Storage Developer Conference

Current storage technologies include a range of security features and capabilities to allow storage to serve as a last line of defense in an organization’s defense in depth strategy. However, the threat landscape continues to change in negative ways, so new responses are needed. Additionally, the storage technology itself is changing to address the increased capacity and throughput needs of organizations. Technical work in ISO/IEC, IEEE, NVM Express, DMTF, OpenFabric Alliance, Trusted Computing Group (TCG), Open Compute Project (OCP), Storage Networking Industry Association (SNIA), etc. are introducing new storage technologies, specifying the way storage fits into increasingly complex ICT ecosystems, and identifying protection mechanism for data and the systems themselves. Understanding these developments and their interrelationships will be critical for securing storage systems of the future. This session highlights important storage security elements of both current and emerging storage technologies, including encryption, key management, storage sanitization, roots of trust and attestations, secure communications, and support for multitenancy. Like storage, security technologies are also changing, so crypto-agility, protocol changes, and security practices (e.g., zero trust) are explored.

Learning Objectives: 1) Understand current storage security guidance and requirements; 2) Identify security aspects of emerging storage technology; 3) Recognize the implications and challenges associated with securing storage.

The SNIA Computational Storage TWG is driving forward with both a CS Architecture specification and a CS API specification. How will these specification affect the growing industry Computational Storage efforts? Learn what is happening in industry organizations to make Computational storage something that you can buy from a number of vendors to move your computation to where your data resides. Hear what is being developed in different organizations to make your data processing faster and allow for scale-out storage solutions to multiply your compute power.

Learning Objectives: 1) Learn what is going on in the standards bodies; 2) Learn how the standards can help you utilize Computational Storage; 3) Learn about where Computational Storage is being standardized and how to get involved.

DNA data storage is an attractive option for digital data storage because of its extreme density, durability and eternal relevance. This is especially attractive when contrasted with the exponential growth in world-wide digital data production. In this talk we will present our efforts in building an end-to-end system, from the computational component of encoding and decoding to the molecular biology component of random access, sequencing and fluidics automation. We will also discuss some early efforts in building a hybrid electronic/molecular computer system that can offer more than just data storage, for example, image similarity search.

Learning Objectives: 1) Describe the properties of synthetic DNA as a digital data storage medium; 2) Describe how an end-to-end DNA data storage system works; 3) Describe how to perform certain types of computation with synthetic DNA molecules.

The SNIA Swordfish specification has expanded to include full NVMe and NVMe-oF enablement and alignment across DMTF, NVMe, and SNIA for NVMe and NVMe-oF use cases. This presentation will provide an overview of the most recent work adding detailed implementation requirements for specific configurations, ensuring NVMe and NVMe-oF environments can be represented entirely in Swordfish and Redfish environments.

Learning Objectives: 1) Describe how the NVMe and NVMe-oF environments can be managed in Swordfish and Redfish; 2) Provide an overview of current work in progress to extend NVMe and NVMe-oF manageability in Swordfish; 3) Describe the updated guidance for implementations in Swordfish profiles and documentation.

Over the past nearly three decades, PCI-SIG® has delivered a succession of industry-leading specifications that remain ahead of the curve of the increasing demand for a high-bandwidth, low-latency interconnect for compute-intensive systems in diverse market segments, including data centers, PCs and automotive applications. Each new PCI Express® (PCIe®) specification consistently delivers enhanced performance, unprecedented speeds, and low latency – doubling the data rate over previous generations. The PCIe 6.0 specification – targeted for final release in 2021 – will deliver 64 GT/s data rate (256 GB/s via x16 configuration), while maintaining backward compatibility with previous generations. In this session, attendees will learn the nuts and bolts of PCIe 6.0 architecture and how it will enable high-performance networking. Some key features of the upcoming specification include PAM4 encoding, low-latency Forward Error Correction (FEC), and backward compatibility with all previous generations of PCIe technology. This presentation will also highlight PCIe 6.0 technology use cases and the heterogenous computing applications that will be accelerated by PCIe 6.0 technology, including artificial intelligence, machine learning and deep learning. Finally, attendees will receive an update on the release timeline of the PCIe 6.0 specification later this year and rollout of the interoperability and compliance program.

Learning Objectives: 1) Attendees will learn the nuts and bolts of PCIe 6.0 architecture and how it will enable high-performance networking; 2) Key features of the upcoming PCIe 6.0 specification; 3) PCIe 6.0 technololgy use cases and the heterogenous computing applications that will be accelerated by PCIe 6.0.

Abstract Block storage access across Storage Area Networks (SANs) have an interesting protocol and transport history. The NVMe-oF transport family provides storage administrators with the most efficient and streamlined protocols so far leading to more efficient data transfers and better SAN deployments. In this session we will explore some of the protocol history to set the context for a deep dive into NVMe/TCP, NVMe/RoCE, and NVMe/FC. We will then examine network configurations, network topology, QoS settings, and offload processing considerations. This knowledge is critical when deciding how to build, deploy, operate, and evaluate the performance of a SAN as well as understanding end to end hardware and software implementation tradeoffs. Agenda SAN Transport History and Overview Protocol History Protocol Comparisons NVMe/FC Deep Dive NVMe/RoCE Deep Dive NVMe/TCP Deep Dive Networking Configurations and Topologies for NVMe-oF QoS, Flow Control and congestion L2 local vs L3 routed vs Overlay Offload Processing Considerations and Comparisons

Learning Objectives: 1) Cross Comparison of SAN transports; 2) First principles behavior for NVMe-oF transports; 3) Practical networking considerations for deploying NVMe-oF; 4) Implications of NVMe-oF transports for data flow and packet processing.

