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IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)

作者： Iudean, Bogdan Babes Bolyai Univ Dept Comp Sci Cluj Napoca Romania

ISBN: (纸本)9798350351583;9798350351576

Multi-core processors, cloud computing, and distributed applications now define the landscape of modern software development and research. Efficiently teaching multithreading concepts is vital to equip students for real-world industry challenges. Navigating the complexities of multithreading proves challenging for students due to the high level of abstraction and difficulty associated with these concepts. The complexity of these technological fields raises the necessity for a comprehensive educational approach that facilitates students to understand the multithreading functionalities and usages with ease. This experience paper details our teaching approach, utilizing narrative-driven methods in parallel and distributed programming laboratories. We emphasize the relevance, novelty, and benefits of integrating interactive storytelling into the tangled learning process of parallel and distributed programming concepts. Concurrency, parallelization, and workload distribution are explained through live narrations, accompanied by animated presentations following a procedural storyline that spans laboratories. Complex ideas are transformed into meaningful character interactions, like stone-age people training octopuses to make ice-cream concurrently. This unique approach aims not only to enhance comprehension but also to make learning a vibrant and memorable experience for students, bridging the gap between theory and practical application. Our report extracts valuable lessons from student activities, emphasizing the motivational impact of engaging narratives. Students reflect on the relevance of concepts, shifting focus from implementation to understanding. Beyond just facilitating and easier access to knowledge, our approach aims to raise a deeper appreciation for the intricate world of parallel and distributed programming domain by encouraging students to see beyond the technical depth.

关键词： narrative-driven teaching parallel and distributed programming multithreading concepts interactive storytelling educational innovation

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parallel Algorithm for Discovering and Comparing Three-Dimensional Proteins Patterns

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2024年第3期21卷 508-515页

作者： Valdes-Jimenez, Alejandro Reyes-Parada, Miguel Nunez-Vivanco, Gabriel Jimenez-Gonzalez, Daniel Univ Bio Bio Dept Informat Syst Concepcion 4051381 Chile Univ Politecn Catalunya BarcelonaTech UPC Dept Arquitectura Comp DAC Barcelona 08034 Spain Univ Santiago Chile Escuela Med Fac Ciencias Med Ctr Invest Biomed & Aplicada CIBAP Santiago 9170022 Chile Univ Autonoma Chile Fac Ciencias Salud Providencia 7500912 Chile Univ Aysen Dept Nat Sci & Technol Coyhaique 5950000 Chile Barcelona Supercomp Ctr BSC Barcelona 08034 Spain

Identifying conserved (similar) three-dimensional patterns among a set of proteins can be helpful for the rational design of polypharmacological drugs. Some available tools allow this identification from a limited perspective, only considering the available information, such as known binding sites or previously annotated structural motifs. Thus, these approaches do not look for similarities among all putative orthosteric and or allosteric bindings sites between protein structures. To overcome this tech-weakness Geomfinder was developed, an algorithm for the estimation of similarities between all pairs of three-dimensional amino acids patterns detected in any two given protein structures, which works without information about their known patterns. Even though Geomfinder is a functional alternative to compare small structural proteins, it is computationally unfeasible for the case of large protein processing and the algorithm needs to improve its performance. This work presents several parallel versions of the Geomfinder to exploit SMPs, distributed memory systems, hybrid version of SMP and distributed memory systems, and GPU based systems. Results show significant improvements in performance as compared to the original version and achieve up to 24.5x speedup when analyzing proteins of average size and up to 95.4x in larger proteins.

