6 research outputs found
HPC as a Service: A naive model
Applications like Big Data, Machine Learning, Deep Learning and even other
Engineering and Scientific research requires a lot of computing power; making
High-Performance Computing (HPC) an important field. But access to
Supercomputers is out of range from the majority. Nowadays Supercomputers are
actually clusters of computers usually made-up of commodity hardware. Such
clusters are called Beowulf Clusters. The history of which goes back to 1994
when NASA built a Supercomputer by creating a cluster of commodity hardware. In
recent times a lot of effort has been done in making HPC Clusters of even
single board computers (SBCs). Although the creation of clusters of commodity
hardware is possible but is a cumbersome task. Moreover, the maintenance of
such systems is also difficult and requires special expertise and time. The
concept of cloud is to provide on-demand resources that can be services,
platform or even infrastructure and this is done by sharing a big resource
pool. Cloud computing has resolved problems like maintenance of hardware and
requirement of having expertise in networking etc. An effort is made of
bringing concepts from cloud computing to HPC in order to get benefits of
cloud. The main target is to create a system which can develop a capability of
providing computing power as a service which to further be referred to as
Supercomputer as a service. A prototype was made using Raspberry Pi (RPi) 3B
and 3B+ Single Board Computers. The reason for using RPi boards was increasing
popularity of ARM processors in the field of HPCComment: 2019 8th International Conference on Information and Communication
Technologies (ICICT), Karachi, Pakistan, 201
Applications and Algorithms for Inference of Huge Phylogenetic Trees: a Review
Abstract Phylogenetics enables us to use various techniques to extract evolutionary relationships from sequence analysis. Most of the phylogenetic analysis techniques produce phylogenetic trees that represent relationship between any set of species or their evolutionary history. This article presents a comprehensive survey of the applications and the algorithms for inference of huge phylogenetic trees and also gives the reader an overview of the methods currently employed for the inference of phylogenetic trees. A comprehensive comparison of the methods and algorithms is presented in this paper
Compatibility of objective functions with simplex algorithm for controller tuning of hvdc system
This work aims to tune multiple controllers at the same time for a HVDC system by using a self-generated (SG) simulation-based optimization technique. Online optimization is a powerful tool to improve performance of the system. Proportion integral (PI) controllers of Multi-infeed HVDC systems are optimized by the evaluation of objective functions in time simulation design (TSD). Model based simulation setup is applied for rapid selection of optimal PI control parameters, designed in PSCAD software. A multiple objective function (OF), i.e. Integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), integral time square error (ITSE), and integral square time error (ISTE), is assembled for testing the compatibility of OFs with nonlinear self-generated simplex algorithm (SS-SA). Improved control parameters are achieved after multiple iterations. All OFs generate optimum responses and their results are compared with each other by their minimized numerical values. Disturbance rejection criteria are also proposed to assess the designed controller performance along with robustness of system. Results are displayed in form of graphs and tables in this paper