This presentation by provides an overview of the NVM Express® ratified technical proposal TP4146 Flexible Data Placement and shows how a host can manage its user data to capitalize on a lower Write Amplification Factor (WAF) by an SSD to extend the life of the device, improve performance, and lower latency. Mike Allison, the lead author of the technical proposal will cover: a) The new terms associated with FDP (e.g., Placement Identifier, Reclaim Unit, Reclaim Unit Handle, Reclaim Groups, etc.); b) Enabling the FDP capability; c) Managing the Reclaim Unit Handles during namespace creation; d) How I/O writes place of the user data to a Reclaim Unit; e) The differences between other placement capabilities supported by NVM Express.

Learning Objectives 1) Obtain an understanding of the architecture of the NVM Express Flexible data placement (FDP) capability; 2) Learn how issue I/O write commands to place user data and avoid SSD garbage collection; 3) Understand the differences between FDP, ZNS, and Streams.

SSDs that support Zoned Namespace (ZNS) are increasingly popular for large-scale storage deployments due to their cost efficiency and performance improvements over conventional SSDs, which include 3-4x throughput increase, prolonged SSD lifetime, as well as making QLC media available to I/O heavy workloads. As the zoned storage hardware ecosystem has matured, its open-source software ecosystem has also grown. As a result, we are now emerging at a new stage that provides a solid foundation for large-scale cloud adoption. This talk describes SSDs that support Zoned Namespace s, the work of SNIA's Zoned Storage TWG to standardize ZNS SSD device models, and the quickly evolving software ecosystem across filesystems (f2fs, btrfs, SSDFS), database systems (RocksDB, TerarkDB, MySQL), and cloud orchestration platforms (Openstack and Kubernetes /w Mayastor, Longhorn, SPDK's CSAL).

Learning Objectives 1) ZNS SSDs; 2) Emerging hardware & software eco-system for zoned storage; 3) Zoned storage cloud adoption.

The IEEE Security In Storage Work Group (SISWG) produces standards that many storage developers, storage vendors, and storage system operators care about, including: a) A family of standards on sanitization: the IEEE 2883 family b) A family of standards on encryption methods for storage components: the IEEE 1619 family c) A standard on Discovery, Authentication, and Authentication in Host Attachments of Storage Devices: the IEEE 1667 specification IEEE has a different work group (IEEE P3172) focusing on post-quantum cryptography, but when they are done, a family method that recommends new quantum encryption for various storage types (e.g., block, stream) may be appropriate for SISWG’s IEEE 1619 family. IEEE has a different work group focusing on Zero Trust Security (ZTS, IEEE P2887), however an application of those principles for storage devices and systems is also within the purview of the IEEE SISWG.

Learning Objectives 1) Understand the scope of standards developed by the IEEE SISWG; 2) Understand the relevance of SISWG standards to the listener's business; 3) Understand how to participate in the IEEE SISWG.

The introduction of CXL has significantly advanced the enablement of memory disaggregation. Along with disaggregation has risen the need for reliable and effective ways to transparently tier data in real time between local direct attached CPU memory and CXL pooled memory. While the CXL hardware level elements have advanced in definition, the OS level support, drivers and application APIs that facilitate mass adoption are still very much under development and still in discovery phase. Even though memory tiering presents new challenges, we can learn a great deal from the evolution of storage from direct attached to storage area networks, software defined storage and early disaggregated/composable storage solutions such as NVMe over fabrics. Presented from the viewpoint of a real time block storage tiering architect with products deployed in more than 1 million PCs and servers.

It’s been a year since the announcement that Intel would “Wind Down” its Optane 3D XPoint memories. Has anything risen to take its place? Should it? This presentation reviews the alternatives to Optane that are now available or are in development, and evaluates the likelihood that one or more of these could fill the void that is being left behind. We will also briefly review the legacy Optane left behind to see how that legacy is likely to be used to support persistent memories in more diverse applications, including cache memory chiplets. Along the way we’ll show how Optane not only spawned new thinking on software, as embodied in the SNIA Nonvolatile Memory Programming Model, but also drove the creation of new communication protocols, particularly CXL and UCIe.

Learning Objectives: 1) Understand the growing role of emerging memory technologies in future processors; 2) Learn how Persistence, NUMA, and Chiplets have blossomed in Optane's wake; 3) See how SNIA's NVM Programming Model will support tomorrow's software, even though Optane won't be using it.

