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New IBM Storage Solution: A Global Data Platform Architected to Break AI and Performance Barriers

By David Wohlford posted Tue May 17, 2022 12:30 AM

  


Register for the webinar Breaking performance barriers for AI and hybrid cloud on Tuesday, May 17 at 11 AM ET. 

Artificial intelligence (AI) is rapidly being adopted and embedded into business and society.1 AI allows organizations to make better decisions and improve core business processes2.   The beginning of an AI pipeline is data with a continual need of more data to achieve more results3.   With more data comes more challenges and we start to see there is no AI without an IA (information architecture).  Innovation is needed if we are going to speed up and solve the difficult data challenges and barriers that exist.  Barriers such as data silos, infrastructure complexity, data mobility, application performance and the continual drive for forklift upgrades.



The goal should be to break these barriers and create a data platform that provides:

  • performance with multiple data interfaces
  • data connections that break silos
  • data automation for the management of all this data
  • data security that creates secure connections and secure data resources

That is why IBM® Storage has engineered a global data platform. This software platform consists of a set of core data services, with each core data service containing one or more specific data services to help break data barriers and solve customer application requirements.

The global data platform is designed with an integrated set of data services that are easy to upgrade without data disruption, easy to use with a GUI and API access, and is included with each deployment of our IBM Spectrum® Scale software.   To learn more about the value that customers have obtained with the IBM global data platform and IBM Spectrum Scale software, read  Forrester’s The Total Economic Impact™ Of IBM Spectrum Scale.

The functionality of the global data platform has its roots in over 23 years of customers that started in 1998 as IBM Global Parallel File System (GPFS™).   Since that time, it has grown to over 4000 customers and has become both a software defined platform with IBM Spectrum Scale and simple to deploy building blocks with IBM Elastic Storage® System (ESS).



Today we are pleased to announce an important milestone in the history for IBM Spectrum Scale and IBM ESS, the IBM ESS 3500.  This exciting new addition to IBM ESS product family will be generally available on May 20 and is available now for ordering.



The IBM ESS 3500 has been enhanced for easy installation and scalability which is powered by IBM Spectrum Scale software.  It is targeted for AI, machine learning (ML), high-performance computing (HPC), and analytics workloads.  With the ability to run applications in parallel the system is also well suited for data collaboration, critical business applications, hybrid cloud applications and consolidation of multiple workloads on a single system. (See table).

Workloads and Applications

Use Cases

Business Impact

AI/ML/HPC

NVIDIA, TensorFlow, Caffe, Pytorch, IBM Cloud® Pak for Data, ML Kit, AWS Lambda, AWS SageMaker …

Faster GPU and AI analysis with access to more data and connected data with high-performance data access services

Analytics

Cloudera, Hadoop, Apache Spark™, SAS®, Tableau, Python, Power BI, …

Eliminate silos and speed time to value with data caching services and combined HDFS and S3

Collaboration

Media Development, AI Model Development, Computer Aided Engineering

Increase workgroup productivity with easier access to more data from edge to core to cloud

Critical Apps

Business critical applications that have expanding data requirements

Maintain business continuity with data that is always online and secure with security services

Hybrid Cloud

Red Hat® OpenShift® workloads, backup and archive, applications that move data or access on-prem and cloud

Faster time to production as data is consumed anywhere and connected everywhere

Consolidation

Data lake, data ocean, and big data

Lower costs as data is resilient and accessible without duplication



            • 2u per node
            • 84, 7.68, 15.36 TB NVMe flash drives
            • Scale-up from 12 to 24 drives


New Controller

  • AMD 7642 Processor with ~12%+ performance
  • Four PCIe Gen4 slots
  • Two integrated network ports (separation of MGMT and BMC)
  • Streamlined design for better thermal results
  • Simplified Service

Future-ready power supply [2000W]

  • Ready for additional HDD enclosure units
  • Ready for enhanced NVMe flash drives


                             Up-to 1.8TB/s per rack                                    As low as 17ms global access

                             Up-to 633YB per cluster                                  Up-to 24M IOPs per rack


IBM ESS 3500 already has over 200PBs of NVMe flash capacity on order by customers as demand for this new model is ahead of schedule.  Customer can plug this system into their existing environment in a few hours and start to see the benefits of what a global data platform can achieve.  

        • Scalability from 46TB to 633YB
        • Break performance barriers for AI workloads
        • Access file and object data locally from the edge, the core, and the cloud
        • Reduce local capacity requirements by connecting data silos
        • Secure data assets with multiple data security services


 

Find out more about our IBM ESS 3500 and the easiest was to deploy the global data platform by visiting IBM ESS product page.

Register now for the Free webinar

 

 

1 https://www.ibm.com/thought-leadership/institute-business-value/report/ai-data-integration

2 “Why is AI important” https://csuglobal.edu/blog/why-is-artificial-intelligence-so-important

3 “Artificial Inteligence and Machine Learning” MIT Lincoln Laboratory: https://www.youtube.com/watch?v=t4K6lney7Zw


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