作者: ATRIA 時(shí)間: 2025-3-21 21:11 作者: Enrage 時(shí)間: 2025-3-22 02:38 作者: 兩種語言 時(shí)間: 2025-3-22 05:50 作者: Odyssey 時(shí)間: 2025-3-22 09:53 作者: 巫婆 時(shí)間: 2025-3-22 13:14 作者: 巫婆 時(shí)間: 2025-3-22 17:18 作者: Highbrow 時(shí)間: 2025-3-22 23:10
https://doi.org/10.1007/978-3-662-26253-5ation, work well for stateless applications, the feasibility of containerization of stateful applications, such as database management system (DBMS), still remains unclear due to potential performance overhead. The myriad of container operation models and storage backends even raises the complexity 作者: Physiatrist 時(shí)間: 2025-3-23 01:52 作者: Fissure 時(shí)間: 2025-3-23 08:51 作者: granite 時(shí)間: 2025-3-23 11:57
Ergebnisse der empirischen Analyse,exchanged and used by various tasks allocated on different nodes of the system. The management of such a huge communication demand is crucial for reaching the best possible performance of the system. Meanwhile, we have to deal with more interferences as the trend is to use a single all-purpose inter作者: 急急忙忙 時(shí)間: 2025-3-23 17:14 作者: idiopathic 時(shí)間: 2025-3-23 18:45 作者: 忍受 時(shí)間: 2025-3-24 01:38 作者: 健壯 時(shí)間: 2025-3-24 03:40 作者: Constituent 時(shí)間: 2025-3-24 09:54 作者: GUISE 時(shí)間: 2025-3-24 11:52
978-3-030-10548-8Springer Nature Switzerland AG 2019作者: 持續(xù) 時(shí)間: 2025-3-24 18:47
Euro-Par 2018: Parallel Processing Workshops978-3-030-10549-5Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: DNR215 時(shí)間: 2025-3-24 22:16 作者: 樹木中 時(shí)間: 2025-3-25 01:49 作者: 沙發(fā) 時(shí)間: 2025-3-25 05:53 作者: white-matter 時(shí)間: 2025-3-25 10:23
Einteilung der Erkrankungen der Harnorgane,ations in the distribution, is not dependent on the total number of processors and is thus well suited for use in a workflow management systems. We describe a preliminary implementation of the algorithm within such a workflow system and show performance results that indicate a significant performance benefit in data redistribution generation.作者: muscle-fibers 時(shí)間: 2025-3-25 12:27 作者: facetious 時(shí)間: 2025-3-25 19:44
Scalable Work-Stealing Load-Balancer for HPC Distributed Memory Systems benchmark which emulates arbitrary workload distribution and imbalance characteristics. Finally, we compare TITUS_DLB to the . solution developed for the YALES2 computational fluid dynamics and combustion solver. We achieve up?to 54% performance gain over thousands of cores.作者: 一瞥 時(shí)間: 2025-3-25 22:19 作者: 無法取消 時(shí)間: 2025-3-26 02:44 作者: AIL 時(shí)間: 2025-3-26 07:23 作者: 泄露 時(shí)間: 2025-3-26 10:15 作者: Admonish 時(shí)間: 2025-3-26 13:13
https://doi.org/10.1007/978-3-663-19790-4esults for both performance and overlap only when inter-node communications are used by MPI processes. However, we also show that enabling Simultaneous Multi-Threading for intra-communications leads to bad performances due to cache effects.作者: 桉樹 時(shí)間: 2025-3-26 16:46
The Impact of the Storage Tier: A Baseline Performance Analysis of Containerized DBMS clear performance overhead for containerized DBMS on top of virtual machines (VMs) compared to physical resources. Further, a containerized DBMS on top of VMs with different storage backends results in a tolerable performance overhead. Building upon these baseline results, we derive a set of open evaluation challenges for containerized DBMSs.作者: Euphonious 時(shí)間: 2025-3-26 22:10
Towards Vertically Scalable Spark Applicationsith its executors, but resources must be provisioned statically. To tackle this problem, the paper describes a container-based version of Spark that supports the dynamic resizing of the memory and CPU cores associated with the different executors. The evaluation demonstrates the feasibility of the approach and identifies the trade-offs involved.作者: 填滿 時(shí)間: 2025-3-27 02:23 作者: Admire 時(shí)間: 2025-3-27 09:02 作者: 誰在削木頭 時(shí)間: 2025-3-27 12:49
0302-9743 g, Euro-Par2018, which took place in Turin, Italy, in August 2018.?.The 64 full papers presented in this volume were carefully reviewed and selected from 109 submissions..Euro-Par is an annual, international conference in Europe, covering all aspects?of parallel and distributed processing. These ran作者: Folklore 時(shí)間: 2025-3-27 17:01 作者: NICE 時(shí)間: 2025-3-27 21:31
,Kan?lchenfunktion im allgemeinen,cts of the novel hardware development framework. This paper provides background and instructions for mastering the first steps of hardware development using the CAPI SNAP framework. The insights reported in this paper are based on the experiences of software engineering students with little to no prior knowledge about hardware development.作者: 革新 時(shí)間: 2025-3-27 23:59 作者: 懶鬼才會衰弱 時(shí)間: 2025-3-28 03:31 作者: 星星 時(shí)間: 2025-3-28 07:08 作者: 朋黨派系 時(shí)間: 2025-3-28 10:37 作者: 闡明 時(shí)間: 2025-3-28 15:44
