Name: Why Distributed Edge Data is the Future of AI
Start: 2023-10-03T17:00:00Z
End: 2023-10-03T17:00:59.000Z
Location: BrightTALK
Rating: 0

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In today's world of AI/ML, high-performance computing, and data centers, RDMA (Remote Direct Memory Access) is essential due to its ability to provide high-speed, low-latency data transfer. This technology enhances scalability, reduces CPU overhead, and ensures efficient handling of massive data volumes, making it crucial for modern computing environments. But how does it actually work?

In this session, we'll define RDMA, explore its historical development, and its significant benefits. In addition, we’ll provide an in-depth look at RDMA over Converged Ethernet (RoCE) and InfiniBand (IB), cover the fundamental objects, Verbs API, and wire protocol. 

Key Takeaways:
1. Insights into the historical development and evolution of RDMA technology.
2. Comprehensive understanding of RDMA and its role in modern computing.
3. Detailed exploration of RDMA implementations
4. Explanation of fundamental RDMA components, such as the Verbs API and wire protocol (e.g., IB and RocE)

Join us for an insightful SNIA Data, Storage & Networking webinar on RDMA.

Everything You Wanted to Know About RDMA But Were Too Proud to Ask

As artificial intelligence continues to transform industries, the demands on storage systems are evolving at an unprecedented pace. Join STA for a dynamic roundtable discussion featuring industry experts, including Patrick Kennedy of ServeTheHome, J Metz, Chair of SNIA, and STA board member Jeremiah Tussey. Together, they’ll explore the trends and technologies shaping the future of storage in an AI-driven world and how organizations can prepare for these changes.

What You’ll Learn:
- The impact of AI on storage architectures, including advances in SAS and other technologies.
- How storage scalability and performance requirements are adapting to AI workloads.
- Emerging innovations in storage management and data processing for AI-driven applications.
- Real-world insights into optimizing storage solutions for machine learning and deep learning.
- Predictions for the future of storage in AI, including opportunities and challenges.

Don't miss this opportunity to gain expert insights and join the conversation about the next wave of storage innovation.

Storage Trends in AI 2025

Artificial intelligence and Machine learning (AI/ML) is a hot topic in every business at the moment, and there is a growing dialog about what constitutes an Open Model, is it the weights? Is it the data?

Those are important questions, but equally important is ensuring that the tooling and frameworks to train, validate, fine-tune, and perform inference are open source. Storage systems are a crucial component of these workflows, how can open-source solutions address the needs for high capacity and high performance?

Data is key to any and all AI/ML workflows, without it there would be no data to use as an input for model training, re-evaluation and refinement of models, or even just securely storing models once training is complete, especially if they have taken weeks to produce!

Open source solutions like Ceph can provide almost limitless scaling capabilities, both for performance and capacity. In this webinar, learn how Ceph can be used as the backing store for AI/ML workloads.
We’ll cover:
• The demands of AI on storage systems
• How open source Ceph storage fits into the picture
• How to approach Ceph cluster scaling to meet AI’s needs
• How to get started with Ceph

Ceph Storage in a World of AI/ML Workloads

New Memories like MRAM, ReRAM, PCM, or FRAM are vying to replace embedded flash and, eventually, even embedded SRAM.  Are there other memory technologies threatened with similar fates?  What will the memory market look like in another 20 years?
Catch up on the latest in new memory technologies in this fast-paced, entertaining panel, as we explain what these new memory technologies are, the applications that have already adopted them in the marketplace, their impact on computer architectures and AI, the outlook for important near-term changes, and how economics dictate success or failure.  Noted analysts Jim Handy of Objective Analysis and Tom Coughlin of Coughlin Associates, moderated by Arthur Sainio, SNIA PM Special Interest Group Co-Chair, will present the findings of their latest report as they discuss where emerging memories complement CXL, Chiplets, Processing In Memory, Endpoint AI, and wearables, and they explain the inevitability of a conversion from established technologies to new memory types.

A Deep Look at New Memories

The SNIA Cloud Storage Technologies Initiative (CSTI) conducted a poll early in 2024 during a live webinar “Navigating Complexities of Object Storage Compatibility,” citing 72% of organizations have encountered incompatibility issues between various object storage implementations. These results resulted in a call to action for SNIA to create an open expert community dedicated to resolving these issues and building best practices for the industry.  

Since then, SNIA CSTI partnered with the SNIA Cloud Storage Technical Working Group (TWG) and successfully organized, hosted, and completed the first SNIA Cloud Object Storage Plugfest (multi-vendor interoperability testing), co-located at SNIA Developer Conference (SDC), September 2024, in Santa Clara, CA. Participating Plugfest companies included engineers from Dell, Google, Hammerspace, IBM, Microsoft, NetApp, VAST Data, and Versity Software. Three days of Plugfest testing discovered and resolved issues and included a Birds of a Feather (BoF) session to gain consensus on next steps for the industry. Plugfest contributors are now planning two 2025 Plugfest events in Denver in April and Santa Clara in September.