关键词： CUDA MPI OpenMP parallel and distributed programming proteins three-dimensional patterns discovering

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A distributed and energy-efficient KNN for EEG classification with dynamic money-saving policy in heterogeneous clusters

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COMPUTING 2023年第11期105卷 2487-2510页

作者： Escobar, Juan Jose Rodriguez, Francisco Prieto, Beatriz Kimovski, Dragi Ortiz, Andres Damas, Miguel Univ Granada Dept Software Engn CITIC Granada Spain Univ Granada Dept Comp Engn Automation & Robot CITIC Granada Spain Univ Klagenfurt Inst Informat Technol Klagenfurt Austria Univ Malaga Dept Commun Engn Malaga Spain

Due to energy consumption's increasing importance in recent years, energy-time efficiency is a highly relevant objective to address in High-Performance Computing (HPC) systems, where cost significantly impacts the tasks executed. Among these tasks, classification problems are considered due to their great computational complexity, which is sometimes aggravated when processing high-dimensional datasets. In addition, implementing efficient applications for high-performance systems is not an easy task since hardware must be considered to maximize performance, especially on heterogeneous platforms with multi-core CPUs. Thus, this article proposes an efficient distributed K-Nearest Neighbors (KNN) for Electroencephalogram (EEG) classification that uses minimum Redundancy Maximum Relevance (mRMR) as a feature selection technique to reduce the dimensionality of the dataset. The approach implements an energy policy that can stop or resume the execution of the program based on the cost per Megawatt. Since the procedure is based on the master-worker scheme, the performance of three different workload distributions is also analyzed to identify which one is more suitable according to the experimental conditions. The proposed approach outperforms the classification results obtained by previous works that use the same dataset. It achieves a speedup of 74.53 when running on a multi-node heterogeneous cluster, consuming only 13.38% of the energy consumed by the sequential version. Moreover, the results show that financial costs can be reduced when energy policy is activated and the importance of developing efficient methods, proving that energy-aware computing is necessary for sustainable computing.

关键词： parallel and distributed programming Heterogeneous clusters Energy-aware computing EEG classification KNN Money-saving

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Energy-Aware KNN for EEG Classification: A Case Study in Heterogeneous Platforms 17th

Energy-Aware KNN for EEG Classification: A Case Study in Het...

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17th International Work-Conference on Artificial Neural Networks (IWANN)

作者： Jose Escobar, Juan Rodriguez, Francisco Kiziltepe, Rukiye Savran Prieto, Beatriz Kimovski, Dragi Ortiz, Andres Damas, Miguel Univ Granada CITIC Dept Software Engn Granada Spain Univ Granada CITIC Dept Comp Engn Automat & Robot Granada Spain Karadeniz Tech Univ Sofware Engn Trabzon Turkiye Univ Klagenfurt Inst Informat Technol Klagenfurt Austria Univ Malaga Dept Commun Engn Malaga Spain

ISBN: (纸本)9783031430848;9783031430855

The growing energy consumption caused by IT is forcing application developers to consider energy efficiency as one of the fundamental design parameters. This parameter acquires great relevance in HPC systems when running artificial neural networks and Machine Learning applications. Thus, this article shows an example of how to estimate and consider energy consumption in a real case of EEG classification. An efficient and distributed implementation of the KNN algorithm that uses mRMR as a feature selection technique to reduce the dimensionality of the dataset is proposed. The performance of three different workload distributions is analyzed to identify which one is more suitable according to the experimental conditions. The proposed approach outperforms the classification results obtained by previous works. It achieves an accuracy rate of 88.8% and a speedup of 74.53 when running on a multi-node heterogeneous cluster, consuming only 13.38% of the energy of the sequential version.

关键词： parallel and distributed programming Heterogeneous clusters Energy-aware computing EEG classification KNN mRMR

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distributed futures for efficient data transfer between parallel processes 20

Distributed futures for efficient data transfer between para...

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35th Annual ACM Symposium on Applied Computing (SAC)

作者： Leca, Pierre Suijlen, Wijnand Henrio, Ludovic Baude, Francoise Huawei Technol Boulogne Billancourt France Univ Lyon EnsL UCBL CNRSInriaLIP Lyon Lyon France Univ Cote dAzur CNRS I3S Sophia Antipolis France

ISBN: (纸本)9781450368667

This paper defines distributed futures, a construct that provides at the same time a data container similar to a distributed vector, and a single synchronization entity that behaves similarly to a standard future. This simple construct makes it easy to program a composition, in a task-parallel way, of several massively data-parallel tasks. The approach is implemented and evaluated in the context of a bulk synchronous parallel (BSP) active object framework.

