SSUG::Digital: 007 – Manage the lifecycle of your files using the policy engine
Digital EventThis episode will provide a comprehensive introduction to the IBM Spectrum Scale policy engine. It highlights the underlying architecture and how policies are executed in a IBM Spectrum Scale cluster. This episode also discusses example rules and policies facilitating Information Lifecycle Management accompanied with practical tips. Download slides here References Whitepaper: IBM Spectrum Scale …
SSUG::Digital: 008 – Scalable multi-node training for AI workloads on NVIDIA DGX, Red Hat OpenShift and IBM Spectrum Scale
Digital EventNvidia and IBM did a complex proof-of-concept to demonstrate the scaling of AI workload using Nvidia DGX, Red Hat OpenShift and IBM Spectrum Scale at the example of ResNet-50 and the segmentation of images using the Audi A2D2 dataset. The project team published an IBM Redpaper with all the technical details and will present the …
SC20 Meeting (Session 1): Storage for AI
The Spectrum Scale user group meets annually at the SC conference. For 2020 the user group will be split into two 90 minute digital sessions. The second session will be on Wednesday Nov 18th, 11 am EST >> Session 2: What is new in Spectrum Scale 5.1? << This session will focus on Storage for …
SSUG::Digital: 009 – Deep Thought: An AI Project for Autonomous Driving Development
Digital EventContinental, a tier-1 automotive supplier, runs a new high-performance cluster based on NVIDIA DGX, IBM Spectrum Scale and IBM ESS to boost autonomous driving development performance. Continental uses this system for deep learning, simulation, virtual data generation and related workloads. The new cluster reduces development time from weeks to hours. Speakers from Continental and the …
SSUG::Digital: 010 – Data Accelerator for Analytics and AI (DAAA)
Digital EventThis talk focuses on the need of data orchestration in enterprise data pipelines. It provides details about data orchestration and how to address typical challenges that customers face when dealing with large and ever-growing amounts of data for data analytics. While the amount of data increases steadily, AI workloads need to speed up in order …