Browsing by Author "Zhang, Yang"

Now showing 1 - 5 of 5
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    de Boor-suitable (DS) T-splines of Bidegree (3, 3)
    (2018-11-30) Zhang, Yang; Goldman, Ron
    Necessary and sufficient conditions under which the de Boor algorithm can be applied to evaluate points on a T-spline surface of bidegree (3, 3) are investigated. These de Boor-suitable (DS) T-splines are compared to the standard analysis-suitable (AS) T-splines. An algorithm is also developed to search in a T-mesh for the appropriate control points and blend them using the de Boor algorithm to compute the corresponding point on the T-spline surface.
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    Grid-centric scheduling strategies for workflow applications
    (2010) Zhang, Yang; Cooper, Keith D.
    Grid computing faces a great challenge because the resources are not localized, but distributed, heterogeneous and dynamic. Thus, it is essential to provide a set of programming tools that execute an application on the Grid resources with as little input from the user as possible. The thesis of this work is that Grid-centric scheduling techniques of workflow applications can provide good usability of the Grid environment by reliably executing the application on a large scale distributed system with good performance. We support our thesis with new and effective approaches in the following five aspects. First, we modeled the performance of the existing scheduling approaches in a multi-cluster Grid environment. We implemented several widely-used scheduling algorithms and identified the best candidate. The study further introduced a new measurement, based on our experiments, which can improve the schedule quality of some scheduling algorithms as much as 20 fold in a multi-cluster Grid environment. Second, we studied the scalability of the existing Grid scheduling algorithms. To deal with Grid systems consisting of hundreds of thousands of resources, we designed and implemented a novel approach that performs explicit resource selection decoupled from scheduling Our experimental evaluation confirmed that our decoupled approach can be scalable in such an environment without sacrificing the quality of the schedule by more than 10%. Third, we proposed solutions to address the dynamic nature of Grid computing with a new cluster-based hybrid scheduling mechanism. Our experimental results collected from real executions on production clusters demonstrated that this approach produces programs running 30% to 100% faster than the other scheduling approaches we implemented on both reserved and shared resources. Fourth, we improved the reliability of Grid computing by incorporating fault- tolerance and recovery mechanisms into the workow application execution. Our experiments on a simulated multi-cluster Grid environment demonstrated the effectiveness of our approach and also characterized the three-way trade-off between reliability, performance and resource usage when executing a workflow application. Finally, we improved the large batch-queue wait time often found in production Grid clusters. We developed a novel approach to partition the workow application and submit them judiciously to achieve less total batch-queue wait time. The experimental results derived from production site batch queue logs show that our approach can reduce total wait time by as much as 70%. Our approaches combined can greatly improve the usability of Grid computing while increasing the performance of workow applications on a multi-cluster Grid environment.
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    Inferring causal molecular networks: empirical assessment through a community-based effort
    (Springer Nature, 2016) Hill, Steven M.; Heiser, Laura M.; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K.; Carlin, Daniel E.; Zhang, Yang; Sokolov, Artem; Paull, Evan O.; Wong, Chris K.; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V.; Favorov, Alexander V.; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W.; Long, Byron L.; Noren, David P.; Bisberg, Alexander J.; HPN-DREAM Consortium; Mills, Gordon B.; Gray, Joe W.; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A.; Fertig, Elana J.; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M.; Spellman, Paul T.; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach
    It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well asﾠin silicoﾠdata from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.
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    Scalable Grid Application Scheduling via Decoupled Resource Selection and Scheduling
    (2006-01-20) Casanova, Henri; Chien, Andrew A.; Kee, Yang-Suk; Kennedy, Ken; Koelbel, Charles; Mandal, Anirban; Zhang, Yang
    Over the past years grid infrastructures have been deployed at larger and larger scales, with envisioned deployments incorporating tens of thousands of resources. Therefore, application scheduling algorithms can become unscalable (albeit polynomial) and thus unusable in large-scale environments. One reason for unscalability is that these algorithms perform implicit resource selection. One can achieve better scalability by performing explicit resource selection decoupled from scheduling (aka "decoupled" approach). Furthermore, we hypothesize that one can achieve similar or even better performance as with the non-decoupled approach (aka "one step" approach) by selecting resources judiciously. Leveraging the Virtual Grid Execution System, we demonstrate that the decoupled approach is indeed both scalable and effective in large-scale and highly heterogeneous resource environments.
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    Scheduling Algorithms Performance Evaluation in Grid Environments
    (2006-04-18) Kennedy, Ken; Koelbel, Charles; Zhang, Yang
    Effective scheduling is critical for the performance of an application launched onto the Grid environment. Deriving efficient algorithms for this scheduling has always been a challenging research area. Many scheduling algorithms have been proposed, studied and compared but there are few studies comparing their performance in Grid environments. The Grid environment has the unique property of drastic cost differences between inter-cluster and the intra-cluster data transfers. In this paper, we compare several scheduling algorithms that represent two major schemes. We further analyze the results to show how different resource environments and workflow application structures affect the algorithms' performances, and suggest directions for future research in Grid schedulers.