Restarting for 2022, the SSUG::Digital talks are back with talks over two days.
Day 2 Talk 1: GPU Direct Storage with Spectrum Scale
With GPUDirect Storage (GDS) Nvidia has created a data path from the storage directly into the buffer of Nvidia GPUs. IBM Spectrum Scale is perfectly suited to take advantage of this feature from Nvidia to further enhance storage performance. This joint session by Nvidia and IBM development provides GDS overview, highlights how GDS has been integrated with Spectrum Scale and how it can be used to drive higher performance.
Day 2 Talk 2: Spectrum Scale performance improvements
Spectrum Scale is a highly scalable, high-performance storage solution for file and object storage. IBM continues to enhance Spectrum Scale performance, in response to recent hardware advancements and evolving workloads. This presentation will discuss performance related improvements in Spectrum Scale 5.X versions focusing on enhancements made in support of AI and HPC use cases, including improvements for IO 500 performance benchmark, improvements to RDMA to select NUMA aware adapters and more.
See >>here<< for sessions of Day 1 – Jan 18th, 2022.
User Group Host: Kristy Kallback-Rose
|Ingo Meents||Ingo Meents has been working as an architect in IBM Spectrum Scale and its predecessors’ development for more than 10 years. His current focus is on RDMA technologies like Nvidia’s GPU Direct Storage (GDS) to eliminate the IO bottleneck faced by modern AI applications. He is leading the agile team that has made GDS in Spectrum Scale generally available and is working on further enhancements.
|John Lewars (IBM)||John Lewars is a Senior Technical Staff Member leading performance engineering work in the IBM Spectrum Scale development team. He has been with IBM for over 20 years, working first on several aspects of IBM's largest high performance computing systems, and later on the IBM Spectrum Scale (formerly GPFS) development team. John's work on the Spectrum Scale team includes working with large customer deployments and improving network resiliency, along with co-leading development of the team's first public cloud and container support deliverables.
|Jay Vaddi||Jay Vaddi is a Storage Performance Engineer at IBM Tucson, AZ. He has been with IBM and the performance team for over five years. His focus is primarily on performance analysis and evaluations of IBM Spectrum Scale and IBM Elastic Storage System products.
|Kiran Kumar Modukuri ||Kiran Modukuri is a Principal software engineer at NVIDIA DGX Platform software team with special focus on accelerating IO pipelines for AI and Machine Learning. He is the Co-architect of NVIDIA MagnumIO GPUDirect Storage and he has technical contributions to Distributed Filesystems, caching and replication technologies over the last 16 years. Kiran has Master's degree in electrical and computer engineering from university of Arizona.
|Pidad D'Souza||Pidad D'Souza is a System Architect specializing in performance engineering of IBM Spectrum Scale and IBM POWER systems. He has been with IBM for over 17 years, leading system performance engineering of GPU accelerated systems designed for applications in the fields of AI & HPC. He has presented extensively at several international conferences, and delivered customer workshops and lab sessions.