关键词： parallel and distributed programming Futures

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Approches coopératives pour certaines classes de problèmes d'optimisation non convexe: Algorithmes parallèles / distribués et applications: Cooperative approaches for some classes of nonconvex optimization problems: parallel / distributed algorithms and applications

Approches coopératives pour certaines classes de problèmes...

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作者： Samir, Sara Université de Lorraine

学位级别：博士

Dans cette thèse, nous nous intéressons au développement des approches coopératives pour la résolution de certaines classes de problèmes d'optimisation non convexe qui jouent un rôle très important de par leurs applications dans de nombreux domaines. Il s'agit de combiner plusieurs algorithmes connus sous les noms des algorithmes composants (participants). La combinaison est basée principalement sur la programmation DC (Difference of Convex Functions) et DCA (DC Algorithm) avec des métaheuristiques. Pour la conception des logiciels nous utilisons les paradigmes de la programmation parallèle et distribuée. Chaque processus s'occupe d'un algorithme et communique avec les autres en appelant les fonctions de la bibliothèque MPI (Message Passing Interface) qui est un protocole de communication en programmation parallèle et distribuée. Outre l'introduction et la conclusion, la thèse est composée de quatre chapitres. Le chapitre 1 concerne les outils théoriques et algorithmiques comme servant de base méthodologique aux chapitres suivants. Le chapitre 2 s'articule autour les problèmes linéaires à variables mixtes binaires. Pour la résolution de ces problèmes, nous proposons une approche coopérative entre DCA et VNS (Variable Neighborhood Search). Puisque le schéma est constitué de deux algorithmes, nous optons pour la communication point à point entre les processus. Nous adaptons notre schéma pour résoudre le problème de localisation de l'installation avec des contraintes de capacités. Dans le chapitre 3, nous étudions la programmation quadratique à variables binaires. Nous développons une coopération entre DCA-Like (une nouvelle version de DCA) et deux autres métaheuristiques : GA (Genetic Algorithm) et MBO (Migrating Birds Optimization). Pour la communication entre les processus, nous utilisons la communication collective. Plus précisément une fonction qui permet la diffusion simultanée l'information d'un processus à tous les autres. Cette approche est adaptée et appliqué

关键词： Optimisation non convexe Approches coopératives Programmation parallèle et distribuée Programmation DC et DCA Métaheuristiques Nonconvex optimization Cooperative approaches parallel and distributed programming DC programming and DCA Metaheuristics 006.382 3 519.6

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A Collaborative Approach Based on DCA and VNS for Solving Mixed Binary Linear Programs 11th

A Collaborative Approach Based on DCA and VNS for Solving Mi...

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11th Asian Conference on Intelligent Information and Database Systems (ACIIDS)

作者： Samir, Sara Hoai An Le Thi Univ Lorraine LGIPM Comp Sci & Applicat Dept Metz France

ISBN: (纸本)9783030147990

This paper addresses the Mixed Binary Linear programming problems (MBLPs) by a collaborative approach using two component algorithms. The first is DCA (Difference of Convex functions Algorithm), an efficient deterministic algorithm in nonconvex programming framework, and the second is VNS (Variable Neighborhood Search), a well known metaheuristic method. The DCA and VNS are executed in parallel. At the end of each cycle, the best-found solution is exchanged between these algorithms via MPI (Message Passing Interface) library. The next cycle starts with the previous best-found solution as an initial solution. The performance of the proposed approach is tested on a set of benchmarks of the Capacitated Facility Location Problem. Numerical experiments show the efficiency of our approach.

