A comparative study of black‐box optimization heuristics for online tuning of high performance computing I/O accelerators

Author(s):  
Sophie Robert ◽  
Soraya Zertal ◽  
Grégory Vaumourin ◽  
Philippe Couvée

2022 ◽  
Vol 21 ◽  
pp. 23-30
Author(s):  
E. M. Karanikolaou ◽  
M. P. Bekakos

The need for new and more reliable metrics is always in demand. In this paper, a new metric is proposed for the evaluation of high performance computing platforms in conjunction with their energy consumption. The aim of the new metric is to reliably compare different HPC systems concerning their energy efficiency. The metric provides a mean to rank supercomputers of similar capabilities, avoiding the misleading results of metrics like performance-per-watt, currently used for ranking systems, as in the Green500 list, where systems with totally different sizes and capabilities are ranked consecutively. An example of this misuse for two adjacent systems in the Green500 list, is discussed. A comparative study for the energy efficiency of three high performance computing platforms, with different architectures, using the proposed metric is presented.



Author(s):  
Aniruddha Marathe ◽  
Rachel Harris ◽  
David K. Lowenthal ◽  
Bronis R. de Supinski ◽  
Barry Rountree ◽  
...  


Author(s):  
Ranjit Rajak

The computer technologies have rapidly developed in both software and hardware field. The complexity of software is increasing as per the market demand because the manual systems are going to become automation as well as the cost of hardware is decreasing. High Performance Computing (HPC) is very demanding technology and an attractive area of computing due to huge data processing in many applications of computing. The paper focus upon different applications of HPC and the types of HPC such as Cluster Computing, Grid Computing and Cloud Computing. It also studies, different classifications and applications of above types of HPC. All these types of HPC are demanding area of computer science. This paper also done comparative study of grid, cloud and cluster computing based on benefits, drawbacks, key areas of research, characterstics, issues and challenges.



2018 ◽  
Author(s):  
Eric B. Gauch ◽  
Bruno E. C. Milanesi ◽  
Bruno Silva ◽  
Renato L. F. Cunha ◽  
Marco A. S. Netto

High Performance Computing (HPC) has always been a fundamental component to conduct scientific experiments. Model calibrations/simulations often require several executions of scientific applications by changing their input parameters. This process is a common practice in research even though it represents a tedious and error-prone task. In this paper we propose Copper framework which employs a black-box strategy and contains a set of plugins to accelerate user experiments for exploring search spaces in HPC parametric applications. Copper has been used to conduct scientific experiments in different areas including, agriculture, oil gas, flood simulation, and bioinformatics.





Author(s):  
Aniruddha Marathe ◽  
Rachel Harris ◽  
David K. Lowenthal ◽  
Bronis R. de Supinski ◽  
Barry Rountree ◽  
...  


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