Calculating matrixes in parallel code
This material focuses on the question of whether there is currently the necessary architectural support, provided by hardware for the efficient execution of virtual machines used in High Performance Computing (HPC). The High Performance Computing (HPC) technique has evolved as there has been an incr...
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nemertes-10889-241612022-12-13T04:38:19Z Calculating matrixes in parallel code Υπολογισμός πινάκων με παράλληλο κώδικα Κλαδής, Διονύσης Kladis, Dionysis High performance computing (HPC) Hypervisors Υπολογιστές υψηλής απόδοσης Εικονικές μηχανές This material focuses on the question of whether there is currently the necessary architectural support, provided by hardware for the efficient execution of virtual machines used in High Performance Computing (HPC). The High Performance Computing (HPC) technique has evolved as there has been an increase in computing power demand. This is related to the development of technology and complex research work that leads to an increase in the need for rapid calculations. The technique of High Performance Computing (HPC) is increasingly used in all kinds of fields of science and beyond. Today, in all aspects of science, it takes a huge amount of time to solve scientific problems. So sustainable computer supercomputers, on the other hand, are very expensive to build and monitor. Virtual machine technology is a field with ongoing research even today. Despite the industry’s current focus on architectural support on current software and hardware platforms, we believe that some historical perspective is needed to address the problem properly. The first half of this paper provides a historical perspective and theoretical framework developed five decades ago by major leading companies in the field. It also describes older systems and applications that defined modern virtual machine development and High Performance Computing (HPC) techniques. As is often the case in active and rapidly evolving fields such as information technology, theory defines some necessary but not sufficient features. Therefore current architecture is the result of combining the theoretical framework with the ideas derived from real applications in these systems. The second half of the paper describes the steps we have taken to utilize the technology of virtual machines relying on the technique of High Performance Computing (HPC), with the specific way of implementing, where the Hypervisors act as graphical terminals for one of the virtual operating systems for possible use in common areas and production scenarios. This material presents a such use case on our implemented infrastructure, we have created in python a matrix calculation code in parrallel and in sequential modes and executing them through in our local computer and at the cluster. It compares performance times of execution times through a test code for the Cluster test of High Performance Computing (HPC) virtual machines. In conclusion, the performance of the computer farm platform is checked by comparing the execution times and data processing speeds in High Performance Computing (HPC) Cluster when utilizing the full capabilities of processors in Hypervisors. Finally, the process and the data collected are reviewed and concluded by reviewing the results and proposing possible improvements. 2022-12-12T06:39:30Z 2022-12-12T06:39:30Z 2022-11-25 https://hdl.handle.net/10889/24161 en Attribution-ShareAlike 3.0 United States http://creativecommons.org/licenses/by-sa/3.0/us/ application/pdf |
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UPatras |
collection |
Nemertes |
language |
English |
topic |
High performance computing (HPC) Hypervisors Υπολογιστές υψηλής απόδοσης Εικονικές μηχανές |
spellingShingle |
High performance computing (HPC) Hypervisors Υπολογιστές υψηλής απόδοσης Εικονικές μηχανές Κλαδής, Διονύσης Calculating matrixes in parallel code |
description |
This material focuses on the question of whether there is currently the necessary architectural
support, provided by hardware for the efficient execution of virtual machines
used in High Performance Computing (HPC). The High Performance Computing (HPC)
technique has evolved as there has been an increase in computing power demand. This
is related to the development of technology and complex research work that leads to an
increase in the need for rapid calculations. The technique of High Performance Computing
(HPC) is increasingly used in all kinds of fields of science and beyond. Today,
in all aspects of science, it takes a huge amount of time to solve scientific problems. So
sustainable computer supercomputers, on the other hand, are very expensive to build and
monitor. Virtual machine technology is a field with ongoing research even today. Despite
the industry’s current focus on architectural support on current software and hardware
platforms, we believe that some historical perspective is needed to address the problem
properly.
The first half of this paper provides a historical perspective and theoretical framework
developed five decades ago by major leading companies in the field. It also describes
older systems and applications that defined modern virtual machine development and
High Performance Computing (HPC) techniques. As is often the case in active and rapidly
evolving fields such as information technology, theory defines some necessary but not
sufficient features. Therefore current architecture is the result of combining the theoretical
framework with the ideas derived from real applications in these systems.
The second half of the paper describes the steps we have taken to utilize the technology of
virtual machines relying on the technique of High Performance Computing (HPC), with
the specific way of implementing, where the Hypervisors act as graphical terminals for
one of the virtual operating systems for possible use in common areas and production
scenarios. This material presents a such use case on our implemented infrastructure, we
have created in python a matrix calculation code in parrallel and in sequential modes and
executing them through in our local computer and at the cluster. It compares performance
times of execution times through a test code for the Cluster test of High Performance
Computing (HPC) virtual machines.
In conclusion, the performance of the computer farm platform is checked by comparing
the execution times and data processing speeds in High Performance Computing (HPC)
Cluster when utilizing the full capabilities of processors in Hypervisors. Finally, the
process and the data collected are reviewed and concluded by reviewing the results and
proposing possible improvements. |
author2 |
Kladis, Dionysis |
author_facet |
Kladis, Dionysis Κλαδής, Διονύσης |
author |
Κλαδής, Διονύσης |
author_sort |
Κλαδής, Διονύσης |
title |
Calculating matrixes in parallel code |
title_short |
Calculating matrixes in parallel code |
title_full |
Calculating matrixes in parallel code |
title_fullStr |
Calculating matrixes in parallel code |
title_full_unstemmed |
Calculating matrixes in parallel code |
title_sort |
calculating matrixes in parallel code |
publishDate |
2022 |
url |
https://hdl.handle.net/10889/24161 |
work_keys_str_mv |
AT kladēsdionysēs calculatingmatrixesinparallelcode AT kladēsdionysēs ypologismospinakōnmeparallēlokōdika |
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