Getting Started with CAPI SNAP: Hardware Development for Software Engineerscts of the novel hardware development framework. This paper provides background and instructions for mastering the first steps of hardware development using the CAPI SNAP framework. The insights reported in this paper are based on the experiences of software engineering students with little to no prior knowledge about hardware development.作者: Pander 時(shí)間: 2025-3-28 22:03 作者: 專橫 時(shí)間: 2025-3-28 23:26
https://doi.org/10.1007/978-3-322-90038-8erance mechanisms of Flink during regular operation (when there are no failures) on a distributed system and the impact on performance when there are failures. We use the Intel HiBench for conducting the evaluation.作者: indecipherable 時(shí)間: 2025-3-29 06:28
Autonomic and Latency-Aware Degree of Parallelism Management in SPary of the application, in this work we propose an autonomic and adaptive strategy to choose the proper number of replicas in SPar to address latency constraints. We experimentally evaluated our implemented strategy and demonstrated its effectiveness on a real-world application, demonstrating that our作者: 猛然一拉 時(shí)間: 2025-3-29 10:17
A Multi-level Elasticity Framework for Distributed Data Stream Processingentralized managers oversee the overall application and infrastructure adaptation. We have integrated the proposed solution into Apache Storm, relying on a previous extension we developed, and conducted an experimental evaluation. It shows that, even with simple control policies, E2DF can improve re作者: Admire 時(shí)間: 2025-3-29 15:00 作者: 斜坡 時(shí)間: 2025-3-29 18:50
A Methodology for Handling Data Movements by Anticipation: Position Papererences of both communication types are reduced by adding geometric constraints on the allocation of tasks into machines. The proposed constraints reduce implicitly the data movements by restricting the set of possible allocations for each task. This methodology has been proved to be efficient in a 作者: 收藏品 時(shí)間: 2025-3-29 21:57
NUMAPROF, A NUMA Memory Profilerd interface, the tool also provides hints about unpinned memory accesses (unpinned thread or unpinned page) which can help the developer find portion of codes not safely handling the NUMA binding. The tool also provides dedicated metrics to track access to MCDRAM of the Intel Xeon Phi codenamed Knig作者: 巨大沒有 時(shí)間: 2025-3-30 03:00
https://doi.org/10.1007/978-3-662-26254-2y of the application, in this work we propose an autonomic and adaptive strategy to choose the proper number of replicas in SPar to address latency constraints. We experimentally evaluated our implemented strategy and demonstrated its effectiveness on a real-world application, demonstrating that our作者: 出處 時(shí)間: 2025-3-30 07:04 作者: 人造 時(shí)間: 2025-3-30 08:24
Klaus von Rosenstiel,Hans Rundfeldtcheduling of all submitted containers and for efficient management, on the fly, of the resources allocation. The key idea is to make the specification on resources demand less rigid and to ask the system to decide on the precise number of resources to allocate to a container. Our framework is implem作者: 仇恨 時(shí)間: 2025-3-30 15:53 作者: 粘土 時(shí)間: 2025-3-30 18:29 作者: Innovative 時(shí)間: 2025-3-30 21:10
TPICDS: A Two-Phase Parallel Approach for Incremental Clustering of Data Streamstation of a recently developed prototype-based algorithm into three existing parallel frameworks. Based on the evaluation of performance, the paper then presents a customised pipeline framework that combines incremental and two-phase learning into a balanced approach that dynamically allocates the a作者: semiskilled 時(shí)間: 2025-3-31 02:49
Cost of Fault-Tolerance on Data Stream Processingincreasing amount of data produced every day, data streaming engines run on top of a distributed system. In this setting failures will likely happen. Current distributed data streaming engines like Apache Flink provide fault tolerance. In this paper we evaluate the impact on performance of fault tol作者: 烤架 時(shí)間: 2025-3-31 06:34
Autonomic and Latency-Aware Degree of Parallelism Management in SParlism to increase performance. However, programmers are often facing a trade-off between coding productivity and performance when introducing parallelism. SPar was created for balancing this trade-off to the application programmers by using the . attributes’ annotation mechanism. In SPar and other pr作者: chapel 時(shí)間: 2025-3-31 11:26 作者: CHASM 時(shí)間: 2025-3-31 15:33 作者: Antarctic 時(shí)間: 2025-3-31 17:35
A Resource Allocation Framework with Qualitative and Quantitative SLA Classesk is proposed in the context of containers with two qualitative and two quantitative SLAs classes to meet the needs of users. The two qualitative classes represent the satisfaction time criterion, and the reputation criterion. Moreover, the two quantitative classes represent the criterion over the n
