scholarly journals Branch and Bound Based Load Balancing for Parallel Applications

1999 ◽  
pp. 194-199 ◽  
Author(s):  
Shobana Radhakrishnan ◽  
Robert K. Brunner ◽  
Laxmikant V. Kalé
Keyword(s):  
Load Balancing ◽  
Branch And Bound ◽  
Parallel Applications

Periodic hierarchical load balancing for large supercomputers

2011 ◽  
Vol 25 (4) ◽  
pp. 371-385 ◽  
Author(s):  
Gengbin Zheng ◽  
Abhinav Bhatelé ◽  
Esteban Meneses ◽  
Laxmikant V. Kalé
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Parallel Machines ◽  
National Laboratory ◽  
Argonne National Laboratory ◽  
Parallel Applications ◽  
Scientific Application ◽  
Computing Center ◽  
Blue Gene ◽  
Advanced Computing

Large parallel machines with hundreds of thousands of processors are becoming more prevalent. Ensuring good load balance is critical for scaling certain classes of parallel applications on even thousands of processors. Centralized load balancing algorithms suffer from scalability problems, especially on machines with a relatively small amount of memory. Fully distributed load balancing algorithms, on the other hand, tend to take longer to arrive at good solutions. In this paper, we present an automatic dynamic hierarchical load balancing method that overcomes the scalability challenges of centralized schemes and longer running times of traditional distributed schemes. Our solution overcomes these issues by creating multiple levels of load balancing domains which form a tree. This hierarchical method is demonstrated within a measurement-based load balancing framework in Charm++. We discuss techniques to deal with scalability challenges of load balancing at very large scale. We present performance data of the hierarchical load balancing method on up to 16,384 cores of Ranger (at the Texas Advanced Computing Center) and 65,536 cores of Intrepid (the Blue Gene/P at Argonne National Laboratory) for a synthetic benchmark. We also demonstrate the successful deployment of the method in a scientific application, NAMD, with results on Intrepid.

scholarly journals A tool for simulating parallel branch-and-bound methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yana Golubeva ◽  
Yury Orlov ◽  
Mikhail Posypkin
Keyword(s):  
Load Balancing ◽  
Branch And Bound ◽  
Optimization Methods ◽  
Search Tree ◽  
Process Data ◽  
B Method ◽  
Logical Time ◽  
Parallel Branch And Bound ◽  
Important Research Topic ◽  
User Friendly

Abstract The Branch-and-Bound method is known as one of the most powerful but very resource consuming global optimization methods. Parallel and distributed computing can efficiently cope with this issue. The major difficulty in parallel B&B method is the need for dynamic load redistribution. Therefore design and study of load balancing algorithms is a separate and very important research topic. This paper presents a tool for simulating parallel Branchand-Bound method. The simulator allows one to run load balancing algorithms with various numbers of processors, sizes of the search tree, the characteristics of the supercomputer’s interconnect thereby fostering deep study of load distribution strategies. The process of resolution of the optimization problem by B&B method is replaced by a stochastic branching process. Data exchanges are modeled using the concept of logical time. The user friendly graphical interface to the simulator provides efficient visualization and convenient performance analysis.

Asymmetry-aware load balancing for parallel applications in single-ISA multi-core systems

2012 ◽  
Vol 13 (6) ◽  
pp. 413-427 ◽  
Author(s):  
Eunsung Kim ◽  
Hyeonsang Eom ◽  
Heon Y. Yeom
Keyword(s):  
Load Balancing ◽  
Parallel Applications

Resource-Aware Load Balancing of Parallel Applications

2009 ◽  
pp. 12-21 ◽  
Author(s):  
Eric Aubanel
Keyword(s):  
Load Balancing ◽  
Dynamic Network ◽  
Computational Grid ◽  
Parallel Applications ◽  
Computational Grids ◽  
Concurrent Execution ◽  
Processor Performance ◽  
Wide Range ◽  
Tightly Coupled ◽  
Resource Aware

The problem of load balancing parallel applications is particularly challenging on computational grids, since the characteristics of both the application and the platform must be taken into account. This chapter reviews the wide range of solutions that have been proposed. It considers tightly coupled parallel applications that can be described by an undirected graph representing concurrent execution of tasks and communication of tasks, executing on computational grids with static and dynamic network and processor performance. While a rich set of solution techniques have been proposed, there has not been of yet any performance comparisons between them. Such comparisons will require parallel benchmarks and computational grid emulators and simulators.

Non-Intrusive Data Collection for Load Balancing of Parallel Applications

2007 ◽  
pp. 147-153 ◽  
Author(s):  
Stanley Y. Chien ◽  
Gun Makinabakan ◽  
Akin Ecer ◽  
Hasan U. Akay
Keyword(s):  
Data Collection ◽  
Load Balancing ◽  
Parallel Applications
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