This webinar will share insights into industry best practices, explain the benefits your implementation may gain with improved compatibility, and welcome your client and server cloud object storage team to join us in building momentum. Join us on November 21st where we’ll discuss:  
• Implications on client applications
• Complexity and variety of APIs 
• Access control mechanisms 
• Performance and scalability requirements
• Real-world incompatibilities found in various object storage implementations
• Missing or incorrect response headers
• Unsupported API calls and unexpected behavior

More information:
• SNIA CSTI https://www.snia.org/groups/csti
• SDC'24 https://www.sniadeveloper.org/
• Cloud Object Storage Plugfest (Sept. 2024)  https://www.sniadeveloper.org/cloud-object-storage-plugfest

Building Community to Tackle Cloud Object Storage Incompatibilities

Join us for an insightful webinar on the transformative impact of AI on networking. This session will delve into the various use cases of AI, the nature of traffic for different workloads, and the network impact of these workloads. We will explore the multiple networking challenges posed by AI and how Ethernet is evolving to meet these demands. Special focus will be given to congestion issues during model training, the role of Ultra Ethernet Consortium (UEC), and the specific requirements related to training large language models (LLMs) and other use cases.

Learning Objectives:
- Understand the different types of Network Topologies typically used with AI workloads.
- Identify the nature of traffic for various AI workloads and their impact on networks.
- Learn about the challenges Ethernet faces with AI workloads and the solutions being implemented.
- Explore a specific use case to see how Ethernet addresses bandwidth and congestion issues.

Don’t miss this opportunity to stay ahead in the rapidly evolving field of AI and networking. Register now to secure your spot and gain valuable insights from industry experts!

Ethernet in the Age of AI: Adapting to New Networking Challenges

This presentation examines the critical role of storage solutions in optimizing AI workloads, with a primary focus on storage-intensive AI training workloads. We will highlight how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms. We will explore how AI frameworks like PyTorch utilize different storage connectors to access various storage solutions. Finally, the presentation will delve into the use of file-based storage and object storage in the context of AI training: 
 
Attendees will:
- Gain a clear understanding of the critical role of storage in AI model training workloads
 - Understand how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms
- Learn how AI frameworks like PyTorch use different storage connectors to access various storage solutions.
- Explore how file-based storage and object storage is used in AI training

The Critical Role of Storage in Optimizing AI Training Workloads

Unlocking a Sustainable Future for Data Storage

In a world of surging data demands, how can we reduce the environmental toll of storage solutions? Discover the power of the circular economy to reshape the storage industry for a greener tomorrow with this webinar, featuring Jonmichael Hands (Co-Chair SNIA SSD SIG and Board Member, Circular Drive Initiative) and Shruti Sethi (Sr. PM at Microsoft and Leadership Team, Open Compute Project-Sustainability).

Key Highlights:

- Circular Drive Initiative: Rethink the lifecycle of storage devices—from design to end-of-life—to unlock significant environmental benefits.
- Media Sanitization Best Practices: Securely erase data to enable reuse, extend device life, and cut down on e-waste. Explore techniques like:
- - Cryptographic erase
- - Block erase
- - Overwrite methods
- Compliance & Transparency: Learn how standards like IEEE 2883-2022 and ISO/IEC 27040:2024 guide secure data disposal, with organizations like SERI R2 and ADISA leading the charge in setting industry benchmarks.
- Carbon Accounting in Storage: Understand how tracking and reducing carbon emissions in storage aligns with global sustainability goals.

This session is your roadmap to driving real change by adopting circular economy principles, embracing advanced sanitization methods, and leveraging carbon accounting to reduce the industry’s environmental footprint.

Advancing Sustainable Storage: The Impact of the Circular Economy, Media Sanitization Policies, and Carbon Accounting

The key to optimal SAN performance is managing performance impacts due to congestion. The Fibre Channel industry introduced Fabric Notifications as a key resiliency mechanism for storage networks in 2021 to combat congestion, link integrity, and delivery errors. These functions have been implemented by the ecosystem and have enhanced the overall user experience when deploying Fibre Channel SANs. This webinar explores the evolution of Fabric Notifications and the available solutions of this exciting new technology. In this webinar, you will learn the following:
• The state of Fabric Notifications as defined by the Fibre Channel standards.
• The mechanisms and techniques for implementing Fabric Notifications.
• The currently available solutions deploying Fabric Notifications.

The Evolution of Congestion Management in Fibre Channel

Organizations often operate data centers in multiple locations and are often geographically distributed to provide scale and disaster recovery capabilities. As with any fabric topology, scalability, data integrity and security are key requirements. This webinar will discuss how Fibre Channel can be effectively deployed in these applications using optical transport technology.  Topics to be covered:
• Optical Transport 101: A brief survey of optical networking (DWDM) technology 
• Fibre Channel transport via OTN 
• Robustness: Optical transport protection options: Resiliency against fiber outages
• Security: Optical transport OTN encryption: No-overhead layer 1 encryption that can be combined with IPSec or other higher-layer security protocols

