Taipei, Taiwan, 4th June 2018 - GIGABYTE, an industry leader in server systems and motherboards, has collaborated with local cloud and storage platform providers to showcase an integrated AI / Data Science Cloud atCOMPUTEX 2018, demonstrating how customers can build a private cloud to own & protect their data while connecting with public cloud services, and incorporate inbuilt AI capabilities to use Big Data for real-time deep learning and inference processing (AIoT).

GIGABYTE Featured Hardware

GIGABYTE's Network & Communication Business Unit exhibit area at COMPUTEX 2018 will showcase our six main product lines and their target applications:

Product Series Target Application COMPUTEX 2018 Featured Product Product Features
H-Series

Density Optimized Servers

Hyper-converged data centers / cloud service providers

H281-PE0

2U 4-nodes w/ dual Intel Xeon Scalable processors per node & optional liquid cooling system
G-Series

GPU Servers

AI training, deep learning & high performance computing

G481-S80

4U dual Intel Xeon Scalable processors & 8 x V100 / P100 SXM2 GPUs w/ optional liquid cooling system
S-Series

Storage Servers

Scale-out software defined storage

S451-3R0

4U dual Intel Xeon Scalable processors & 36 x 3.5' SSD / HDD drives
R-Series

Rack Servers

General purpose rack servers for enterprise IT

R281-Z92

2U dual AMD EPYC 7000 series processors w/ 24 x 2.5' ultra-fast NVMe U.2 storage drives
W-Series

Workstations

Media content creation or software development

W281-T91

Dual Cavium ThunderX2 processors ARM workstation tower
RACKLUTION-OP

Open Compute Project Compliant Systems

Hyper scale data centers

DO60-MR0

12OU 21' Open Rack Standard compliant mini-rack w/ compute & storage nodes

AI / Data Science Cloud Demonstration

GIGABYTE will not only showcase our hardware during COMPUTEX but also demonstrate to our customers the practical applications of our products by building a private cloud in collaboration with our partners InfinitiesSoft, ITRI and Bigtera. We have called our demonstration an AI / Data Science Cloud, a deep learning & Big Data enabled private cloud created with InfinitiesSoft CloudFusion, ITRI's IOD-MB and Bigtera's VirtualStor Scaler and running live onsite on GIGABYTE's H-Series, G-Series and S-Series servers. It provides local and remote services in categories such as compute, storage, Big Data analytics, deep learning & AI training, and management functions. The platform has a high availability architecture that can avoid a single point of failure and can be quickly scaled out at remote locations.

Diagram A: AI / Data Science Cloud Hardware Topology

InfinitiesSoft CloudFusion

The top layer of GIGABYTE's AI / Data Science Cloud is InfinitiesSoft CloudFusion, a comprehensive cloud management platform that can support and integrate over 30 different private and public clouds with a single platform, so your private cloud can be integrated together with public cloud services to build a hybrid cloud. CloudFusion allows the user to add or change cloud solutions with ease, allocate resources and limit use for different organizations, units or users, and quickly understand current cloud data center CPU, memory, and storage resource utilization with a graphic display. CloudFusion also supports a highly elastic open API interface for developers to ensure additional public or private clouds can also be swiftly connected and integrated into the platform, ensuring it is future-proof.

Diagram B: AI / Data Science Cloud Platform Overview

ITRI's IOD-MB

Below the management layer of GIGABYTE's AI / Data Science Cloud is the virtualization layer, an enhanced OpenStack platform developed by ITRI called IOD-MB (ITRI OpenStack Distribution for Machine Learning and Big Data). This OpenStack platform features integration with Kubernetes for automatic deployment of machine learning containers onto GPU servers for AI training. Data scientists can therefore focus on their core competencies (such as algorithm development and data analysis) instead of spending time on resource allocation, environment setup or container preparation. IOD-MB is a powerful, flexible and extensive IaaS solution integrating virtualization, machine learning and Big Data analysis capabilities for private and hybrid clouds.

Diagram C: AI / Data Science Cloud Platform Features / Services

Bigtera VirtualStor Scaler

GIGABYTE's 'AI / Data Science Cloud' includes a scale-out storage cluster created with Bigtera's VirtualStor Scaler storage platform and running on our S-Series Storage Servers. VirtualStor Scaler provides customers with a cost effective x86 scale-out storage solution that allows them to pay as they grow. VirtualStor Scaler's scale-out architecture provides the flexibility to specify the storage type (NAS, SAN, object storage), performance (IOPS and throughput), and efficiency all while delivering resilient and secure capacity. VirtualStor Scaler's unique advantages include offering multi-tenant storage capabilities to provide different 'virtual storage' for different tenants, making storage management flexible, as well as providing functionality to consolidate legacy devices and help seamlessly migrate old data to a new storage system without downtime.

Diagram D: AI / Data Science Cloud Platform Storage Platform Features

GIGABYTE invites you to visit our booth at COMPUTEX 2018 and learn more about how our products can help you in building your own private cloud infrastructure, as well as other solutions to meet your enterprise IT and data center computing needs.

GIGABYTE @ COMPUTEX 2018

Date & Time:

Tuesday 5th June to Friday 8th June 9.30am ~ 6.00pm, Saturday 9thJune 9.30am ~ 4.00pm

Location:

Taipei World Trade Center Hall 1, Booth D0002

For more information on GIGABYTE Server products, please visit: http://b2b.gigabyte.com

For more information on InfinitiesSoft CloudFusion, please visit: http://www.infinitiessoft.com

For more information on ITRI's IOD-MB, please visit: http://www.itri.org.tw

For more information on Bigtera VirtualStor Scaler, please visit: http://www.bigtera.com

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Gigabyte Technology Co. Ltd. published this content on 04 June 2018 and is solely responsible for the information contained herein. Distributed by Public, unedited and unaltered, on 04 June 2018 02:12:01 UTC