Cloud Computing have highlighted the importance of container orchestration to manage distributed implication's life-cycle. With the advent of Edge Computing, DevOs expect to find die features of containers in the ...
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ISBN:
(纸本)9781665414555
Cloud Computing have highlighted the importance of container orchestration to manage distributed implication's life-cycle. With the advent of Edge Computing, DevOs expect to find die features of containers in the cloud, also at the edge. However, orchestration systems have MA been designed to deal with geo-distribution aspects such as latency, intermittent networks, etc. In other words, it is unclear whether they could he directly used on top of massively distributed edge infrastructures without revision. In this paper, we provide an evaluation of Kubernetes in a WANWide context. Precisely, we present and discuss results we obtained during an experimental campaign to analyze the impact of WAN links on its behaviour. While there exist initiatives investigating Kubernetes revisions to deal with distribution aspects, there is, to the best of our knowledge. no rigorous performance evaluations to disqualify the vanilla code.
The increasing complexity of modern and future computing systems makes it challenging to develop applications that aim for maximum performance. Hybrid parallel programming models offer new ways to exploit the capabili...
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ISBN:
(纸本)9781728165820
The increasing complexity of modern and future computing systems makes it challenging to develop applications that aim for maximum performance. Hybrid parallel programming models offer new ways to exploit the capabilities of the underlying infrastructure. However, the performance gain is sometimes accompanied by increased programming complexity. We introduce an extension to PyCOMPSs, a high-level task-basedparallel programming model for Python applications, to support tasks that use MPI natively as part of the task model. Without compromising application's programmability, using Native MPI tasks in PyCOMPSs offers up to 3x improvement in total performance for compute intensive applications and up to 1.9x improvement in total performance for 110 intensive applications over sequential implementation of the tasks.
Ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant ...
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ISBN:
(纸本)9781479927289
Ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. The goal of this paper is on the one hand to classify and benchmark the ant algorithms, and on the other hand to put forward the successful elements of these methods. Moreover, the performance of the different types of ant algorithms is evaluated according to several criteria, and not only according to the quality of the obtained solutions.
This paper demonstrates on speeding up an accurate analysis of fault trees using stochastic logic through GPGPUs. Actually, probability models of dynamic gates and new accurate models for different combinations of col...
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ISBN:
(纸本)9781467387767
This paper demonstrates on speeding up an accurate analysis of fault trees using stochastic logic through GPGPUs. Actually, probability models of dynamic gates and new accurate models for different combinations of cold spare gate e.g., two cold spare gates with a share spare and a cold spare gate with more than one spare inputs are developed in this paper. Experimental results show that on average;the proposed analysis method is 235 times faster than CPU simulation time. Moreover, proposing new stochastic models results accuracy and simplicity as additional advantages of the proposed method.
HPC systems and parallel applications are increasing their complexity. Therefore the possibility of easily study and project at large scale the performance of scientific applications is of paramount importance. In thi...
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ISBN:
(纸本)9781728165820
HPC systems and parallel applications are increasing their complexity. Therefore the possibility of easily study and project at large scale the performance of scientific applications is of paramount importance. In this paper we describe a performance analysis method and we apply it to four complex HPC applications. We perform our study on a pre-production HPC system powered by the latest Arm-based CPUs for HPC, the Marvell ThunderX2. For each application we spot inefficiencies and factors that limit their scalability. The results show that in several cases the bottlenecks do not come from the hardware but from the way applications are programmed or the way the system software is configured.
Traditional approaches for capacity planning are based on queueing network models. However, modeling with queueing networks requires the knowledge of the service demands of each class of workloads at each device descr...
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ISBN:
(纸本)9780769530895
Traditional approaches for capacity planning are based on queueing network models. However, modeling with queueing networks requires the knowledge of the service demands of each class of workloads at each device described in the model. In real systems, such service demands can be very difficult to measure. In this paper, we present an optimization-based technique to address the problem. The technique is formulated as a robust linear parameter estimation that can be used with both closed and open queueing network models. We consider the case where aggregate measurements (throughput and utilization) are available. Such measurements are typically much easier to obtain than the service demands. We present experimental results which prove the effectiveness of the constrained and robust linear estimation.
The efficient scheduling of large mixed parallel applications is challenging. Most existing algorithms utilize scheduling heuristics and approximation algorithms to determine a good schedule as basis for an efficient ...
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ISBN:
(纸本)9780769535449
The efficient scheduling of large mixed parallel applications is challenging. Most existing algorithms utilize scheduling heuristics and approximation algorithms to determine a good schedule as basis for an efficient execution in large scale scientific computing. This paper concentrates on the scheduling of mixed parallel applications represented by task graphs with parallel tasks and precedence constraints between them. Layer-based scheduling algorithms for homogeneous target platforms are improved by adding a move-blocks phase that further reduces the resulting parallel runtime. The layer-based scheduling approach is described and the move-blocks algorithm is introduced in detail. The move-blocks extension provides better scheduling results for small as well as for large problems but has only a small increase in runtime. This is shown by a comparison of the modified and the original algorithms over a wide range of test cases.
In this paper, we present parallelo parallel Library (PPL), a novel Rust library for structured parallel programming. Rust's fearless concurrency concept makes it a promising language for parallel application deve...
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ISBN:
(纸本)9798350363074;9798350363081
In this paper, we present parallelo parallel Library (PPL), a novel Rust library for structured parallel programming. Rust's fearless concurrency concept makes it a promising language for parallel application development. We present the development progress of parallelo parallel Library (PPL) and report preliminary performance results, comparing it to existing popular Rust libraries. Our results show that PPL provides robust support for parallel programming through high-level abstractions, delivering performance that matches or exceeds current state-of-the-art in the Rust ecosystem.
We evaluate the applicability of many-core architectures for the simulation of networks on chips (NoC). Compared to the well established shared memory multi-core architectures, many-core architectures significantly di...
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ISBN:
(纸本)9781467387767
We evaluate the applicability of many-core architectures for the simulation of networks on chips (NoC). Compared to the well established shared memory multi-core architectures, many-core architectures significantly differ not only in the number of processing elements but also in the on-chip communication architecture, the memory subsystem, and the computational performance of an individual core. Proven multi-core simulation approaches do not consider such architectural aspects and thus suffer limited performance when being applied to many-core architectures. To enable high performance simulation, we identify conceptual drawbacks of state of the art parallel simulation approaches and consequently propose a novel globally asynchronous locally synchronous (GALS) simulation concept suited for many core architectures. Our results show that our GALS simulation approach yields a speedup of up to 2.3 over parallel discrete event simulation.
Checkpointing-Aided parallel Execution (CAPE) is a framework that is based on checkpointing technique and serves to automatically translates and execute OpenMP programs on distributed-memory architectures. Through som...
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ISBN:
(纸本)9781538649756
Checkpointing-Aided parallel Execution (CAPE) is a framework that is based on checkpointing technique and serves to automatically translates and execute OpenMP programs on distributed-memory architectures. Through some comparisons with MPI, CAPE has demonstrated high-performance and the potential for fully compatibility with OpenMP on distributed-memory systems. However, there is still a long way to improve the performance, flexibility, portability and capability. This paper presents the new execution model for CAPE that improves its performance and makes CAPE even more flexible.
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