One of the goals of HPE’s Spaceborne Computer program is proving the value of edge computing. Spaceborne Computer-1 (SBC-1) was launched in August of 2017 with the latest available COTS (Commercial off the Shelf) hardware, including twenty solid state disks (SSDs) for storage. The disappointing durability of those SSDs will be covered; the Failure Analysis (FA) of them upon Return To Earth (RTE) will be presented and the mitigation done in Spaceborne Computer-2 will be detailed. HPE’s Spaceborne Computer-2 (SBC-2) launched in February of 2021 with over 6 TB of internal SSD storage. Onboard storage of ISS-generated “raw” data is critical to proving the value of edge computing, to delivering results and insights to scientists and researchers faster and to enabling deeper exploration of the cosmos. The storage design will be summarized, including the concept of operations (ConOps) for backup and disaster recovery. Several successful SBC-2 edge computing experiments will be reviewed, all of which demonstrate a reduction in download size to Earth of at least 95%. Additionally, Spaceborne Computer-2 has access to the ISS Payloads Network Attached Storage (PL-NAS). The PL-NAS is a NASA file server with five hard drive bays and allows onboard ISS systems to access a shared folder location on the PL-NAS. A summary of the decision to opt for SSDs on HPE’s Spaceborne Computer instead of traditional hard drives will be presented. SBC-2 exploitation of the PL-NAS for EVA safety operations will be detailed. Finally, the market for anticipated edge services is being better defined and concepts will be presented, all of which require stable and reliable storage at the edge.

Learning Objectives: 1)Storage considerations for space-based storage; 2) Value of capable "raw" storage to support edge computing, AI/ML and HPC; 3) Lessons learned from storage experiments in space; 4) Failure rates of SSDs in Space; 5) Future space-based services requiring storage.

Azure Disks provide block storage for Azure Virtual Machines and are a core pillar of the Azure IaaS platform. In this talk, we will provide an overview of Direct Drive - Azure's next-generation block storage architecture. Direct Drive forms the foundation for a new family of Azure disk offerings, starting with Ultra Disk (Azure's highest performance disks). We will describe the challenges of providing durable, highly-available, high-performance disks at cloud scale as well as the software and hardware innovations that allow us to overcome these challenges.

For the past three decades, PCI-SIG® has delivered a succession of industry-leading PCI Express® (PCIe®) specifications that remain ahead of the increasing demand for a high-bandwidth, low-latency interconnect for compute-intensive systems in diverse market segments, including data centers, Artificial Intelligence and Machine Learning (AI/ML), high-performance computing (HPC) and storage applications. In early 2022, PCI-SIG released the PCIe 6.0 specification to members, doubling the data rate of the PCIe 5.0 specification to 64 GT/s (up to 256 GB/s for a x16 configuration). To achieve high data transfer rates with low latency, PCIe 6.0 technology adds innovative new features like Pulse Amplitude Modulation with 4 levels (PAM4) signaling, low-latency Forward Error Correction (FEC) and Flit-based encoding. PCIe 6.0 technology is an optimal solution to meet the demands of Artificial Intelligence and Machine Learning applications, which often require high data bandwidth, low latency transport channels. This presentation will explore the benefits of PCIe 6.0 architecture for storage and AI/ML workloads and its impact on next-generation cloud data centers. Attendees will also learn about the potential AI/ML use cases for PCIe 6.0 technology. Finally, the presentation will provide a preview of what is coming next for PCIe specifications.

Los Alamos is working to revolutionize how scientific data management is done, moving from large Petabyte sized files generated periodically by extreme scale simulations to a record and column based approach. Along the journey, the NVMe Computational Storage efforts became a strategic way to help accomplish this revolution. Los Alamos has been working on a series of proof of concepts with a set of data storage industry partners and these partnerships have proven to be the key to success. This talk will summarize the three proof of concept applications of Computation Storage and some of the industry partnership projects that have helped pave the way for LANL and hopefully industry to new approaches to large scale data management.

Computational Storage is a new field that is addressing performance and scaling issues for compute with traditional server architectures. This is an active area of innovation in the industry where multiple device and solution providers are collaborating in defining this architecture while actively working to create new and exciting solutions. The SNIA Computational Storage TWG is leading the way with new interface definitions with Computational Storage APIs that work across different hardware architectures. Learn how these APIs may be applied and what types of problems they can help solve.