关键词： Mixed Binary Linear programming problems DC programming and DCA Metaheuristics parallel and distributed programming

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International Master's degree program "High-Performance and distributed information processing systems" 3

International Master's degree program "High-Performance and ...

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3rd International Conference on Information Technology and Nanotechnology (ITNT)

作者： Kolomiets, E. I. Samara Natl Res Univ Moskovskoe Shosse 34 Samara 443086 Russia

This paper presents information on the content and resources of the internationally certified Master's program "High-Performance and distributed Information Processing Systems" in the field of Applied Mathematics and Computer Science. The paper studies scientific achievements of the academic staff, peculiarities of courses currently held, characteristics of available facilities and resources, prospects for the Master's worldwide research activities at a high scientific level, and opportunities to pursue postgraduate studies and to defend a PhD thesis. (c) 2017 The Authors. Published by Elsevier Ltd.

关键词： Master's Program curriculum core courses description parallel and distributed programming high-performance computing data mining

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Approximating the buffer allocation problem using epochs

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JOURNAL OF parallel AND distributed COMPUTING 2008年第9期68卷 1263-1282页

作者： Pedersen, Jan Baekgaard Brodsky, Alex Sampson, Jeffrey Univ Nevada Sch Comp Sci Las Vegas NV 89154 USA Univ Winnipeg Dept Appl Comp Sci Winnipeg MB R3B 2E9 Canada

The correctness of applications that perform asynchronous message passing typically relies on the underlying hardware having a sufficient amount of memory (message buffers) to hold all undelivered messages-such applications may deadlock when executed on a system with an insufficient number of message buffers. Thus, determining the minimum number of buffers that an application needs to prevent deadlock is an important task when writing portable parallel applications. Unfortunately, both this problem (called the Buffer Allocation Problem) and the simpler problem of determining whether an application may deadlock for a given number of available message buffers are intractable [A. Brodsky, J. Pedersen, A. Wagner, On the complexity of buffer allocation in message passing systems, journal of parallel and distributed Computing 65 (2005) 692-713]. We present a new epoch-based polynomial-time approach for approximating a solution to the Buffer Allocation Problem. Our approach partitions application executions into epochs and intersperses barrier synchronizations between them, thus limiting the number of message buffers necessary to ensure deadlock-freedorn. This approach produces near optimal solutions for many common cases and can be adapted to guide application modifications that ensure deadlock-freedom when the application is executed on different systems. We describe a prototype implementation, and present all empirical evaluation of this approach. Lastly, we describe a space-time trade-off between the number of available message buffers and the number of barrier synchronizations, and describe how this trade-off can be used to fine-tune application performance. (c) 2008 Elsevier Inc. All rights reserved.

关键词： message passing systems buffer allocation complexity parallel and distributed programming

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On the complexity of buffer allocation in message passing systems

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JOURNAL OF parallel AND distributed COMPUTING 2005年第6期65卷 692-713页

作者： Brodsky, A Pedersen, JB Wagner, A Univ Nevada Sch Comp Sci Las Vegas NV 89154 USA Univ Toronto Dept Comp Sci Toronto ON M5S 3G4 Canada Univ British Columbia Dept Comp Sci Vancouver BC V6T 1Z4 Canada

Message passing programs commonly use message buffers to avoid unnecessary synchronizations and to improve performance by overlapping communication with computation. Unfortunately, using buffers can introduce portability problems and can lead to deadlock problems on systems without a sufficient number of message buffers. We explore a variety of problems related to buffer allocation for safe and efficient execution of message passing programs. We show that determining the minimum number of message buffers or verifying that each process has a sufficient number of message buffers are intractable problems. However, we give a polynomial time algorithm to determine the minimum number of message buffers needed to ensure that no send operation is unnecessarily delayed due to lack of message buffers. We extend these results to several different buffering schemes, which in some cases make the problems tractable. (c) 2005 Elsevier Inc. All rights reserved.

关键词： message passing systems buffer allocation complexity parallel and distributed programming

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