Load Balancing in Parallel Computers: Theory and PracticeLoad Balancing in Parallel Computers: Theory and Practice is about the essential software technique of load balancing in distributed memory message-passing parallel computers, also called multicomputers. Each processor has its own address space and has to communicate with other processors by message passing. In general, a direct, point-to-point interconnection network is used for the communications. Many commercial parallel computers are of this class, including the Intel Paragon, the Thinking Machine CM-5, and the IBM SP2. Load Balancing in Parallel Computers: Theory and Practice presents a comprehensive treatment of the subject using rigorous mathematical analyses and practical implementations. The focus is on nearest-neighbor load balancing methods in which every processor at every step is restricted to balancing its workload with its direct neighbours only. Nearest-neighbor methods are iterative in nature because a global balanced state can be reached through processors' successive local operations. Since nearest-neighbor methods have a relatively relaxed requirement for the spread of local load information across the system, they are flexible in terms of allowing one to control the balancing quality, effective for preserving communication locality, and can be easily scaled in parallel computers with a direct communication network. Load Balancing in Parallel Computers: Theory and Practice serves as an excellent reference source and may be used as a text for advanced courses on the subject. |
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Citi izdevumi - Skatīt visu
Load Balancing in Parallel Computers: Theory and Practice Chenzhong Xu,Francis C.M. Lau Ierobežota priekšskatīšana - 2007 |
Load Balancing in Parallel Computers Chenzhong Xu,Francis C. M. Lau Priekšskatījums nav pieejams - 2014 |
Load Balancing in Parallel Computers: Theory and Practice Chenzhong Xu,Francis C.M. Lau Priekšskatījums nav pieejams - 1997 |
Bieži izmantoti vārdi un frāzes
ACWN analysis applications balancing domains branch-and-bound algorithms chain Chapter chromatic index circulant matrix color path combinatorial optimization communication steps convergence factor convergence rate counter value data parallel denote diffusion matrix diffusion method diffusive load balancing dimension exchange method Distributed Computing distributed memory dynamic load balancing edge-coloring efficiency eigenvalues execution Figure first flow GDE method global balanced gossiping graph grid hypercube IEEE IEEE Transactions initial workload distribution iteration step iteration sweeps k-ary n-cube Lemma load balancing algorithms load balancing operation load balancing procedure load balancing process load distribution load sharing loaded processors memory computers mesh migration multicomputers networks nodes number of iterations one-port optimal exchange parameter Parallel and Distributed parallel branch-and-bound parallel computers Parsytec partitioning performance random remapping ring rithms run-time simulated annealing simulation speedup strategies structures subproblem synchronous implementations termination detection Theorem tori torus transputers unstructured grids vertex vertices workload information workload variance