TY - JOUR
T1 - Why parallel computer processing systems are preferred to serial computer processing systems
T2 - A formal discussion
AU - Konigsberg, Zvi Retchkiman
PY - 2011
Y1 - 2011
N2 - Serial computer processing systems are characterized by the fact of executing software using a single central processing unit (CPU) while parallel computer processing systems simultaneously use multiple CPU's at the time. Parallel computer processing systems are an evolution of serial computer processing systems that attempt to emulate what has always been the state of affairs in the natural world: many complex, interrelated events happening at the same time, yet within a sequence. Today, commercial applications provide an equal or greater driving force in the development of faster computers. These applications require the processing of large amounts of data. Some of the arguments which have been used to say why it is better parallel than serial are: save time and/or money, solve larger problems. Besides that there are physical and economical limits to serial computer processing systems. However we would like to be more precise and give a definitive and unquestionable formal proof to justify the claim that parallel computer processing systems are better than serial processing systems. The main objective and contribution of this paper consists in using a formal and mathematical approach to prove that parallel computer processing systems are better than serial computer processing systems (better related to: saving time and/or money and being able to solve larger problems). This is achieved thanks to the theory of Lyapunov stability and max-plus algebra applied to discrete event systems modeled with time Petri nets.
AB - Serial computer processing systems are characterized by the fact of executing software using a single central processing unit (CPU) while parallel computer processing systems simultaneously use multiple CPU's at the time. Parallel computer processing systems are an evolution of serial computer processing systems that attempt to emulate what has always been the state of affairs in the natural world: many complex, interrelated events happening at the same time, yet within a sequence. Today, commercial applications provide an equal or greater driving force in the development of faster computers. These applications require the processing of large amounts of data. Some of the arguments which have been used to say why it is better parallel than serial are: save time and/or money, solve larger problems. Besides that there are physical and economical limits to serial computer processing systems. However we would like to be more precise and give a definitive and unquestionable formal proof to justify the claim that parallel computer processing systems are better than serial processing systems. The main objective and contribution of this paper consists in using a formal and mathematical approach to prove that parallel computer processing systems are better than serial computer processing systems (better related to: saving time and/or money and being able to solve larger problems). This is achieved thanks to the theory of Lyapunov stability and max-plus algebra applied to discrete event systems modeled with time Petri nets.
KW - Lyapunov methods
KW - Max-plus algebra
KW - Parallel and serial computer processing systems
KW - Timed petri nets
UR - http://www.scopus.com/inward/record.url?scp=79959359543&partnerID=8YFLogxK
M3 - Artículo
SN - 1311-8080
VL - 70
SP - 329
EP - 347
JO - International Journal of Pure and Applied Mathematics
JF - International Journal of Pure and Applied Mathematics
IS - 3
ER -