results confirm that strategies that maximize host utilization provide the best energy efficiency.

Jonathan Muraña

Empirical power consumption characterization and energy aware scheduling in data centers

数据中心能耗实证特性与能效调度

In cloud computing resource allocation, Virtual Machine Placement (VMP) is one of the most studied problems with several possible formulations and different optimization criteria. The present work summarizes a doctoral dissertation focused on studying Many-Objective Virtual Machine Placement (MaVMP) problems. As first contributions, novel taxonomies were proposed for VMP problems in cloud computing environments, in order to gain a systematic understanding of the existing approaches. Additionally, first formulations of MaVMP problems were proposed in: (1) static MaVMP for initial placement, (2)semi-dynamic MaVMP with recon guration of VMs and (3) dynamic two-phase MaVMP for complex cloud computing environments under uncertainty. Considering the novelty of the proposed formulations, several methods and algorithms were also proposed to address main identi ed issues on solving each particular MaVMP problem. Experimental results prove the correctness, effectiveness and scalability of the proposed methods and algorithms in different experimental scenarios even when comparing to state-of-the-art alternatives.

Fabio Lopez-Pires

Many-Objective Resource Allocation for Elastic Infrastructures in Overbooked Cloud Computing Datacenters Under Uncertainty

多目标资源分配在超售云计算数据中心弹性基础设施中的不确定性问题

Authentication is the process of verifying a user’s identity for them to access a system’s resources. An authentication factor is a piece of information used for this authentication. Three well-known groups of authentication factors exist: knowledge-based (what you know), possession-based (what you have) and inherence-based (what you are). Authentication schemes belonging to distinct authentication factors can be combined in a multi-factor manner to increase security. Although multiple multi-factor proposals are seen in literature, the absence of a method that allows a proper comparison and selection of these authentication methods, based on an application’s security requirements, can be observed. Existing frameworks for the analysis of authentication methods have been identified through the realization of a systematic literature review, but most of these focus on specific contexts and do not provide a generic enough solution. Due to the above, this research focuses on the creation of a recommendation framework that guides in the comparison and selection of single and multi-factor authentication schemes, considering both the application’s requirements and its context. This has been attained not only through the knowledge found in literature, but the experience from industry experts has been compiled as well through the collaboration with a multinational software development company. Consequently, the knowledge found in literature has been obtained from a systematic literature review, whereas the experience from industry experts was obtained through a survey and interviews. The framework proposal has been generated based on the above and has been validated through an expert panel and a case study methodology in collaboration with the partnered software development company. A tool prototype has been constructed as well. The result is a recommendation framework for the comparison and selection of authentication methods that can support this decision process in multiple contexts.

Ignacio Velásquez

Framework for the Comparison and Selection of Schemes for Multi-Factor Authentication

多因素认证方案比较与选择框架

Image segmentation is a fundamental process in image processing, aiming to transform the image into a more comprehensible or simplified representation. This process groups pixels under common characteristics, facilitating the unique identification of regions or elements of interest. The quality of segmentation is crucial as it significantly influences the subsequent stages of image processing. Image segmentation plays a vital role in various advanced applications, including computer vision and the analysis of medical, topographical, and astronomical images. Given that there is no universal segmentation method guaranteeing optimal performance for all cases, selecting an appropriate technique for a specific type of image or application represents a complex and demanding challenge. In this work, we propose the use of Multi-Objective Evolutionary Algorithms (MOEAs) as a training tool that integrates operations representative of the usual techniques and strategies in image segmentation. This allows for the generation of operation sequences adapted to specific applications or types of images. The objective functions used to guide the evolutionary process are the maximization of sensitivity (TPR) and specificity(TNR), fundamental components of ROC analysis. Experiments were conducted with multiple images sharing common characteristics from image databases, specifically: i ) benign and malignant melanoma images, ii ) ophthalmoscopic retinal images, and iii ) binary cell form images. We compared the segmentation generated by our proposed algorithm with the ideal segmentation. The results are quite promising and demonstrate the feasibility of using MOEAs to generate sequences of segmentation operations valid for specific applications.

Pedro Esteban Gardel Sotomayor

Diego P. Pinto-Roa

Julio César Mello-Román

José Luis Vázquez Noguera

Ramón Quintana

Fredy Roa

Multi-objective Evolutionary Algorithms based Operation Sequence Design for Image Segmentation

基于多目标进化算法的图像分割操作序列设计

This paper presents the results of a security assessment of FIWARE technology. We adopted an offensive perspective to identify vulnerabilities in deploying FIWARE components in specific architecture configurations. We identify security issues by experimenting in a locally controlled environment and propose a threat model following the OWASP methodology. We implemented attacks for three of the identified attack goals and validated our approach with an exploratory analysis of an actual working and productive FIWARE platform. This analysis helped us distinguish different types of attacks, and we ended up with recommendations for components, architecture, and access control.

