Browsing by Author "Elsevier Inc., publisher"

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Open Access
A semi-static approach to mapping dynamic iterative task onto heterogeneous computing systems
(Colorado State University. Libraries, 2006) Maciejewski, Anthony A., author; Ahmad, Ishfaq, author; Siegel, Howard Jay, author; Kwok, Yu-Kwong, author; Ghafoor, Arif, author; Elsevier Inc., publisher
Minimization of the execution time of an iterative application in a heterogeneous parallel computing environment requires an appropriate mapping scheme for matching and scheduling the subtasks of a given application onto the processors. Often, some of the characteristics of the application subtasks are unknown a priori or change from iteration to iteration during execution-time based on the inputs being processed. In such a scenario, it may not be feasible to use the same off-line-derived mapping for each iteration of the application. One possibility is to employ a semi-static methodology that starts with an initial mapping but dynamically performs remapping between application iterations by observing the effects of the changing characteristics of the application's input data, called dynamic parameters, on the application's execution time. A contribution in this paper is to implement and evaluate a semi-static methodology involving the on-line use of off-line-derived mappings. The off-line phase is based on a genetic algorithm (GA) to generate high-quality mappings for a range of values for the dynamic parameters. A dynamic parameter space partitioning and sampling scheme is proposed that partitions the parameter space into a number of hyper-rectangles, within which the "best" mapping for each hyper-rectangle is stored in a mapping table. During the on-line phase, the actual dynamic parameters are observed and the off-line-derived mapping table is referenced to choose the most suitable mapping. Experimental results indicate that the semi-static approach outperforms a dynamic on-line approach and performs reasonably close to an infeasible on-line GA approach. Furthermore, the semi-static approach considerably outperforms the method of using the same mapping for all iterations.
Open Access
Characterizing resource allocation heuristics for heterogeneous computing systems
(Colorado State University. Libraries, 2005) Yao, Bin, author; Theys, Mitchell D., author; Robertson, James P., author; Reuther, Albert I., author; Maheswaran, Muthucumaru, author; Bölöni, Ladislau, author; Beck Noah, author; Maciejewski, Anthony A., author; Siegel, Howard Jay, author; Braun, Tracy D., author; Ali, Shoukat, author; Elsevier Inc., publisher
In many distributed computing environments, collections of applications need to be processed using a set of heterogeneous computing (HC) resources to maximize some performance goal. An important research problem in these environments is how to assign resources to applications (matching) and order the execution of the applications (scheduling) so as to maximize some performance criterion without violating any constraints. This process of matching and scheduling is called mapping. To make meaningful comparisons among mapping heuristics, a system designer needs to understand the assumptions made by the heuristics for (1) the model used for the application and communication tasks, (2) the model used for system platforms, and (3) the attributes of the mapping heuristics. This chapter presents a three-part classification scheme (3PCS) for HC systems. The 3PCS is useful for researchers who want to (a) understand a mapper given in the literature, (b) describe their design of a mapper more thoroughly by using a common standard, and (c) select a mapper to match a given real-world environment.
Open Access
Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment
(Colorado State University. Libraries, 2006) Yellampalli, Siva Sankar, author; Vangari, Praveen, author; Sripada, Siddhartha, author; Sharma, Ashish, author; Kaul, Aditya, author; Joshi, Rohit, author; Dilmaghani, Raheleh B., author; Chitta, Ramakrishna, author; Tideman, Sonja, author; Schneider, Myron, author; Braun, Tracy D., author; Maciejewski, Anthony A., author; Siegel, Howard Jay, author; Shivle, Sameer, author; Kim, Jong-Kook, author; Elsevier Inc., publisher
In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is essential to assign the resources to tasks (match) and order the execution of tasks on each resource (schedule) to exploit the heterogeneity of the resources and tasks. Dynamic mapping (defined as matching and scheduling) is performed when the arrival of tasks is not known a priori. In the heterogeneous environment considered in this study, tasks arrive randomly, tasks are independent (i.e., no inter-task communication), and tasks have priorities and multiple soft deadlines. The value of a task is calculated based on the priority of the task and the completion time of the task with respect to its deadlines. The goal of a dynamic mapping heuristic in this research is to maximize the value accrued of completed tasks in a given interval of time. This research proposes, evaluates, and compares eight dynamic mapping heuristics. Two static mapping schemes (all arrival information of tasks are known) are designed also for comparison. The performance of the best heuristics is 84% of a calculated upper bound for the scenarios considered.
Open Access
Endangered species and biodiversity (Encyclopedia of the Anthropocene)
(Colorado State University. Libraries, 2018) Rolston, Holmes, 1932-2025, author; Elsevier Inc., publisher
Anthropocene enthusiasts assert the dominant human place in nature, conservation policy, and the biosphere, with plans for managing, even re-engineering the planet. This worldview de-emphasizes the goal of protecting nature for its own sake in favor of protecting and revising the environment for benefits to humans. But this preserves endangered species only so far as they promise benefits for humans. Environmental ethicists raise concerns that this effort to go beyond nature fails to recognize both Earth's creative genesis and the myriads of species lines, a failure which diminishes the richness of life on Earth, and simultaneously the fullness of human life.
