Sivarama P. Dandamudi

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Load sharing improves performance of distributed systems by distributing load from heavily-loaded nodes to lightly-loaded nodes in the system. We consider two basic dynamic load sharing policies: sender-initiated and receiver-initiated. In the sender-initiated policy, a heavily-loaded node attempts to transfer work to a lightly-loaded node and in the(More)
Multicomputer systems are distributed-memory The Cosmic Cube [25], the Finite Element Machine [20], the NCUBE/ten [13], and the Transputer system [30] are examples of multicomputer systems. The Butterfly Parallel Proces-'Or [513 the NYU U1tracomputer [l and the CEDAR system 191 are examples of multiprocessor systems. The IBM RP3 [23] is an example of a(More)
− Performance of distributed systems can be improved by load sharing (i.e., distributing load from heavily loaded nodes to lightly loaded ones). Dynamic load sharing policies take system state into account in making job distribution decisions. The state information can be maintained in one of two basic ways: distributed or centralized. Two examples of(More)
A simple fork and join type of job structure has been extensively used for performance evaluation of processor scheduling policies in multiprocessor systems. However, parallel programs often exhibit a more complicated structure. It is not clear how the program structure affects the performance of processor scheduling policies. This paper studies the impact(More)
In parallel systems it is possible for several processors to request concurrent access to a shared data structure such as a synchronization variable. Such an access pattern causes what is known as hot-spot contention. In shared-memory multiprocessor systems that use a multistage interconnection network, hot-spot contention may result in "tree saturation"(More)