Juan Pablo Perata

Gustavo Betarte

A Methodological Approach for the Security Analysis of FIWARE Technology

一种用于FIWARE技术安全分析的方法论方法

Hernán Astudillo

Carlos Luna

José Miguel Rojas

Preface to the CLEI 2023 Special Issue – Volume II

CLEI 2023特刊前言 – 第二卷

Cryptography based on elliptic curves is endowed with efficient methods for public-key cryptography. Recent research has shown the superiority of the Montgomery and Edwards curves over the Weierstrass curves as they require fewer arithmetic operations. Using these modern curves has, however, introduced several challenges to the cryptographic algorithm’s design, opening up new opportunities for optimization. Our main objective is to propose algorithmic optimizations and implementation techniques for cryptographic algorithms based on elliptic curves. In order to speed up the execution of these algorithms, our approach relies on the use of extensions to the instruction set architecture. In addition to those specific for cryptography, we use extensions that follow the Single Instruction, Multiple Data (SIMD) parallel computing paradigm. In this model, the processor executes the same operation over a set of data in parallel. We investigated how to apply SIMD to the implementation of elliptic curve algorithms. As part of our contributions, we design parallel algorithms for prime field and elliptic curve arithmetic. We also design a new three-point ladder algorithm for the scalar multiplication P + kQ, and a faster formula for calculating 3P on Montgomery curves. These algorithms have found applicability in isogeny-based cryptography. Using SIMD extensions such as SSE, AVX, and AVX2, we develop optimized implementations of the following cryptographic algorithms: X25519, X448, SIDH, ECDH, ECDSA, EdDSA, and qDSA. Performance benchmarks show that these implementations are faster than existing implementations in the state of the art. Our study confirms that using extensions to the instruction set architecture is an effective tool for optimizing implementations of cryptographic algorithms based on elliptic curves. May this be an incentive not only for those seeking to speed up programs in general but also for computer manufacturers to include more advanced extensions that support the increasing demand for cryptography.

Armando Faz Hernandez

Julio López

High-Performance Elliptic Curve Cryptography: A SIMD Approach to Modern Curves (Extended Thesis Summary)

高性能椭圆曲线密码学：现代曲线的SIMD方法（扩展论文摘要）

The Stochastic Shortest Path (SSP) is a formalism widely used for modeling goal-oriented probabilistic planning problems. When dead ends, which are states from which goal states cannot be reached, are present in the problem and cannot be avoided, the standard criterion for solving SSPs is not well defined in these scenarios. Because of that, several alternate criteria for solving SSPs with unavoidable dead ends have been proposed in the literature. One of these criteria is GUBS (Goals with Utility-Based Semantics), a criterion that makes trade-offs between probability-to-goal and cost by combining goal prioritization with Expected Utility Theory. GUBS is a good choice for these problems because it is one of the only criteria that are known to maintain the ?-strong probability-to-goal priority property, a property that provides guarantees on how a decision criterion can choose policies without having to preprocess any specific SSP problem. Although there already exist two exact algorithms for solving GUBS, eGUBS-VI and eGUBS-AO*, both are offline and there is no algorithm for solving GUBS in an online manner. In this paper we propose UCT-GUBS, an online approximate algorithm based on UCT (a Monte Carlo tree search algorithm) that solves SSPs under the GUBS criterion. We provide an analysis of an empirical evaluation performed on two probabilistic planning domains (Triangle Tireworld and Navigation) to observe how the probability-to-goal and utility values of the resulting policies compare to the optimal values, and also how the time performance of UCT-GUBS compares to the ones of eGUBS-VI and eGUBS-AO*. Our conclusion is that, like other algorithms, the usage of UCT-GUBS has to be evaluated considering the application requirements and of the problem being solved. Depending on these factors, it can be a good alternative for obtaining policies in an online fashion while, for some problems, also being able to have better time performance than other algorithms

Publication Information	Publisher: Latin American Center for Informatics Studies，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2019，Proportion of original research papers: 0.00%，Self Citation Rate:N.A.， Gold OA Rate: 0.00%
Average review cycle	网友分享经验：40 Weeks

CLEI Eletronic Journal (CLEIej)

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