Open Access
Metabolic engineering of Arabidopsis for butanetriol production using bacterial genes
(Colorado State University. Libraries, 2013-11) Abdel-Ghany, Salah E., author; Day, Irene, author; Heuberger, Adam L., author; Broeckling, Corey D., author; Reddy, Anireddy S. N., author; Elsevier Inc., publisher
1,2,4-butanetriol (butanetriol) is a useful precursor for the synthesis of the energetic material butanetriol trinitrate and several pharmaceutical compounds. Bacterial synthesis of butanetriol from xylose or arabinose takes place in a pathway that requires four enzymes. To produce butanetriol in plants by expressing bacterial enzymes, we cloned native bacterial or codon optimized synthetic genes under different promoters into a binary vector and stably transformed Arabidopsis plants. Transgenic lines expressing introduced genes were analyzed for the production of butanetriol using gas chromatography coupled to mass spectrometry (GC-MS). Soil-grown transgenic plants expressing these genes produced up to 20 µg/g of butanetriol. To test if an exogenous supply of pentose sugar precursors would enhance the butanetriol level, transgenic plants were grown in a medium supplemented with either xylose or arabinose and the amount of butanetriol was quantified. Plants expressing synthetic genes in the arabinose pathway showed up to a forty-fold increase in butanetriol levels after arabinose was added to the medium. Transgenic plants expressing either bacterial or synthetic xylose pathways, or the arabinose pathway showed toxicity symptoms when xylose or arabinose was added to the medium, suggesting that a by-product in the pathway or butanetriol affected plant growth. Furthermore, the metabolite profile of plants expressing arabinose and xylose pathways was altered. Our results demonstrate that bacterial pathways that produce butanetriol can be engineered into plants to produce this chemical. This proof-of-concept study for phytoproduction of butanetriol paves the way to further manipulate metabolic pathways in plants to enhance the level of butanetriol production.
Open Access
Robust static allocation of resources for independent tasks under makespan and dollar cost constraints
(Colorado State University. Libraries, 2006) Pippin, Alan, author; Raskey, Michael, author; Guru, Kumara, author; Lee, Panho, author; Aydin, Mahir, author; Zhang, Junxing, author; Ali, Syed, author; Krishnamurthy, Yogish, author; Al-Otaibi, Mohammad, author; Shestak, Vladimir, author; Horiuchi, Aaron, author; Pichel, Ron, author; Mehta, Ashish, author; Oltikar, Mohana, author; Maciejewski, Anthony A., author; Siegel, H. J., author; Sugavanam, Prasanna, author; Elsevier Inc., publisher
Heterogeneous computing (HC) systems composed of interconnected machines with varied computational capabilities often operate in environments where there may be inaccuracies in the estimation of task execution times. Makespan (defined as the completion time for an entire set of tasks) is often the performance feature that needs to be optimized in such systems. Resource allocation is typically performed based on estimates of the computation time of each task on each class of machines. Hence, it is important that makespan be robust against errors in computation time estimates. In this research, the problem of finding a static mapping of tasks to maximize the robustness of makespan against the errors in task execution time estimates given an overall makespan constraint is studied. Two variations of this basic problem are considered: (1) where there is a given, fixed set of machines, (2) where an HC system is to be constructed from a set of machines within a dollar cost constraint. Six heuristic techniques for each of these variations of the problem are presented and evaluated.
Open Access
Static allocation of resources to communicating subtasks in a heterogeneous ad hoc grid environment
(Colorado State University. Libraries, 2006) Velazco, José, author; Sridharan, Jayashree, author; Sousa, J., author; Sendek, David, author; Saylor, William, author; Satyasekaran, Praveen, author; Pichumani, Prakash, author; Dussinger, Steve, author; Chindam, Kiran, author; Castain, Ralph, author; Banka, Tarun, author; Sugavanam, Prasanna, author; Maciejewski, Anthony A., author; Siegel, H. J., author; Shivle, Sameer, author; Elsevier Inc., publisher
An ad hoc grid is a heterogeneous computing and communication system that allows a group of mobile devices to accomplish a mission, often in a hostile environment. Energy management is a major concern in ad hoc grids. The problem studied here focuses on statically assigning resources in an ad hoc grid to an application composed of communicating subtasks. The goal of the allocation is to minimize the average percentage of energy consumed by the application to execute across the machines in the ad hoc grid, while meeting an application execution time constraint. This pre-computed allocation is then used when the application is deployed in a mission. Six different heuristic approaches of varying time complexities have been designed and compared via simulations to solve this ad hoc grid allocation problem. Also, a lower bound based on the performance metric has been designed to compare the performance of the heuristics developed.