Fibre Channel Data Center Interconnects (DCI): 64G FC and More

The digital landscape is in hyperdrive, demanding an IT metamorphosis that transcends mere tools. Enter AIOps – not just a technological upgrade, but a paradigm shift redefining how we approach IT operations. This presentation delves beyond the nuts and bolts, unveiling AIOps as a revolution that infuses AI's intelligence into the very fabric of IT thinking and processes.
Key Themes:
• From Dev to Production and Reactive to Proactive: Revolutionizing the IT Mindset: We'll move beyond the "fix it when it breaks" mentality, embracing a shift left, a future-proof approach where AI analyzes risk, anticipates issues, prescribes solutions, and learns continuously.
• Beyond Siloed Solutions: Embracing Holistic Collaboration:  AIOps fosters seamless integration across departments, applications, and infrastructure, promoting real-time visibility and unified action.
• Automating the process: From Insights to Intelligent Action: Dive into the world of self-healing IT, where AI-powered workflows and automation resolve issues and optimize performance without human intervention.

AIOps: Reactive to Proactive – Revolutionizing the IT Mindset

Data is one of the most critical resources of our time. Storage for data is always a critical architectural element in any data center. There are considerations for storage: performance, scalability, reliability, etc. A decade ago, the market was aggressively embracing public storage because of its agility and scalability. In the last few years, people are rethinking that approach, moving toward on-premises storage with cloud consumption models. The new cloud native architecture on-premises has the promise of the traditional data center’s security and reliability with cloud agility and scalability. 
Ceph, an enterprise unified SDS, is the perfect solution for this cloud native on-premises architecture. In this webinar, we will describe how Ceph is uniquely qualified to satisfy this architecture and how the technology community is investing to enable the vision of “Ceph, the Linux of Storage Today”.

Ceph: The Linux of Storage Today

What new storage trends are developing in the coming year? What applications and other factors are driving these trends? Learn from this discussion between industry experts Jeff Janukowicz, Research Vice President at IDC; Brian Beeler, Owner and Editor In Chief, StorageReview.com; and Cameron T. Brett, SNIA STA Forum Chair.

This discussion will cover:

·      How are AI and machine learning affecting storage needs?

·      What is the state of the storage industry in 2024?

·      Security concerns being addressed in data storage.

·      EDSFF E1 and E3: should you make the switch?

·      Is SAS dead? What is the role of SAS in the future of storage?

·      How to make data storage sustainable for current and future need.

Hear about applications driving upcoming trends and learn about market data illustrating the assertions. This promises to be a lively session and you don’t want to miss it!

Storage Trends 2024

The latest buzz around generative artificial intelligence (AI) ignores the massive costs to run and power the technology. Without any guard rails in place, what are the impacts of AI on sustainability and costs across our technology resources? This webinar will offer insights on the potentially hidden technical and infrastructure costs associated with generative AI, best practices and potential solutions to be considered, discussing:   

• Scalability considerations for generative AI in enterprises 
• Significant computational requirements and cost for Large Language Model inferencing 
• Fabric requirements and costs 
• Sustainability impacts due to increased power consumption, heat dissipation, and cooling implications 
• AI infrastructure savings - On-prem vs. Cloud
• Practical steps to reduce impact, leveraging existing pre-trained models for specific market domains

Addressing the Hidden Costs of AI

Any discussion about storage systems is incomplete without the mention of Throughput, IOPs, and Latency. But what exactly do these terms mean and why are they important?
Collectively, these three terms are often referred to as storage performance metrics. Performance can be defined as the effectiveness of a storage system to address I/O needs of an application or workload. Different application workloads have different I/O patterns, and with that arises different bottlenecks, so there is no “one-size fits all” in storage systems. These storage performance metrics help with storage solution design and selection based on application/workload demands
 In this webinar, we’ll cover:
• What storage performance metrics mean – understanding key terminology nuances
• Why users/storage administrators should care about them
• How these metrics impact application performance 
• Real-world use cases

Everything You Wanted to Know About Throughput, IOPs, and Latency

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.  

This webinar, with a broad cross-section of industry veterans, provides insight into the following:

• Defining the Gen AI dataflow bottlenecks
• Tools and methods for identifying acceleration options
• Matchmaking the right xPU solution to the target Gen AI workload(s)
• Optimizing the network to support acceleration options
• Moving data closer to processing, or processing closer to data
• The role of the software stack in determining Gen AI performance

Accelerating Generative AI – Options for Conquering the Dataflow Bottlenecks

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.

Emerging Memories Branch Out

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.
 
This analysis is based on years of experience with implementation, deployment and evaluation of a wide range of object storage systems on the market. Attendees will leave with a deeper understanding of the challenges around compatibility and how to address them in their own applications.
 
During this webinar, we'll call for participation in a Cloud Object Storage Plugfest, facilitated by SNIA and co-located at Storage Developer Conference (SDC) 2024, aimed at improving cross-implementation compatibility for client and/or server implementations of private and public cloud object storage solutions. This endeavor is designed to be an independent, vendor-neutral effort with broad industry support, focused on a variety of solutions, including on-premises and in the cloud.

Navigating the Complexities of Object Storage Compatibility

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

Why Distributed Edge Data is the Future of AI

Artificial Intelligence

Edge

Data Fabric

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Why Distributed Edge Data is the Future of AI

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