The ever-present connectivity in our lives, and the data storage demands that come with it, is growing exponentially. The projected material supply for silicon-based memory technologies is unable to satisfy future demand, therefore, alternative memory materials are being explored in academia and industry1. DNA is analogous to a biological hard drive. It carries and transfers information with exceptional density, stability, and energy efficiency, making it a compelling alternative to current non-volatile information storage technologies.

Google will provide an overview of their experience developing Redfish and Swordfish client applications. This session will provide an overview of lessons learned through the initial proof-of-concept through development phases and will include recommendations to both client and storage vendor implementers of areas that may require additional focus.

If you haven’t caught the new wave in storage management, it’s time to dive in. This presentation provides a broad look at the Redfish and Swordfish ReSTful hierarchies, maps these to some common applications, and provides an overview of the Swordfish tools and documentation ecosystem developed by SNIA’s Scalable Storage Management Technical Work Group (SSM TWG) and the Redfish Forum. It will also provide an overview of what’s new in ’22, including enhancements to NVMe support, storage fabric management, and capacity and performance metric management.

NVMe over IP is a technology able to provide complete and scalable SAN solutions. Security is of paramount importance for SANs and the fundamental methods to secure NMVe over IP fabrics (i.e., DH-HMAC-CHAP authentication and TLS secure channel) have been defined. However, the security provisioning of these methods does not scale yet to large fabrics.

Computational Storage offers near-data acceleration, and it is gaining popularity with recent commercialization and standardization efforts. In this talk, we present how Computational Storage can be used to scale the performance of a key-value storage engine and deep learning training workloads. We propose a new key-value storage engine, named RETINA, where Computational Storage, Samsung SmartSSD, accelerates its data processing and user-defined processing pipelines.

Software-Enabled Flash™ (SEF) technology, a vendor-neutral Linux Foundation open source project, fundamentally redefines how flash memory is used for cloud and enterprise applications, providing storage developers the power to control flash memory data placement, latency outcomes and isolation. This session will dive deep into: using the new Software-Enabled Flash SDK to build applications, traditional I/O stacks vs. SEF implementations, configuration and control options available to the programmer, and how to get the most from SEF-based applications.

In this presentation, we will describe a complete end-to-end Software Defined Storage (SDS) solution for cloud data centers using Infrastructure Processing Units (IPUs). IPUs provide a high performance NVMe interface to host, abstracting away the details of networked storage and enabling storage disaggregation and bare-metal hosting. NVMe/TCP is a high performance protocol widely deployed because of its ease of deployment and better scalability in large scale-out networks.

With the ongoing work in the CS TWG, the chairs will present the latest updates from the membership of the working group. In addition, the latest release will be reviewed at a high level to provide attendees a view into next steps and implementation of the specification in progress. Use cases, Security considerations, and other key topics with also be addressed.

Modern AI systems usually require diverse data processing and feature engineering at a tremendous scale and employ heavy and complex deep learning model that requires expensive accelerators or GPUs. This leads to the typical design of running data processing and AI on two separate platforms, which leads to severe data movement issues and creates big challenges for efficient AI solutions.

Learn what is happening in NVMe to support Computational Storage devices. The development is ongoing and not finalized, but this presentation will describe the directions that the proposal is taking. Kim will describe the high level architecture that is being defined in NVMe for Computational Storage. We will describe how this new command set fits within the NVMe I/O Command Set architecture. The commands that are necessary for Computational Storage will be described. We will discuss a proposed new memory model that is able to be used for computational programs.