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Article
Comprehensive techniques for multi-tenant deep learning framework on a Hadoop YARN cluster
We have designed and implemented a new data processing framework called “MeLoN” (Multi-tenant dEep Learning framework On yarN) which aims to effectively support distributed deep learning applications that can ...
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Article
Comprehensive techniques of multi-GPU memory optimization for deep learning acceleration
This paper presents a comprehensive suite of techniques for optimized memory management in multi-GPU systems to accelerate deep learning application execution. We employ a hybrid utilization of GPU and CPU mem...
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Article
Towards an optimized distributed deep learning framework for a heterogeneous multi-GPU cluster
This paper presents a novel “Distributed Deep Learning Framework” for a heterogeneous multi-GPU cluster that can effectively improve overall resource utilization without sacrificing training accuracy. Specificall...
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Article
Towards optimal scheduling policy for heterogeneous memory architecture in many-core system
With the advent of Intels second-generation many-core processor (Knights Landing: KNL), high-bandwidth memory (HBM) with potentially five times more bandwidth than existing dynamic random-access memory has bec...
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Article
On the role of message broker middleware for many-task computing on a big-data platform
We have designed and implemented a new data processing framework called “Many-task computing On HAdoop” (MOHA) which aims to effectively support fine-grained many-task applications that can show another type o...
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Article
Making a case for the on-demand multiple distributed message queue system in a Hadoop cluster
In this paper, we present a framework that can provide users with a simple, convenient and powerful way to deploy multiple message queue system on demand in a Hadoop cluster. Specifically, we are leveraging th...
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Article
Adaptive hybrid storage systems leveraging SSDs and HDDs in HPC cloud environments
Cloud computing should inherently support various types of data-intensive workloads with different storage access patterns. This makes a high-performance storage system in the Cloud an important component. Eme...
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Article
On the role of application and resource characterizations in heterogeneous distributed computing systems
Loosely coupled applications composed of a potentially very large number (from tens of thousands to even billions) of tasks are commonly used in high-throughput computing and many-task computing paradigms. To ...
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Article
Exploiting resource profiling mechanism for large-scale scientific computing on grids
Large-scale scientific applications from various scientific domains (e.g., astronomy, physics, pharmaceuticals, chemistry, etc.) usually require substantial amounts of computing resources and storage space. In...
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Article
High performance parallelization of Boyer–Moore algorithm on many-core accelerators
Boyer–Moore (BM) algorithm is a single pattern string matching algorithm. It is considered as the most efficient string matching algorithm and used in many applications. The algorithm first calculates two stri...
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Article
Scalable and effective peer-to-peer desktop grid system
We have designed a set of protocols that use peer-to-peer techniques to efficiently implement a distributed and decentralized desktop grid. Incoming jobs with different resource requirements are matched with s...
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Article
Towards effective science cloud provisioning for a large-scale high-throughput computing
The science cloud paradigm has been actively developed and investigated, but still requires a suitable model for science cloud system in order to support increasing scientific computation needs with high perfo...