Custom Built of Smart Computing Platform for Supporting Optimization Methods and Artificial Intelligence Research | [Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences • 2021]

Author(s):

1. Indar Sugiarto: Department of Electrical Engineering, Petra Christian University,Jl. Siwalankerto No.121-131, Surabaya, 60236,Indonesia

2. Doddy Prayogo: Department of Civil Engineering, Petra Christian University Surabaya,60236,Indonesia

3. Henry Palit: Department of Informatics, Petra Christian University,Surabaya, 60236,Indonesia

4. Felix Pasila: Department of Electrical Engineering, Petra Christian University,Jl. Siwalankerto No.121-131, Surabaya, 60236,Indonesia

5. Resmana Lim: Department of Electrical Engineering, Petra Christian University,Jl. Siwalankerto No.121-131, Surabaya, 60236,Indonesia

6. Agustinus Noertjahyana: Department of Informatics, Petra Christian University,Surabaya, 60236,Indonesia

7. I Gede Widyadana: Department of Industrial Engineering, Petra Christian University Surabaya,60236,Indonesia

8. Surya Hermawan: Department of Civil Engineering, Petra Christian University Surabaya,60236,Indonesia

9. Agustinus Bimo Gumelar: Department of Information System, Narotama University,Jl. Arief Rachman Hakim 51, Sukolilo, Surabaya, 60117,Indonesia

10. Bernardo Nugroho Yahya: Department of Industrial and Management Engineering, Hankuk University of Foreign Studies,107, Imun-ro, Dongdaemun-gu, Seoul, 130-791,Korea

Abstract:

This paper describes a prototype of a computing platform dedicated to artificial intelligence explorations. The platform, dubbed as PakCarik, is essentially a high throughput computing platform with GPU (graphics processing units) acceleration. PakCarik is an Indonesian acronym for Platform Komputasi Cerdas Ramah Industri Kreatif, which can be translated as “Creative Industry friendly Intelligence Computing Platform”. This platform aims to provide complete development and production environment for AI-based projects, especially to those that rely on machine learning and multiobjective optimization paradigms. The method for constructing PakCarik was based on a computer hardware assembling technique that uses commercial of-the-shelf hardware and was tested on several AI-related application scenarios. The testing methods in this experiment include: high-performance lapack (HPL) benchmarking, message passing interface (MPI) benchmarking, and TensorFlow (TF) benchmarking. From the experiment, the authors can observe that PakCarik's performance is quite similar to the commonly used cloud computing services such as Google Compute Engine and Amazon EC2, even though falls a bit behind the dedicated AI platform such as Nvidia DGX-1 used in the benchmarking experiment. Its maximum computing performance was measured at 326 Gflops. The authors conclude that PakCarik is ready to be deployed in real-world applications and it can be made even more powerful by adding more GPU cards in it.

Page(s): 59-64

DOI: DOI not available

Published: Journal: Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, Volume: 58, Issue: S, Year: 2021

Keywords:

machine learning , Artificial Intelligence , Graphics Processing Unit Accelerator , Multiobjective Optimization , High Throughput Computing

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