Hierarchical Scheduling in Parallel and Cluster Systems

Pirmais vāks
Springer Science & Business Media, 2012. gada 6. dec. - 251 lappuses
Multiple processor systems are an important class of parallel systems. Over the years, several architectures have been proposed to build such systems to satisfy the requirements of high performance computing. These architectures span a wide variety of system types. At the low end of the spectrum, we can build a small, shared-memory parallel system with tens of processors. These systems typically use a bus to interconnect the processors and memory. Such systems, for example, are becoming commonplace in high-performance graph ics workstations. These systems are called uniform memory access (UMA) multiprocessors because they provide uniform access of memory to all pro cessors. These systems provide a single address space, which is preferred by programmers. This architecture, however, cannot be extended even to medium systems with hundreds of processors due to bus bandwidth limitations. To scale systems to medium range i. e. , to hundreds of processors, non-bus interconnection networks have been proposed. These systems, for example, use a multistage dynamic interconnection network. Such systems also provide global, shared memory like the UMA systems. However, they introduce local and remote memories, which lead to non-uniform memory access (NUMA) architecture. Distributed-memory architecture is used for systems with thousands of pro cessors. These systems differ from the shared-memory architectures in that there is no globally accessible shared memory. Instead, they use message pass ing to facilitate communication among the processors. As a result, they do not provide single address space.

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List of Tables
1
PARALLEL AND CLUSTER SYSTEMS
13
PARALLEL JOB SCHEDULING
49
11
62
13
68
16
74
19
82
HIERARCHICAL TASK QUEUE ORGANIZATION
87
PERFORMANCE OF SCHEDULING POLICIES
121
PERFORMANCE WITH SYNCHRONIZATION
141
21
144
SCHEDULING IN SHAREDMEMORY
167
SCHEDULING IN DISTRIBUTEDMEMORY
193
SCHEDULING IN CLUSTER SYSTEMS
213
22
240
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