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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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Chapter and Conference Paper
Exploring the Volatility of Large-Scale Shared Distributed Computing Resources
Scientific applications often require colossal amount of computing resources for running user’s tasks. Grid computing has been proved to be powerful research testbed for accessing massive amount of computing r...
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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...
