THANK YOU FOR SUBSCRIBING
IBM introduces next-generation software-defined storage, IBM ESS 3500, and improves its global data platform to address AI adoption challenges.
FREMONT, CA: Data is the key element in unlocking value through new business and operational insights in the contemporary hybrid cloud reality environment. However, recent studies and IBM claim that data complexity and data silos are prominent hindrances to AI adoption. Therefore, overcoming this challenge has become a major focus for businesses to improve data access and transform business processes from supply chains and asset management to analytics.
To address these challenges, IBM announced major enhancements to their next-generation software-defined storage, IBM ESS 3500. This solution is designed to improve data delivery for AI workloads and enable faster time to market with cloud-scale performance and capacity. Enterprises are increasingly adopting AI and Kubernetes, which require a new paradigm that simplifies data access, boosts productivity and grows easily as these projects expand. IBM is aware of the need for distributed file and object workloads as well as the need to address a wide range of use cases, including design simulations, particularly AI and ML.
Improving Data Science and Optimising Application Development
IBM ESS 3500 is introduced to help customers accelerate data science, modernise and optimise application development, simplify and fasten DevOps, and advance content repositories. This new solution is enabled by spectrum scale, which is designed to provide security and availability to organisations. It also assists in supporting the unification of data from a myriad of sources across the core, edge, and cloud without the need to create additional copies of data.
It is observed that IBM customers are extensively relying on the capabilities of the IBM spectrum scale and the IBM ESS family. It offers them value in data resiliency and security with these solutions against accidental and malicious attacks that can lead to data loss. Moreover, clients commend the power and techniques IBM employs to tackle these issues. Currently, IBM is shifting their sales effort to the new IBM ESS 3500 to reach new customers as the new solution projects a higher level of functionality and performance with the IBM spectrum scale.
Improving AI Training Time Using IBM Spectrum Scale and IBM Elastic Storage Systems
The IBM ESS 3500 is optimised for AI-accelerated computing solutions, such as NVIDIA DGX systems with GPUDirect support. According to recent client surveys, IBM holds the ability to improve AI training time by as much as 70 per cent using the IBM spectrum scale and IBM elastic storage systems. This solution is designed to run compute-intensive workloads with the capacity to scale from 46TB to 1PBe effective capacity in a 2U form factor using LZ4 compression with a 2.5x compression rate. It is also indicated to support over 1.8TB/s in a 20-node rack configuration.
AI workloads require powerful infrastructure that delivers cost-effective performance and scale. Therefore, customers resolving prominent AI challenges depend on NVIDIA DGX systems and NVIDIA DGX SuperPOD. Establishing these systems’ collaboration with IBM, the new IBM ESS 3500 storage software allows customers to swiftly and easily raise their infrastructure to accelerate AI-powered insights from their data.