scholarly journals A Hybrid CPU-GPU-MIC Algorithm for the Hitting Set Problem

2017 ◽  
Author(s):  
Danilo Carastan-Santos ◽  
David C. Martins-Jr ◽  
Luiz C. S. Rozante ◽  
Siang W. Song ◽  
Raphael Y. de Camargo
Keyword(s):  
Load Balancing ◽  
High Performance Computing ◽  
High Performance ◽  
Exact Algorithm ◽  
Communication Cost ◽  
Heterogeneous Clusters ◽  
Hitting Set ◽  
Reasonable Time ◽  
Performance Computing ◽  
Hitting Set Problem

We present a hybrid exact algorithm for the Hitting Set Problem (HSP) for highly heterogeneous CPU-GPU-MIC platforms. With several techniques that permit an efficient exploitation of each architecture, low communication cost and effective load balancing, we were able to solve large HSP instances in reasonable time, achieving good performance and scalability. We obtained speedups of up to 25.32 in comparison with using two six-core CPUs and exact HSP solutions for instances with tens of thousands of variables in less than 5 hours. These results reinforce the statement that heterogeneous clusters of CPUs, GPUs and MICs can be used efficiently for high-performance computing.

scholarly journals Service Oriented Load Balancing Framework in Computational Grid Environment

2013 ◽  
Vol 9 (3) ◽  
pp. 1091-1098 ◽  
Author(s):  
Sukalyan Goswami ◽  
Ajanta De Sarkar
Keyword(s):  
Load Balancing ◽  
Grid Computing ◽  
High Performance Computing ◽  
Resource Sharing ◽  
High Performance ◽  
Computational Grid ◽  
Computing Systems ◽  
Grid Systems ◽  
Service Oriented ◽  
Performance Computing

Grid computing or computational grid has become a vast research field in academics. It is a promising platform that provides resource sharing through multi-institutional virtual organizations for dynamic problem solving. Such platforms are much more cost-effective than traditional high performance computing systems. Due to the provision of scalability of resources, these days grid computing has become popular in industry as well. However, computational grid has different constraints and requirements to those of traditional high performance computing systems. In order to fully exploit such grid systems, resource management and scheduling are key challenges, where issues of task allocation and load balancing represent a common problem for most grid systems as because the load scenarios of individual grid resources are dynamic in nature. The objective of this paper is to review different existing load balancing algorithms or techniques applicable in grid computing and propose a layered service oriented framework for computational grid to solve the prevailing problem of dynamic load balancing.

scholarly journals A DAQM-Based Load Balancing Scheme for High Performance Computing Platforms

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 22504-22513 ◽  
Author(s):  
Kaijun Yang ◽  
Meng Li ◽  
Guchuan Zhu ◽  
Yvon Savaria
Keyword(s):  
Load Balancing ◽  
High Performance Computing ◽  
High Performance ◽  
Computing Platforms ◽  
Performance Computing

scholarly journals “Cool” Load Balancing for High Performance Computing Data Centers

2012 ◽  
Vol 61 (12) ◽  
pp. 1752-1764 ◽  
Author(s):  
Osman Sarood ◽  
Phil Miller ◽  
Ehsan Totoni ◽  
Laxmikant V. Kal
Keyword(s):  
Load Balancing ◽  
High Performance Computing ◽  
High Performance ◽  
Data Centers ◽  
Cool Load ◽  
Performance Computing

scholarly journals Representing Increasing Virtual Machine Security Strategy in Cloud Computing Computations

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Mohammad Shirzadi
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Load Balancing ◽  
High Performance Computing ◽  
Virtual Machine ◽  
Lower Energy ◽  
High Performance ◽  
Security Strategy ◽  
Cloud Processing ◽  
Performance Computing

This paper proposes algorithm for Increasing Virtual Machine Security Strategy in Cloud Computing computations. Imbalance between load and energy has been one of the disadvantages of old methods in providing server and hosting, so that if two virtual severs be active on a host and energy load be more on a host, it would allocated the energy of other hosts (virtual host) to itself to stay steady and this option usually leads to hardware overflow errors and users dissatisfaction. This problem has been removed in methods based on cloud processing but not perfectly, therefore,providing an algorithm not only will implement a suitable security background but also it will suitably divide energy consumption and load balancing among virtual severs. The proposed algorithm is compared with several previously proposed Security Strategy including SC-PSSF, PSSF and DEEAC. Comparisons show that the proposed method offers high performance computing, efficiency and consumes lower energy in the network.

The Recent Revolution in High Performance Computing

MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 5-6
Author(s):  
Horst D. Simon
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
New Technologies ◽  
New Technology ◽  
Parallel Architecture ◽  
Time Frame ◽  
Good News ◽  
Computing Industry ◽  
Time And Energy ◽  
Performance Computing

Recent events in the high-performance computing industry have concerned scientists and the general public regarding a crisis or a lack of leadership in the field. That concern is understandable considering the industry's history from 1993 to 1996. Cray Research, the historic leader in supercomputing technology, was unable to survive financially as an independent company and was acquired by Silicon Graphics. Two ambitious new companies that introduced new technologies in the late 1980s and early 1990s—Thinking Machines and Kendall Square Research—were commercial failures and went out of business. And Intel, which introduced its Paragon supercomputer in 1994, discontinued production only two years later.During the same time frame, scientists who had finished the laborious task of writing scientific codes to run on vector parallel supercomputers learned that those codes would have to be rewritten if they were to run on the next-generation, highly parallel architecture. Scientists who are not yet involved in high-performance computing are understandably hesitant about committing their time and energy to such an apparently unstable enterprise.However, beneath the commercial chaos of the last several years, a technological revolution has been occurring. The good news is that the revolution is over, leading to five to ten years of predictable stability, steady improvements in system performance, and increased productivity for scientific applications. It is time for scientists who were sitting on the fence to jump in and reap the benefits of the new technology.

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