Core Message - AI is essentially HPC (High Performance Computing), emphasizing the importance of data in both fields for extracting intelligence and value [1] - DDN (DataDirect Networks) provides the "rocket fuel" or data intelligence infrastructure that enables better, faster, and more accurate insights from massive datasets in real-time [1] - Data intelligence is critical for AI transformation, enablement, and acceleration, requiring the unification, curation, and analysis of distributed data from various sources [1] Challenges and Solutions - Current challenges hindering AI acceleration include GPU scarcity, limited data center space, and insufficient power; a data intelligence framework is needed to alleviate these issues [2] - DDN's solutions focus on delivering more capabilities from existing GPUs, shrinking data center footprint, and lowering power consumption [2] - DDN accelerates data ingestion, freeing up GPU cycles, and optimizing networks to reduce time to insight and enhance value [2] DDN's Technology and Positioning - DDN is the only data intelligence platform deployed internally at NVIDIA, and also supports massive deployments like XAI with over 100,000 GPUs [1] - DDN's new technology, Infinia, is a high-performance, multi-tenancy data intelligence platform that supports multiple protocols and minimizes data movement [2] - DDN's solutions maximize the value from infrastructures deployed at scale in data centers and the cloud, benefiting both HPC and AI applications [3] Market Impact and Growth - DDN powers more than half a million GPUs and has deployments at the exobyte level, demonstrating significant growth and scale [3] - DDN's ability to solve challenges at massive scale translates to bulletproof stability and cost-effectiveness across a broad range of installations [3] - DDN aims to accelerate scientific and business outcomes by handling data at the edge, in data centers, and in the cloud [3]

Core Functionality - Exoscaler data intelligence platform supports multi-tenancy by leveraging VLANs and secure data partitions [1][2] - Client access controls prevent unauthorized data access, enhancing security [2] - Capacity management controls via quotas allow flexible space allocation to tenants [2] Technical Implementation - Network configuration utilizes VLANs with paired IP addresses for intracluster networking and tenant connections [3] - Each tenant maps to two IPs for multiple connections to each VLAN, ensuring high availability [3] - Multi-tenancy is enabled via EMF settings and synced across the cluster [4] - Clients without registered IPs on the appropriate VLAN lose system access due to VLAN isolation [5] Quota Management - Hard quotas enforce strict limits, preventing tenants from exceeding allocated capacity, ensuring total capacity of all tenants never exceed the cluster's capacity [7][9] - Soft quotas allow tenants to use shared capacity by overallocating quotas, potentially leading to less waste but requiring trust [7][10] - Hybrid approach combines soft and hard quotas, providing leeway while preventing excessive consumption of free space [11][12] Data Handling - The system supports on-the-fly quota adjustments while serving data to clients [9] - Demonstrated the creation of a 10 TB (Terabyte) test file to illustrate quota enforcement [8]

The fastest AI isn’t just about GPUs. It’s about removing I/O bottlenecks that slow your business objectives down. Discover how DDN Infinia and Oracle Cloud Infrastructure (OCI) are redefining AI performance. Join this Ask the Experts session to learn how Infinia’s high-performance, S3-compatible storage along Oracle’s powerful and scalable Cloud Infrastructure deliver ultra-low latency, massive throughput, and linear scalability for the most demanding AI workloads. What you’ll learn: - The biggest challeng ...

I mean the other thing I think is extremely enabling is the CUDA ecosystem which you fostered and nurtured and and and helped really people embark on now with CUDA OBJ I think it is opening all kinds of possibilities because people can now tie into this and apply it combination of Kudo OBJ NIMS you know the inference part of it for specific industries life sciences financial services autonomous driving and so on and so forth you take all these things you tie together with the advances that will be made in t ...

Benchmarking & Performance Evaluation - MLPerf and IO500 are trusted, third-party benchmarks that provide clarity for making informed decisions about AI and HPC infrastructure [1] - These benchmarks simulate real-world workloads to measure speed, scalability, and efficiency [1] - The session aims to equip decision-makers with the knowledge to evaluate storage solutions for AI and HPC environments confidently [1] Key Learning Objectives - Identify the most relevant benchmark results for AI & HPC decision-makers [1] - Understand what MLPerf and IO500 tests entail and their significance [1] - Translate performance and scalability metrics into tangible business outcomes [1] DDN's Position - DDN demonstrates leadership in AI performance, offering benefits to users [1] Expertise - The session features technical experts from DDN, including Joel Kaufman, Jason Brown, and Louis Douriez [1]

AI Model Efficiency & Adoption - DeepSync's approach highlights opportunities for significantly more efficient AI models than previously thought [1] - This efficiency is accelerating the adoption of AI across various sectors [1] Product Development & Integration - The company has launched R1, indicating a new product or platform [1] - R1 is designed to interact with Infinia data intelligence layer to solve problems [1]

Uh this is really interesting. You know our journey started out in high performance computing and high performance computing training foundation models and frontier models. That is the extreme version of high performance computing.And so so Nvidia and DDN um found our friendship and our long-term partnership through that origin. Now what we'd like to do as we train these models, these models can now uh turn the world's enterprises, all of our data from raw data into data intelligence. Yeah.And so now our wo ...

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Technology & Innovation - Omniverse is considered a phenomenal technology [1] - Digital twins in Omniverse can accelerate drug development [1] - Omniverse can maximize the likelihood of success and compress the time to take a drug to market [1] Pharmaceutical Industry Application - Developing a drug can cost billions of dollars and take years [1] - Omniverse can help explore multiple avenues in parallel for drug development [1] - Combining attributes from different experiments in Omniverse can maximize benefits [1]