Recent advances in high-speed networks, rapid improvements in microprocessor design, and availability of highly performing clustering software implementations enables cost-effective high-performance parallel computing on clustered low cost workstations and PCs. Such clusters are very attractive because they rely on available of the shelf hardware and software technologies. To simplify programming in network environments and to realize component-based software architectures, many models have emerged as possible standards, namely, RPC: Remote Procedure Call, DCE: Distributed Computing Environment, DCOM: Distributed Component Object Model, CORBA: Common Object Request Broker Architecture, PVM: Parallel Virtual Machine and MPI: Message Passing Interface. The MPI approach is considered one of the most mature methods currently used in parallel programming. MPI implementations on emerging cluster interconnects are an important requirement for useful parallel processing on cost-effective computer clusters. This paper offers an overview of different parallel computing environments and models. Functionality and performance of MPI running on homogeneous and heterogeneous workstation clusters are compared. The project goals, laboratory environment, performance measurements, future work, and a conclusion are presented.
Citation:
Ghassan Fadlallah, Michel Lavoie, Louis-A. Dessaint, "Parallel Computing Environments and Methods," parelec, pp.2, International Conference on Parallel Computing in Electrical Engineering (PARELEC'00), 2000