Traditional Storage Node consists of Compute, Networking and Storage elements. In this case, the entire node is a single failure domain and as such both data and meta data are maintained in storage. Emergence of CXL allows us to re-think the traditional storage node architecture. In future, the storage (behind CXL IO) and metadata memory (behind a CXL memory) can be disaggregated locally or across a bunch of storage nodes to improve the availability of the data. Further, memory persistence can be achieved at a granular level using CXL memory devices. Future extensions to CXL with fabric like attributes have potential to further extend the data replication capabilities of the storage platform. In this talk, we will discuss the various platform architecture options that are emerging for the storage node and how they can change the face of traditional storage node organization.

Learning Objectives: 1) Illustrate that the current architecture assumptions for Storage node need to be revisited; 2) Explore options for new storage node architecture with CXL; 3) Explore architecture options for storage node with a fabric extension (beyond today's CXL); 4) Encourage partnership with industry to work together on storage node innovation; 5) Explore storage infrastructure disaggregation and its value to future of storage.

Adopting new memory technologies such as Persistent Memory and CXL-attached Memory is a challenge for software. While libraries and frameworks (such as PMDK) can help developers build new software around emerging technology, legacy software faces a more severe challenge. At IBM Research Almaden we are exploring a new approach to managing heterogeneous memory in the context of Python. Our solution, PyMM, focuses on ease-of-use and is aimed primarily at the data science community. This talk will outline PyMM and discuss how it is being used to manage Intel Optane persistent memory. We will review the PyMM programming abstractions and some early data science use-cases. PyMM is currently an early research prototype with open source availability.

Learning Objectives: 1) Understand the emergence of heterogeneous memories (e.g., Optane, CXL-attached); 2) Understand the challenges facing integration of legacy s/w with new memory technology; 3) Introduction and demonstration of PyMM; 4) Outline of some existing use cases.

Storage interfaces have evolved more in the past 3 years than in the previous 20 years. In Linux, we see this happening at two different layers: (i) the user- / kernel-space I/O interface, where io_uring is bringing a low-weight, scalable I/O path; and (ii) and the host/device protocol interface, where key-values and zoned block devices are starting to emerge. Applications that want to leverage these new interfaces have to at least change their storage backends. This presents a challenge for early technology adopters, as the mature part of the Linux I/O stack (i.e., the block layer I/O path) might not implement all the needed functionality. While alternatives such as SDPK tend to be available more rapidly, the in-kernel I/O path presents a limitation. In this talk, we will present how we are enabling an asynchronous I/O path for applications to use NVMe devices in passthru mode. We will speak to the upstream efforts to make this path available in Linux. More specifically, we will (i) detail the changes in the mainline Linux kernel, and (ii) we will show how we are using xNVMe to enable this new I/O path transparently to applications. In the process, we will provide a performance evaluation to discuss the trade-offs between the different I/O paths in Linux, including block I/O io_uring, passthru io_uring, and SPDK.

Learning Objectives: 1) Understand the value of I/O passthru; 2) Understand the changes merged into the Linux kernel to support NVMe I/O Pasthru; 3) Understand how to leverage this new I/O path without application changes through xNVMe.

NVMe/TCP has the potential to provide significant benefits in application environments ranging from the Edge to Data Center. However, to fully unlock its potential, we first need to overcome NVMe over Fabrics' discovery problem. This discovery problem, specific to IP based fabrics, can result in the need for the Host admin to configure each Host to access the appropriate NVM subsystems. In addition, any time an NVM Subsystem is added or removed, the Host admin needs to update the impacted hosts. This process of explicitly updating the Host any time a change is made does not scale when more than a few Host and NVM subsystem interfaces are being used. Also, due to the de-centralized nature of this process, it also adds complexity when trying to use NVMe-oF in environments that require high-degrees of automation. For these and other reasons, Dell Technologies, along with several other companies, have been collaborating on innovations that enable an NVMe-oF IP Based fabric to be centrally managed. These innovations, being tracked under nvme.org’s Technical Proposals TP-8009 and TP-8010, enable administrators to set a policy that defines the relationships between Hosts and the NVM subsystems they need to access. These policies are then used by a Centralized Discovery Controller to allow each Host to automatically discover and connect to only the appropriate NVM subsystems and nothing else.

Learning Objectives: 1) Explain NVMe-oF’s discovery problem; 2) Review the network topologies that can support the automated Discovery of NVMe-oF Discovery Controllers; 3) Explore the differences between a FC SAN and an IP based SAN used to transport NVMe-oF/TCP; 4) Understand the proposed discovery process through in-depth review of the discovery protocol.