On Demand Webinars
Workloads using generative artificial intelligence trained on large language models are frequently throttled by insufficient resources (e.g., memory, storage, compute, or network dataflow bottlenecks). If not identified and addressed, these dataflow bottlenecks can constrain Gen AI application performance well below optimal levels.
Given the compelling uses across natural language processing (NLP), video analytics, document resource development, image processing, image generation, and text generation, being able to run these workloads efficiently has become critical to many IT and industry segments. The resources that contribute to generative AI performance and efficiency include CPUs, DPUs, GPUs, FPGAs, plus memory and storage controllers. Join this webinar to hear a panel a broad of industry veterans who discuss the topic of accelerating Gen AI.
Emerging memories are now found in multiple applications both as stand-alone chips and embedded into systems on chips (SoCs) as they replace established technologies, including SRAM, NOR flash, and DRAM. In this webinar, SNIA CMSI members and leading experts Tom Coughlin (Coughlin Associates/IEEE President) and Jim Handy (Objective Analysis) will discuss the latest developments in MRAM, ReRAM, FRAM, PCM, and other new memory technologies to explain why, how, and when these technologies will grow, and how their success will impact both the semiconductor and the capital equipment markets.
Object Storage has firmly established itself as a cornerstone of modern data centers and cloud infrastructure. Ensuring API compatibility has become crucial for object storage developers who want to benefit from the wide ecosystem of existing applications. However, achieving compatibility can be challenging due to the complexity and variety of the APIs, access control mechanisms, and performance and scalability requirements.
In this webinar, we'll highlight real-world incompatibilities found in various object storage implementations. We'll discuss specific examples of existing discrepancies, such as missing or incorrect response headers, unsupported API calls, and unexpected behavior. We’ll also describe the implications these have on actual client applications.
OK, I'll be honest, the title is a little dramatic, but ask yourself this question, how much data do you have today, and have you ever considered what impact you are having on the environment? The reality is, data centers have been shown to account for approximately 1 – 1.5% of global electricity use. In this session, we will explore what sustainability is, and I will give you a hint, it’s not just environmental. We will look at the impact digitization can have on energy consumption, and therefore the environment, and some practical applications that you can do to help address data challenges to address environmental sustainability.
The enterprise storage market is rapidly expanding to include NVMe® and NVMe-oF products pervasively. This presents the challenge: how do you manage these as part of your enterprise data center?
As the NVM Express family of specifications continue to develop, the corresponding Swordfish management capabilities are also evolving. The SNIA Swordfish® management bundle (including the specification, schema, documentation, and more) has expanded to include full NVMe and NVMe-oF technology enablement and alignment across DMTF, NVMe and SNIA for NVMe and NVMe-oF technology use cases.
In conjunction with Redfish®, Swordfish's capabilities to manage NVMe and NVMe-oF devices in the enterprise provide a seamless management ecosystem.
This presentation will introduce management of NVMe and NVMe-oF technology with SNIA Swordfish. Using an example of the SNIA Swordfish functionality, the presenters will introduce how to manage the complexity of discovery controllers with the simplified model presented to Swordfish clients.
The days of simple, static, self-contained file systems have long passed. Today, we have complex, dynamic namespaces, mixing block, file, object, key-value, queue, and graph-based resources, accessed via multiple protocols, and distributed across multiple systems and geographic sites. These complexities result in new challenges for simplifying management.
The good news is, that the SNIA Cloud Data Management Interface (CDMI™), an open ISO standard (ISO/IEC 17826:2022) for managing data objects and containers, already includes extensive capabilities for simplifying the management of complex namespaces. In this webinar, attendees will learn how to simplify namespace management – the open standards way, including namespace discovery, introspection, exports, imports and more.
AI is disrupting so many domains and industries and by doing so, AI models and algorithms are becoming increasingly large and complex. This complexity is driven by the proliferation in size and diversity of localized data everywhere, which creates the need for a unified data fabric and/or federated learning. It could be argued that whoever wins the data race will win the AI race, which is inherently built on two premises: 1) Data is available in a central location for AI to have full access to it, 2) Compute is centralized and abundant.
Edge AI though, defies these assumptions. If centralized (or in the cloud) AI is a superpower and super expert, edge AI is a community of many smart wizards. As humans, we can appreciate the power of cumulative knowledge over a central superpower. In this webinar, we will touch on:
- The value and use cases of distributed edge AI
- How data fabric on the edge differs from the cloud and its impact on AI
- Edge device data privacy trade-offs and distributed agency trends
- Privacy mechanisms for federated learning, inference, and analytics
- How interoperability between cloud and edge AI can happen
With cloud data privacy regulations evolving worldwide and accelerated adoption of AI technologies such as ChatGPT, Large Language Models (LLMs) and more, companies must ensure data and AI models are compliant. Confidential AI is a new collaborative platform for data and AI teams to work with sensitive data sets and run AI models in a confidential environment. It includes infrastructure, software, and workflow orchestration to create a secure, on-demand work environment that meets organization’s privacy requirements and complies with regulatory mandates.
Since its ratification in late 2018, NVMe/TCP has gained a lot of attention due to its great performance characteristics and relatively low cost. Since then, the NVMe/TCP protocol has been enhanced to add features such as Discovery Automation, Authentication and Secure Channels that make it more suitable for use in enterprise environments. More recently, as customers evaluate their options and consider adopting NVMe/TCP for use in their environment, many find they need a bit more information before deciding how to move forward and are asking questions such as:
- How does NVMe/TCP stack up against my existing block storage protocol of choice in terms of performance?
- Should I use a dedicated storage network when deploying NVMe/TCP or is a converged network ok?
- How can I automate interaction with my IP-Based SAN?
Join us for an open discussion regarding these questions and more.
Data Fabric is an architecture, set of services and platform that standardizes and integrates data across the enterprise regardless of data location (On-Prem, Cloud, Multi Cloud, Hybrid Cloud), enabling self-service data access to support various applications, analytics, and use cases. The data fabric leaves data where it lives and applies intelligent automation to govern, secure and bring AI to your data.
This session will discuss:
- Different types of data sources for data fabric integration
- Unification of structured and unstructured data sources into the data fabric
- How to simplify data access by virtually connecting data end points across a hybrid cloud landscape
- Providing automatic enrichment leveraging AI to contextualize data with semantics and knowledge
- Apply global and automated data governance and data privacy policy enforcement for increased data protection and quality