Improvement of Task Retrieval Performance Using AMGA in a Large-Scale Virtual Screening

Ahn, Sunil; Kim, Namgyu; Lee, Seehoon; Hwang, Soonwook; Nam, Dukyun; Koblitz, B.; Breton, Vincent; Han, Sang‐Min

doi:10.1109/ncm.2008.201

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Therefore, failed tasks must be resubmitted, further slowing down the application completion. Frameworks such as pilot jobs have been introduced during the last years (Ahn et al (2008); Bagnasco et al (2008); Kacsuk et al (2008); Maeno (2008); Moscicki (2003b); Sfiligoi (2008); Tsaregorodtsev et al (2008)) and are now extensively used in order to improve QoS and cope with the recurrent errors and high latencies caused by the grid heterogeneity. Application porting and reusability have also been facilitated with the help of workflow technology, as discussed in Deelman et al (2005); Glatard et al (2008); Kacsuk & Sipos (2005); Maheshwari et al (2009) ;Oinn et al (2004).…”

Section: Applications Execution On Gridsmentioning

confidence: 99%

Enabling Grids for GATE Monte-Carlo Radiation Therapy Simulations with the GATE-Lab

Camarasu-Pop¹,

Glatard²,

Benoit-Cattin³

et al. 2011

Applications of Monte Carlo Method in Science and Engineering

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Section: Applications Execution On Gridsmentioning

confidence: 99%

Enabling Grids for GATE Monte-Carlo Radiation Therapy Simulations with the GATE-Lab

Camarasu-Pop¹,

Glatard²,

Benoit-Cattin³

et al. 2011

Applications of Monte Carlo Method in Science and Engineering

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“…One possible solution for (i) is offered by pilot jobs, while (ii) can be addressed by workflow engines. Pilot jobs have been introduced during the last years [1,3,8,11,14,19,27,28] and are now extensively used to improve performance and cope with the latencies and recurrent errors caused by the Grid heterogeneity. Much effort has also been put into workflow technology to facilitate application porting and reusability [5,7,12,15,21].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Partitioning of GATE Monte-Carlo Simulations on EGEE

et al. 2010

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The EGEE Grid offers the necessary infrastructure and resources for reducing the running time of particle tracking Monte-Carlo applications like GATE. However, efforts are required to achieve reliable and efficient execution and to provide execution frameworks to end-users. This paper presents results obtained with porting the GATE software on the EGEE Grid, our ultimate goal being to provide reliable, user-friendly and fast execution of GATE to radiation therapy researchers. To address these requirements, we propose a new parallelization scheme based on a dynamic partitioning and its implementation in two different frameworks using pilot jobs and workflows. Results show that pilot jobs bring strong improvement w.r.t. regular gLite submission, that the proposed dynamic partitioning algorithm further reduces execution time by a factor of S. Camarasu-Pop (B) · T. Glatard · two and that the genericity and user-friendliness offered by the workflow implementation do not introduce significant overhead.

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“…Currently, the number of maximum resubmission is a parameter that can be customized at the level of the application layer. Similar solutions to handle failed jobs on the computing infrastructures have been addressed by different Virtual Research Communities (VRCs) who have developed in these years frameworks such as pilot jobs to cope with this problems and improve the QoS and cope with the recurrent errors and high latencies caused by the grid heterogeneity .…”

Section: The Science Gateway Frameworkmentioning

confidence: 99%

A GEANT4 web‐based application to support Intra‐Operative Electron Radiotherapy using the European grid infrastructure

Casarino

Russo

Candiano

et al. 2014

Concurrency and Computation

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Abstract-Radiotherapy techniques permit to deliver ionizing radiations (X-rays, photons, electrons, protons, etc) inside cancerous tissues to kill the abnormal-cells. Radiotherapy related activities, as the optimization of the therapeutic radiation dose to the patient, worker radioprotection, performance controls and technical innovations of linear accelerators, are strongly based on the ability to predict the dose distribution. Monte Carlo simulations are the most accurate tools in this field but, unfortunately, they require large computing power to achieve accurate results in reasonable times. In the last years, advanced cancer treatment clinical and research communities have adopted e-Infrastructures to reduce this gap. The present paper reports on the developments of a computing facility for helping physicians, radiotherapists and medical physical in using modern R&E networking and distributed resources to address some technical and clinical Intra-Operative Electron Radio-Therapy (IOERT) needs (e.g. the design of the linear accelerator collimation system or the optimization of the patient therapeutic dose distribution).

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Improvement of Task Retrieval Performance Using AMGA in a Large-Scale Virtual Screening

Cited by 5 publications

References 12 publications

Enabling Grids for GATE Monte-Carlo Radiation Therapy Simulations with the GATE-Lab

Enabling Grids for GATE Monte-Carlo Radiation Therapy Simulations with the GATE-Lab

Dynamic Partitioning of GATE Monte-Carlo Simulations on EGEE

A GEANT4 web‐based application to support Intra‐Operative Electron Radiotherapy using the European grid infrastructure

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