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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1.5. rezultāts no 30.
vi. lappuse
4.3.4 Improvements due to the Optimal Parameters 5 THE DIFFUSION METHOD 5.1 5.2 5.3 5.4 5.5 The Diffusion Method . . . . . . . . . . . . . . . . . . . . . . . . Diffusion Method on n-Dimensional Tori .
4.3.4 Improvements due to the Optimal Parameters 5 THE DIFFUSION METHOD 5.1 5.2 5.3 5.4 5.5 The Diffusion Method . . . . . . . . . . . . . . . . . . . . . . . . Diffusion Method on n-Dimensional Tori .
xii. lappuse
Load balancing aims at improving the performance of parallel computers by equalizing the workloads of processors automatically during the execution of parallel programs. This book is about load balancing in distributed memory ...
Load balancing aims at improving the performance of parallel computers by equalizing the workloads of processors automatically during the execution of parallel programs. This book is about load balancing in distributed memory ...
xiii. lappuse
Through statistical simulation, we show significant improvements due to the optimal exchange and the diffusion parameters. Furthermore, we analyze the dimension exchange and the diffusion method in different workload models and system ...
Through statistical simulation, we show significant improvements due to the optimal exchange and the diffusion parameters. Furthermore, we analyze the dimension exchange and the diffusion method in different workload models and system ...
xiv. lappuse
The experimental results show that GDE-based remapping leads to substantial improvements in execution time for both cases. The GDE method is also implemented for parallel partitioning of unstructured finite-element graphs.
The experimental results show that GDE-based remapping leads to substantial improvements in execution time for both cases. The GDE method is also implemented for parallel partitioning of unstructured finite-element graphs.
2. lappuse
... the most critical considerations in parallel programming, automatic parallelization, and run-time resource management. It aims at improving the performance of parallel computers by scheduling users' tasks appropriately on processors ...
... the most critical considerations in parallel programming, automatic parallelization, and run-time resource management. It aims at improving the performance of parallel computers by scheduling users' tasks appropriately on processors ...
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Saturs
| 1 | |
A SURVEY OF NEARESTNEIGHBOR LOAD BALANCING | 21 |
GDE ON TORIAND MESHES | 53 |
THE DIFFUSION METHOD | 79 |
TERMINATION DETECTION OF LOAD BALANCING | 121 |
REMAPPING WITH THE GDE METHOD | 136 |
CONCLUSIONS | 178 |
References | 187 |
13 | 188 |
Citi izdevumi - Skatīt visu
Load Balancing in Parallel Computers: Theory and Practice Chenzhong Xu,Francis C.M. Lau Ierobežota priekšskatīšana - 1996 |
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
according analysis applications assume average bound branch-and-bound Chapter color combinatorial optimization communication communication model compared consider convergence rate cost counter denote dependent derived diffusion method diffusion parameter dimension exchange method direct domain dynamic edges efficiency eigenvalues equal example execution exists expected experiments factor Figure given global gossiping graph grid Hence idle implementation improvement initial iteration Lemma load balancing algorithms load balancing operation load distribution matrix memory mesh messages n-dimensional nearest-neighbor necessary neighbors nodes obtain optimal exchange parameter parallel computers partitioning path performance phase practical present problem procedure processor Proof random remapping respectively ring rule running shows simulation static step strategies structures subproblem sweeps synchronous Table takes termination detection Theorem thinning tion tori torus transfer various vertices workload workload distribution workload variance
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Bibliogrāfiskā informācija
| Nosaukums | Load Balancing in Parallel Computers: Theory and Practice Grāmatas The Springer International Series in Engineering and Computer Science 381. sējums. sējums |
| Autori | Chenzhong Xu, Francis C.M. Lau |
| Izdevums: | ilustrēts |
| Izdevējs | Springer, 2007 |
| ISBN | 0585272565, 9780585272566 |
| Apjoms | 210 lappuses |
| Eksportēt avotu | BiBTeX EndNote RefMan |