• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.247-248
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• 2014

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.8-17
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• 2014

Petascale systems(so called supercomputers) have been mainly used for supporting communication-intensive and tightly-coupled parallel computations based on message passing interfaces such as MPI(HPC: High-Performance Computing). On the other hand, computing paradigms such as High-Throughput Computing(HTC) mainly target compute-intensive (relatively low I/O requirements) applications consisting of many loosely-coupled tasks(there is no communication needed between them). In Korea, recently emerging applications from various scientific fields such as pharmaceutical domain, high-energy physics, and nuclear physics require a very large amount of computing power that cannot be supported by a single type of computing resources. In this paper, we present our HTCaaS(High-Throughput Computing as a Service) which can leverage national distributed computing resources in Korea to support these challenging HTC applications and describe the details of our system architecture, job execution scenario and case studies of various scientific applications.

• Journal of KIISE
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• v.42 no.5
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• pp.573-579
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• 2015

Nationwide supercomputing infrastructures in Korea consist of geographically distributed supercomputing clusters. We developed High-Throughput Computing as a Service(HTCaaS) based on these distributed national supecomputing clusters to facilitate the ease at which scientists can explore large-scale and complex scientific problems. In this paper, we present our mechanism for dynamically managing computing resources and show its effectiveness through a case study of a real scientific application called drug repositioning. Specifically, we show that the resource utilization, accuracy, reliability, and usability can be improved by applying our resource management mechanism. The mechanism is based on the concepts of waiting time and success rate in order to identify valid computing resources. The results show a reduction in the total job completion time and improvement of the overall system throughput.

• International Journal of Contents
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• v.12 no.2
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• pp.6-11
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• 2016

We developed a pilot-job based large-scale distributed computing system to support HTC and MTC, called HTCaaS (High-Throughput Computing as a Service), which helps scientists solve large-scale scientific problems in areas such as pharmaceutical domains, high-energy physics, nuclear physics and bio science. Since most of these problems involve critical data that affect the national economy and activate basic industries, data privacy is a very important issue. In this paper, we implement a privacy enhanced data security mechanism to support HTC and MTC in a large-scale distributed computing system and show how this technique affects performance in our system. With this mechanism, users can securely store data in our system.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.205-206
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• 2014

• Journal of KIISE
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• v.42 no.1
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• pp.15-22
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• 2015

In this paper, we present a case study for a drug repositioning simulation based on distributed supercomputing technology that requires highly efficient processing of large-scale computations. Drug repositioning is the application of known drugs and compounds to new indications (i.e., new diseases), and this process requires efficient processing of a large number of docking tasks with relatively short per-task execution times. This mechanism shows the main characteristics of a Many-Task Computing (MTC) application, and as a representative case of MTC applications, we have applied a drug repositioning simulation in our HTCaaS system which can leverage distributed supercomputing infrastructure, and show that efficient task dispatching, dynamic resource allocation and load balancing, reliability, and seamless integration of multiple computing resources are crucial to support these challenging scientific applications.