• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.387-390
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• 2017

With the advent of high-resolution sensors in the embedded field, the demand for heterogeneous computing continues to increase. Logic Module is an embedded system for controlling LADAR system components and for real-time 3D imaging of laser radar image data. In this paper, we discuss the design of Logic Module and the signal processing using CPU-GPU heterogeneous computing.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.8
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• pp.245-252
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• 2015

Recently, parallel processing methods with accelerator have been introduced into a high performance computing and a mobile computing. The photomosaic application can be parallelized by using inherent data parallelism and accelerator. In this paper, we propose a way to distribute the workload of the photomosaic application into a CPU and GPU heterogeneous computing environment. That is, the photomosaic application is parallelized using both CPU and GPU resource with the asynchronous mode of OpenCL, and then the optimal workload distribution rate is estimated by measuring the execution time with CPU-only and GPU-only distribution rates. The proposed approach is simple but very effective, and can be applied to parallelize other applications on a CPU and GPU heterogeneous computing environment. Based on the experimental results, we confirm that the performance is improved by 141% into a heterogeneous computing environment with the optimal workload distribution compared with using GPU-only method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.86-95
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• 2009

Efficient DAG scheduling is critical for achieving high performance in heterogeneous computing environments. Finding an optimal solution to the problem of scheduling an application modeled by a directed acyclic graph(DAG) onto a set of heterogeneous machines is known to be an NP-complete problem. In this paper we propose a new list scheduling algorithm, called the Heterogeneous Rank-Path Scheduling(HRPS) algorithm, to exploit all of a program's available parallelism in distributed heterogeneous computing system. The primary goal of HRPS is to minimize the schedule length of applications. The performance of the algorithm has been observed by its application to some practical DAGs, and by comparing it with other existing scheduling algorithm such as CPOP, HCPT and FLB in term of the schedule length. The comparison studies show that HRPS significantly outperform CPOP, HCPT and FLB in schedule length.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.9-17
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• 2018

Heterogeneous high performance computing systems are gaining acceptance as the environments for computational scientific simulations of various application fields. Those computing systems, however, have been mostly used with the legacy consoles, resulting in the severe decrement of accessibility and usability of heterogeneous computing assets. To solve this problem, this paper presents the design and implementation of web-based computational science simulation management program. The proposed program provides fundamental primitives including user authentication, data management, physical/virtual computing resource management, job management, etc. that can be used to manage different kinds of simulations efficiently, and also offers highly extensible feature through a modular plug-in architecture. We also present the best practical examples of applications (e.g., scientific simulation education and bio-medical) to confirm our program's effectiveness.

• Smart Media Journal
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• v.11 no.3
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• pp.18-25
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• 2022

Neuromorphic computing generally shows significantly better power, area, and speed performance than neural network computation using CPU and GPU. These characteristics are suitable for resource-constrained IoT environments where energy consumption is important. However, there is a problem in that it is necessary to modify the source code for environment setting and application operation according to heterogeneous IoT devices that support neuromorphic computing. To solve these problems, NAAL was proposed and implemented in this paper. NAAL provides functions necessary for IoT device control and neuromorphic architecture abstraction and inference model operation in various heterogeneous IoT device environments based on common APIs of NAAL. NAAL has the advantage of enabling additional support for new heterogeneous IoT devices and neuromorphic architectures and computing devices in the future.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.81-87
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• 2010

This paper proposes a G-BLAST(BLAST using Grid Computing) system, an integrated software package for BLAST searches operated in heterogeneous distributed environment. G-BLAST employed 'database splicing' method to improve the performance of BLAST searches using exists computing resources. G-BLAST is a basic local alignment search tool of DNA Sequence using grid computing in heterogeneous distributed environment. The G-BLAST improved the existing BLAST search performance in gene sequence analysis. Also G-BLAST implemented the pipeline and data management method for users to easily manage and analyze the BLAST search results. The proposed G-BLAST system has been confirmed the speed and efficiency of BLAST search performance in heterogeneous distributed computing.

• Journal of the Korea Computer Graphics Society
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• v.24 no.2
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• pp.11-20
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• 2018

We propose a new method particle-based method that explicitly preserves thin liquid sheets for animating liquids on CPU-GPU heterogeneous computing framework. Our primary contribution is a particle-based framework that splits at thin points and collapses at dense points to prevent the breakup of liquid on GPU. In contrast to existing surface tracking methods, the our method does not suffer from numerical diffusion or tangles, and robustly handles topology changes on CPU-GPU framework. The thin features are detected by examining stretches of distributions of neighboring particles by performing PCA(Principle component analysis), which is used to reconstruct thin surfaces with anisotropic kernels. The efficiency of the candidate position extraction process to calculate the position of the fluid particle was rapidly improved based on the CPU-GPU heterogeneous computing techniques. Proposed algorithm is intuitively implemented, easy to parallelize and capable of producing quickly detailed thin liquid animations.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.663-674
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• 2016

Traditional supercomputing services suffer from limited accessibility and low utilization in that users(researchers) may perform computational executions only using terminal-based command line interfaces. To address this problem, in this paper, we provide the design and implementation details of National supercomputing service framework. The proposed framework supports all the fundamental primitive functions such as user management/authentication, heterogeneous computing resource management, HPC (High Performance Computing) job management, etc. so that it enables various 3rd-party applications to be newly built on top of the proposed framework. Our framework also provides Web-based RESTful OpenAPIs and the abstraction interfaces of job schedulers (as well as bundle scheduler plug-ins, for example, LoadLeveler, Open Grid Scheduler, TORQUE) in order to easily integrate the broad spectrum of heterogeneous computing clusters. To show and validate the effectiveness of the proposed framework, we describe the best practice scenario of high energy physics Lattice-QCD as an example application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.368-371
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• 2000

The distributed object computing is possible to distributed computing on same or heterogeneous machine environment with growth of distributed computing and object-oriented technology. The typical of model, CORBA is int solved the interoperability in heterogeneous machine environment over the network But, the CORBA has a problem that the server is can't rely on request of client occurs network overhead by extinction of network A plan was on the rise to solve the problem that is combination of mobile agent and distributed computing technology.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.10
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• pp.407-414
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• 2017

Pig monitoring applications consisting of many tasks can take advantage of inherent data parallelism and enable parallel processing using performance accelerators. In this paper, we propose a task distribution method for pig monitoring applications into a heterogenous computing platform consisting of a multicore-CPU and a manycore-GPU. That is, a parallel program written in OpenCL is developed, and then the most suitable processor is determined based on the measured execution time of each task. The proposed method is simple but very effective, and can be applied to parallelize other applications consisting of many tasks on a heterogeneous computing platform consisting of a CPU and a GPU. Experimental results show that the performance of the proposed task distribution method on three different heterogeneous computing platforms can improve the performance of the typical GPU-only method where every tasks are executed on a deviceGPU by a factor of 1.5, 8.7 and 2.7, respectively.