A Multi-Objective GRASP for Energy-aware Scheduling

in International Congress on Computer Science Research (2011, October 28)

An overview of energy efficiency techniques in cluster computing systems

in Cluster Computing (2011), 16(1), 3-15

Scalable and Energy-Efficient Scheduling Techniques for Large-Scale Systems

in Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on (2011)

The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids ... [more ▼]

The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids, and clusters bring in more parameters to the aforementioned list, namely heterogeneity, energy consumption, and transparency. To optimize the per- formance of a computing system, it is manner that exploits heterogeneity and is scalable. Moreover, newer systems also demand energy efficiency as an integral part of schedulers. In this paper, we evaluate the behavior of low complexity energy- efficient algorithms for scheduling. The set of experimental results showed that the evaluated heuristics perform as effi- ciently as related approaches; demonstrating their applicability and scalability for the considered problem. [less ▲]

Energy-efficient scheduling on milliclusters with performance constraints

in Green Computing and Communications (GreenCom), 2011 IEEE/ACM International Conference on (2011)

Today’s datacenters and large scale enterprise com- puting are power hungry. A lot of research effort is devoted in industry and academy to address this challenging issue. In this context, a new type of ... [more ▼]

Today’s datacenters and large scale enterprise com- puting are power hungry. A lot of research effort is devoted in industry and academy to address this challenging issue. In this context, a new type of enterprise computing platform is being investigated. This computing platform is composed of hundred of millicomputers, each requiring orders of magnitude less power. However, this approach brings challenges that must be met in order to compete with the current practice. This paper addresses two such critical challenges. First, it suggests how to decompose large applications into smaller tasks, better suited to millicomputers. Then, it casts the performance oriented and energy efficient problem into a soft real-time scheduling problem, for which several algorithms are then proposed and evaluated. Sensitivity analysis is used to provide insights into the model, and plan the evaluation of the scheduling algorithms. The contention found in multi-core millicomputing processors is also accounted for. [less ▲]

Efficient Hierarchical Task Scheduling on GRIDS Accounting for Computation and Communications

in Bouvry, Pascal; González-Vélez, Horacio; Kolodziej, Joanna (Eds.) Intelligent Decision Systems in Large-Scale Distributed Environments, 362 (2011)

Memory-aware Green Scheduling on Multi-core Processors

in Proceedings of the Second International Workshop on Green Computing (2010, September 16)

Contention on shared resources such as cache and main memory slows down the execution of the applications affecting not only application performance but also induces inefficient use of energy. Therefore ... [more ▼]

Contention on shared resources such as cache and main memory slows down the execution of the applications affecting not only application performance but also induces inefficient use of energy. Therefore, in this paper we deal with the contention problem and energy optimization on shared resources multicore-based machines. Our main contribution is a memory-aware resource allocation algorithm that minimize energy consumption by reducing contention conflicts and maximizing performance. We design a heuristic that includes in its objective function the impact of the contention on the application performance. Experimental results emphasize the interest of the provided solution. [less ▲]

An improved genetic algorithm for efficient scheduling on distributed memory parallel systems

in ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010 (2010, May 19)

A key issue related to the distributed memory multiprocessors architecture for achieving high performance computing is the efficient scheduling of heavily communicated parallel applications such that the ... [more ▼]

A key issue related to the distributed memory multiprocessors architecture for achieving high performance computing is the efficient scheduling of heavily communicated parallel applications such that the total execution time is minimized. Therefore, this paper provides a genetic algorithm based on task clustering techniques for scheduling parallel applications with large communication delays on distributed memory parallel systems. The genetic algorithm is improved with the introduction of some extra knowledge about the scheduling problem. This knowledge is represented by a class of clustering heuristic which is based on structural properties of the parallel application. The major feature of the proposed algorithm is that it takes advantage of the effectiveness of task clustering for reducing communication delays combined with the ability of the genetic algorithms for exploring and exploiting information of the search space of the scheduling problem. The algorithm is assessed by simulation run on some families of traced graphs which represents some of the numerical parallel application programs, and a set of randomly generated applications. Simulation results showed that this algorithm significantly improves the performance of related approaches. [less ▲]

Scheduling with uncertainties on new computing platforms

in Computational Optimization and Applications (2010), 48(2), 369-398

New distributed computing platforms (grids) are based on interconnections of a large number of processing elements. A most important issue for their effective utilization is the optimal use of resources ... [more ▼]

New distributed computing platforms (grids) are based on interconnections of a large number of processing elements. A most important issue for their effective utilization is the optimal use of resources through proper task scheduling. It consists of allocating the tasks of a parallel program to processors on the platform and to determine at what time the tasks will start their execution. As data may be subject to uncertainties or disturbances, it is practically impossible to precisely predict the input parameters of the task scheduling problem. We briefly survey existing approaches for dealing with data uncertainties and discuss their relevance in the context of grid computing. We describe the stabilization process and analyze a scheduling algorithm that is intrinsically stable (i.e., it mitigates the effects of disturbances in input data at runtime). This algorithm is based on a decomposition of the application graph into convex sets of vertices. Finally, it is compared experimentally to pure on-line and well-known off-line algorithms. [less ▲]

A New Genetic Algorithm for Scheduling for Large Communication Delays

in 15th International Euro-Par Conference (2009, August 28)

In modern parallel and distributed systems, the time for exchanging data is usually larger than that for computing elementary operations. Consequently, these communications slow down the execution of the ... [more ▼]

In modern parallel and distributed systems, the time for exchanging data is usually larger than that for computing elementary operations. Consequently, these communications slow down the execution of the application scheduled on such systems. Accounting for these communications is essential for attaining efficient hardware and software utilization. Therefore, we provide in this paper a new combined approach for scheduling parallel applications with large communication delays on an arbitrary number of processors. In this approach, a genetic algorithm is improved with the introduction of some extra knowledge about the scheduling problem. This knowledge is represented by a class of clustering algorithms introduced recently, namely, convex clusters which are based on structural properties of the parallel applications. The developed algorithm is assessed by simulations run on some families of synthetic task graphs and randomly generated applications. The comparison with related approaches emphasizes its interest. [less ▲]