Welcome to this Infinia demo. Today we'll be showing how Infinia can handle all the IO needs in an AI data pipeline. The Infinia architecture can be broken down into sections.Storage services providing enhanced resilience and elastic scale capabilities of the storage itself. The data plane comprised of a key value store as well as the presentation of data to clients via IO protocols. SQL queries of the KV store data and metadata and an SDK to integrate directly with applications and frameworks.And finally, ...

Welcome to this demonstration. Today we'll be showing how DDN enables a one-click high-performance rag pipeline for enterprise use. Our rag pipeline solution is enterprise class and easy to deploy and use in any cloud environment whether AWS, GCP, Azure, any NCP cloud and of course on prem.Let's take a closer look at the architecture. This rag pipeline solution is made of several NVIDIA Nemo NIMS or NVIDIA inference microservices which host embedding reranking LLM models a milild vector database a front-end ...

Welcome to this demonstration. Today we'll be showing how Infinia can be used with Apache Spark. Most AI workflows follow a common set of data functions, data collection, pre-processing, tagging, and indexing that form the data preparation stages of a data pipeline.Once the data is ready, it then is used for training and validation stages before finally being deployed once the model has achieved a certain level of predictive accuracy. Infinia is a key component of this workflow. The Infinia architecture shi ...

Welcome to this demonstration. Today we're going to show you a brief look at the performance of DDN Infinia in Oracle Cloud Infrastructure. Because this is a tech preview, the information presented is for potential future integrations.The overall capabilities, including the performance of this feature, can and will change. No timelines for delivering this capability should be inferred from this demo. The Infinia architecture provides a broad set of capabilities for data management.starting with a variety of ...

Performance Comparison - DDN Infinia writes chunks at 0041 seconds (4 milliseconds) per chunk, significantly faster than AWS [6] - AWS object store writes each chunk at 01169 seconds (112 milliseconds) per chunk [7] - DDN Infinia uploads a 628-chunk document in approximately 25 seconds, while AWS takes around 74 seconds [7] - DDN Infinia is approximately 285 times faster than AWS in document upload [7] - DDN Infinia retrieves chunks in 01600 seconds (160 milliseconds) total, averaging 32 milliseconds per chunk [13] - AWS retrieves chunks in 165 seconds, with each chunk taking 331 milliseconds [14] - DDN Infinia is 103 times faster than AWS in total query retrieval time [14] AI Pipeline Impact - With DDN Infinia, an analyst can upload and query an annual report in just 2 seconds [8] - A 30x performance advantage transforms the entire AI pipeline, making documents readily available for AI consumption [9] - Reduced latency with DDN Infinia can save significant time, potentially turning a 5-minute research task into 3 seconds [15] - Latency compounds across multiple users and sessions, impacting GPU economics and overall productivity [15]

RAG Acceleration with DDN Infinia - DDN Infinia accelerates retrieval-augmented generation (RAG) by removing I/O and object storage delays [1] - DDN Infinia delivers sub-second retrieval [1] - DDN Infinia achieves 96% GPU utilization [1] - DDN Infinia enables seamless scaling for hybrid vector and keyword search workloads [1] Key Benefits - DDN Infinia accelerates hybrid RAG retrieval [1] - DDN Infinia reduces latency and maximizes throughput [1] - DDN Infinia streamlines vector search and context retrieval [1] - DDN Infinia improves LLM performance in enterprise AI environments [1] DDN Overview - DDN is a pioneer in high-performance data storage and management [1] - DDN delivers innovative solutions that empower organizations across the globe [1]

[Music] The countdown is on. SC25 is almost here and DDN is heading to St. Louis this November 17th through the 20th.Here's a sneak peek at what's in store. [Music] [Applause] DDN is the exclusive IO sponsor at Supercomputing 25. Find us at booth 1527, that's 1527, for live demos, our booth theater, and book a one-on-one meeting with our experts building tomorrow's AI and HPC infrastructure.[Music] And don't miss BDN's Beyond Artificial Data Summit, supported by NVIDIA and sponsored by Google Cloud and Supe ...

AI Inference Challenges & KV Caching Solution - AI inference faces challenges with large context windows, impacting tokenization and latency [1][2] - Caching context tokens speeds up responsiveness, lowers latency, and allows storing larger context amounts [4] - Effective caching requires storage systems with low latency and large capacity at scale [5] DDN's Solution & Performance - DDN's Exoscaler platform enables high-performance KV caching for AI inference, improving user concurrency, responsiveness, and user experience [7] - DDN leverages GPU direct storage (GDS) for cached engine [9] - Caching demonstrates a 10x improvement in performance with larger context [14] - DDN's Exoscaler performance can improve time to first token during inference by 10-25x [16] - DDN improves response times, provides larger cache repository space, and delivers cost-effective performance and capacity density [17] Capacity Implications - KV caching accelerates the end-user experience, putting a premium on high-performance shared storage [16] - Approximately 200,000 input characters resulted in a cache of 796 files, totaling almost 13 gigabytes [15]

Hi everyone, welcome to the Rav show. We are your at NVIDIA GDC in Washington and I'm super excited to be with Joe from DDN. Joe, welcome to the Rav show.Super excited to chat today. >> Thank you. Thank you.Pleasure to be here. Thanks for coming over here. Appreciate it.>> Yes. Uh Joe, uh I know we'll be talking a lot about you know the AI ROI industry impact AI factories and uh what's happening at DDN. But just before getting into that, would you like to quickly introduce yourself.Tell us more about what y ...

FPT AI Factory Overview - FPT AI Factory provides AI platform and cloud services through collaboration with Nvidia, DDN, and other partners [1] - FPT AI Factory has developed two AI factories in Vietnam and Japan [1] - FPT AI Factory aims to make AI accessible to everyone, from large enterprises to small startups and research organizations [2] Strategic Partnerships - FPT AI Factory selected DDN due to its high provision, reliability, encryption, and service [2] - DDN offers great performance combined with space efficiency and aligns with FPT AI Factory's AI infrastructure ecosystem [3] - Nvidia systems are integrated with the DDN platform, and Nvidia's related products are tested on the DDN solution [3] AI Applications and Impact - Information technology and software, media and entertainment, and education are leading the way in AI integration [4] - Landing AI uses FPT AI Factory to shorten model training speed, speed up feature deployment, and optimize cost [5] - FPT AI Agent enhanced operational efficiency at Home Credit Vietnam's contact center, increasing performance by 50% and reducing operational cost by 60% [5] Sovereign AI and Business Transformation - FPT AI Factory enables businesses and organizations to speed up AI development while maintaining sovereign AI [6] - FPT AI Factory is transforming AI into practical business tools accessible across Vietnam's economy [6]