SNIA Developer Conference September 15-17, 2025 | Santa Clara, CA
Automotive SSD Specification Update
Abstract
The next generation of automobiles moves to the adoption of PCIe for data communications in vehicles, and the JEDEC Automotive SSD solution enables a high performance, high reliability solution for this shared centralized storage. Features such as SR/IOV highlight the requirements of these computers on wheels with multiple SoC functions for vehicle control, sensors, communications, entertainment, and artificial intelligence.
Learning Objectives
- The attendee learns how cars are moving to PCIe for their communications fabric
- The attendee hears the requirements that JEDEC took into account in the design of the Automotive SSD
- The attendee hears about technical details including reliability and secutiry
Related Sessions
OCP Storage Project Update
This is an update on the activities in the OCP Storage Project.
Data-Intensive Inference Done Better: Scaling Models and RAG in Limited Memory with SSD Offload
Enterprises are rushing to adopt AI inference solutions with RAG to solve business problems, but enthusiasm for the technology's potential is outpacing infrastructure readiness. It quickly becomes prohibitively expensive or even impossible to use more complex models and bigger RAG data sets due to the cost of memory. Using open-source software components and high-performance NVMe SSDs, we explore two different but related approaches for solving these challenges and unlocking new levels of scale: offloading model weights to storage using DeepSpeed, and offloading RAG data to storage using DiskANN. By combining these, we can achieve (a) more complex models running on GPUs that it was previously impossible to use, and (b) greater cost efficiency when using large amounts of RAG data. We'll talk through the approach, share benchmarking results, and show a demo of how the solution works in an example use case.
State of the HPC-AI Market: Highlights from End-User Research on Technology Gaps for HPC and AI
Drawing from recent surveys of the end user members of the HPC-AI Leadership Organization (HALO), Addison Snell of Intersect360 Research will present the trends, needs, and "satisfaction gaps" for buyers of HPC and AI technologies. The talk will focus primarily on the Storage and Networking modules of the survey, with some highlights from others (e.g. processors, facilities, cloud) as appropriate. Addison will also provide overall market context of the total AI or accelerated computing market at a data center level, showing the growth of hyperscale AI, AI-focused clouds, and national sovereign AI data centers, relative to the HPC-AI and enterprise segments, which are experiencing diminishing influence in a booming market.
Chiplets, UCIe, Persistent Memory, and Heterogeneous Integration: The Processor Chip of the Future!
Chiplets have become a near-overnight success with today’s rapid-fire data center conversion to AI. But today’s integration of HBM DRAM with multiple SOC chiplets is only the very beginning of a larger trend in which multiple incompatible technologies will adopt heterogeneous integration to connect new memory technologies with advanced logic chips to provide both significant energy savings and vastly-improved performance at a reduced price point. In this presentation analysts Tom Coughlin and Jim Handy will explain how memory technologies like MRAM, ReRAM, FRAM, and even PCM will eventually displace the DRAM HBM stacks used with xPUs, on-chip NOR flash and SRAM, and even NAND flash in many applications. They will explain how DRAM’s refresh mechanism and NAND and NOR flash’s energy-hogging writes will give way to much cooler memories that will be easier to integrate within the processor’s package, how processor die sizes will dramatically shrink through the use of new memory technologies to replace on-chip NOR and SRAM, and how the UCIe interface will allow these memories to compete to bring down overall costs. They will also show how the approach will not only reduce the purchase price per teraflop, but also how the energy costs per teraflop will also improve.
