Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation

Widiarto Adiyoso; Adila Krisnadhi; Ari Wibisono; Sumarsih Condroayu Purbarani; Anindhita Dwi Saraswati; Annissa Fildzah Rafi Putri; Ibad Rahadian Saladdin; S. Reyneta Carissa Anwar

doi:10.1109/IWBIS.2018.8471715

Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation

Widiarto Adiyoso, Adila Krisnadhi, Ari Wibisono, Sumarsih Condroayu Purbarani, Anindhita Dwi Saraswati, Annissa Fildzah Rafi Putri, Ibad Rahadian Saladdin, S. Reyneta Carissa Anwar

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

Big data is a hot topic that is regularly discussed in the computer science field for the past year. Big data provides numerous benefits for the development of technologies, such as business intelligence and deep learning. Processing big data requires specialized tools and environment, ranging from a commodity-clustered workstation to high performance computing server, especially in big data clustering where unsupervised learning takes place. In this paper, we conduct time analysis of commodity-clustered workstation equipped with Spark as a baseline for multi-CPU big data clustering and TensorFlow installed in a high-performance computing workstation as a baseline for multi-GPU big data clustering. Based on the analysis, it shows that TensorFlow performs have around 5 to 12 times faster computation time than Spark.

Original language	English
Title of host publication	2018 International Workshop on Big Data and Information Security, IWBIS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	113-116
Number of pages	4
ISBN (Electronic)	9781538655252
DOIs	https://doi.org/10.1109/IWBIS.2018.8471715
Publication status	Published - 24 Sept 2018
Event	2018 International Workshop on Big Data and Information Security, IWBIS 2018 - Balai Kartini, Jakarta, Indonesia Duration: 12 May 2018 → 13 May 2018

Publication series

Name	2018 International Workshop on Big Data and Information Security, IWBIS 2018

Conference

Conference	2018 International Workshop on Big Data and Information Security, IWBIS 2018
Country/Territory	Indonesia
City	Balai Kartini, Jakarta
Period	12/05/18 → 13/05/18

Keywords

Big Data
Cluster
K-Means
Spark
TensorFlow

Access to Document

10.1109/IWBIS.2018.8471715

Cite this

Adiyoso, W., Krisnadhi, A., Wibisono, A., Purbarani, S. C., Saraswati, A. D., Putri, A. F. R., Saladdin, I. R., & Anwar, S. R. C. (2018). Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation. In 2018 International Workshop on Big Data and Information Security, IWBIS 2018 (pp. 113-116). Article 8471715 (2018 International Workshop on Big Data and Information Security, IWBIS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWBIS.2018.8471715

Adiyoso, Widiarto ; Krisnadhi, Adila ; Wibisono, Ari et al. / Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation. 2018 International Workshop on Big Data and Information Security, IWBIS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 113-116 (2018 International Workshop on Big Data and Information Security, IWBIS 2018).

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title = "Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation",

abstract = "Big data is a hot topic that is regularly discussed in the computer science field for the past year. Big data provides numerous benefits for the development of technologies, such as business intelligence and deep learning. Processing big data requires specialized tools and environment, ranging from a commodity-clustered workstation to high performance computing server, especially in big data clustering where unsupervised learning takes place. In this paper, we conduct time analysis of commodity-clustered workstation equipped with Spark as a baseline for multi-CPU big data clustering and TensorFlow installed in a high-performance computing workstation as a baseline for multi-GPU big data clustering. Based on the analysis, it shows that TensorFlow performs have around 5 to 12 times faster computation time than Spark.",

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author = "Widiarto Adiyoso and Adila Krisnadhi and Ari Wibisono and Purbarani, {Sumarsih Condroayu} and Saraswati, {Anindhita Dwi} and Putri, {Annissa Fildzah Rafi} and Saladdin, {Ibad Rahadian} and Anwar, {S. Reyneta Carissa}",

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Adiyoso, W, Krisnadhi, A , Wibisono, A, Purbarani, SC, Saraswati, AD, Putri, AFR, Saladdin, IR & Anwar, SRC 2018, Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation. in 2018 International Workshop on Big Data and Information Security, IWBIS 2018., 8471715, 2018 International Workshop on Big Data and Information Security, IWBIS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 113-116, 2018 International Workshop on Big Data and Information Security, IWBIS 2018, Balai Kartini, Jakarta, Indonesia, 12/05/18. https://doi.org/10.1109/IWBIS.2018.8471715

Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation. / Adiyoso, Widiarto; Krisnadhi, Adila ; Wibisono, Ari et al.
2018 International Workshop on Big Data and Information Security, IWBIS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 113-116 8471715 (2018 International Workshop on Big Data and Information Security, IWBIS 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Saraswati, Anindhita Dwi

AU - Putri, Annissa Fildzah Rafi

AU - Saladdin, Ibad Rahadian

AU - Anwar, S. Reyneta Carissa

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AB - Big data is a hot topic that is regularly discussed in the computer science field for the past year. Big data provides numerous benefits for the development of technologies, such as business intelligence and deep learning. Processing big data requires specialized tools and environment, ranging from a commodity-clustered workstation to high performance computing server, especially in big data clustering where unsupervised learning takes place. In this paper, we conduct time analysis of commodity-clustered workstation equipped with Spark as a baseline for multi-CPU big data clustering and TensorFlow installed in a high-performance computing workstation as a baseline for multi-GPU big data clustering. Based on the analysis, it shows that TensorFlow performs have around 5 to 12 times faster computation time than Spark.

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Adiyoso W, Krisnadhi A , Wibisono A, Purbarani SC, Saraswati AD, Putri AFR et al. Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation. In 2018 International Workshop on Big Data and Information Security, IWBIS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 113-116. 8471715. (2018 International Workshop on Big Data and Information Security, IWBIS 2018). doi: 10.1109/IWBIS.2018.8471715

Time Performance Analysis of Multi-CPU and Multi-GPU in Big Data Clustering Computation

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Keywords

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