| Summary: | 碩士 === 逢甲大學 === 資訊工程研究所 === 85 ===
A Massively Parallel Processing (MPP) computer system is a computer system supporting large computation capacity. In the distributed-memory MPPcomputer system, the commumication among nodes are through message passing. Therefore, the message-passing InterProcess Communication (IPC) mechanism is a key issue to the performance of MPP computer systems. In addition to the point-to-point communication type group communication, including broadcast and multicast communication types, are also desired in the programs on a MPP computer system. The group communication can conveniently and efficiently support the communication among multiple processes. This thesis is to research the group IPC mechanism for a MPP computer system and implement this mechanism under a distributed environment.
The design issues for a group IPC mechanism include two aspects: the system architecture of group IPC and the group communication mechanism. The issue about system architecture of group IPC considers how to create/manage the groups and group members, and the organization of the group IPC management system. The issue about of communication mechanism of group IPC considers how to transmit messages and the transmission quality of messages. The proposed group IPC communication system has the following features:(1) It is easy to maintain and manage the information about groups and group members. (2) It is location transparent. (3) By using communication port technique, the port technique, the problem of group overlap is solved. (4) By using a hierarchical point-to-point communication structure, a better communication performance can be cotained. (5) A kernel-level library interface for U-Port B-Port and M-Port is provided to both system programs and applications.
We have successively implemented a MPP communication server, called mppnetmsgserver, on Mach microkernel. The mppnetmsgserver extends Mach IPC to network capability and provides broadcast and multicast communications. This server will be useful for programmers of both parallel processing and distributed computing.
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