Load Balancing in Parallel Computers: Theory and PracticeSpringer, 2007. gada 26. aug. - 210 lappuses Load 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. |
No grāmatas satura
1.5. rezultāts no 84.
xi. lappuse
... processors . An- other project of similar scale , also involving the DOE , will use a vast number of IBM's RS / 6000 processors to achieve a comparable performance . But parallel computing is not limited to massively parallel processing ...
... processors . An- other project of similar scale , also involving the DOE , will use a vast number of IBM's RS / 6000 processors to achieve a comparable performance . But parallel computing is not limited to massively parallel processing ...
xii. lappuse
... processors automatically during the execution of parallel programs . This book is about load balancing in distributed memory message - passing parallel computers , also called multicomputers . Each processor has its own address space ...
... processors automatically during the execution of parallel programs . This book is about load balancing in distributed memory message - passing parallel computers , also called multicomputers . Each processor has its own address space ...
xiii. lappuse
... processor's workload with those of its nearest neighbors one by one , and the most recently computed value is always used in the next equalization step . It is observed that " equal splitting " of workload between a pair of processors ...
... processor's workload with those of its nearest neighbors one by one , and the most recently computed value is always used in the next equalization step . It is observed that " equal splitting " of workload between a pair of processors ...
xiv. lappuse
... processors and a speedup of 146.8 in a system with 256 processors . These two methods give the best results among all the methods we tried . Organization Chapter 1 gives an overview of the load balancing problem , and presents a general ...
... processors and a speedup of 146.8 in a system with 256 processors . These two methods give the best results among all the methods we tried . Organization Chapter 1 gives an overview of the load balancing problem , and presents a general ...
3. lappuse
... processor read and to which they all write . The common memory system provides a simple shared memory pro- gramming abstraction but limits the scalability of parallel computers . By con- trast , a parallel computer with a distributed ...
... processor read and to which they all write . The common memory system provides a simple shared memory pro- gramming abstraction but limits the scalability of parallel computers . By con- trast , a parallel computer with a distributed ...
Saturs
| 1 | |
A SURVEY OF NEARESTNEIGHBOR LOAD BALANCING | 21 |
GDE ON TORI AND MESHES | 53 |
THE DIFFUSION METHOD | 79 |
TERMINATION DETECTION OF LOAD BALANCING | 121 |
REMAPPING WITH THE GDE METHOD | 136 |
GDE VERSUS DIFFUSION | 177 |
179 | 178 |
References | 187 |
Index | 201 |
32 | 206 |
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
ACWN all-port communication model applications balancing domains best-first best-first search branch-and-bound algorithms chain Chapter chromatic index circulant matrix color path combinatorial optimization communication steps computational graph convergence factor convergence rate counter value data parallel diffusion matrix diffusion method diffusive load balancing dimension exchange method edge colored edge-coloring edges efficiency eigenvalues execution Expected number Figure GDE-based global balanced global termination grid heap hypercube iteration step iteration sweeps k-ary n-cube k₁ k₂ Lemma load balancing algorithms load balancing operation load balancing procedure load balancing process load distribution lower bound nearest-neighbor neighbors nodes number of iterations number of processors number of sweeps optimal diffusion parameter optimal exchange parameter PACWN parallel branch-and-bound parallel computers Parsytec partitioning performance pixels PPBB PRAND processor RAND random remapping ring run-time speedup structures subproblem termination delay termination detection Theorem tori torus transputers unstructured grids vertex vertices workload variance α α
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