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Serverless-like platform for container-based YARN clusters
(Elsevier, 2024-06)
[Abstract]: Serverless computing is an emerging paradigm that has gained a lot of relevance in recent years, as it allows users to consume computing resources without worrying about the underlying infrastructure and pay ...
Performance Evaluation of Big Data Frameworks for Large-Scale Data Analytics
(IEEE Computer Society, 2017-02-06)
[Abstract] The increasing adoption of Big Data analytics has led to a high demand for efficient technologies in order to manage and process large datasets. Popular MapReduce frameworks such as Hadoop are being replaced by ...
Evaluation of Java for General Purpose GPU Computing
(IEEE Computer Society, 2013-07-01)
[Abstract] The presence of many-core units as accelerators has been increasing due to their ability to improve the performance of highly parallel workloads. General Purpose GPU(GPGPU) computing has allowed the graphical ...
Analysis and evaluation of MapReduce solutions on an HPC cluster
(Pergamon Press, 2016-02)
[Abstract] The ever growing needs of Big Data applications are demanding challenging capabilities which cannot be handled easily by traditional systems, and thus more and more organizations are adopting High Performance ...
MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads
(Elsevier, 2015)
[Abstract]: The popularity of Big Data computing models like MapReduce has caused the emergence of many frameworks oriented to High Performance Computing (HPC) systems. The suitability of each one to a particular use case ...
Enhancing in-memory Efficiency for MapReduce-based Data Processing
(Academic Press, 2018-10)
[Abstract] As the memory capacity of computational systems increases, the in-memory data management of Big Data processing frameworks becomes more crucial for performance. This paper analyzes and improves the memory ...
Flame-MR: An event-driven architecture for MapReduce applications
(Elsevier BV * North-Holland, 2016)
[Abstract] Nowadays, many organizations analyze their data with the MapReduce paradigm, most of them using the popular Apache Hadoop framework. As the data size managed by MapReduce applications is steadily increasing, the ...
Low‐latency Java communication devices on RDMA‐enabled networks
(John Wiley & Sons Ltd., 2015)
[Abstract] Providing high‐performance inter‐node communication is a key capability for running high performance computing applications efficiently on parallel architectures. In fact, current systems deployments are aggregating ...
Java in the High Performance Computing arena: Research, practice and experience
(Elsevier BV, 2013-05-01)
[Abstract] The rising interest in Java for High Performance Computing (HPC) is based on the appealing features of this language for programming multi-core cluster architectures, particularly the built-in networking and ...
FastMPJ: a scalable and efficient Java message-passing library
(Springer New York LLC, 2014)
[Abstract] The performance and scalability of communications are key for high performance computing (HPC) applications in the current multi-core era. Despite the significant benefits (e.g., productivity, portability, ...
