TECHunplugged is very excited about the rise of Computational Storage and the possibilities it opens to enable next-gen workloads. We’ve covered this not only in blog posts, but also in our very first Industry Insights research paper (free & available for download here).
Today, the SNIA (Storage Networking Industry Association) announced the creation of a technical work group that will focus on Computational Storage.
Computational Storage is a major paradigm shift in the IT industry and is perhaps one of the most transformational changes from an architectural perspective since the adoption of Von Neumann architectures. The premise of computational storage is to bring compute closer to storage to achieve greater performance and better scale certain type of compute operations without having to scale the system footprint from a traditional compute perspective. Computational Storage is particularly relevant in the following use cases: Big Data Analytics, AI, Machine Learning, Pattern Detection and others.
The SNIA Computational Storage TWG will focus on creating standards and ensuring interoperability of computational storage systems, as well as help defining interface standards for deployment, management, security and provisioning of computational storage. This will greatly aid this emerging and transformational technology to gain adoption and momentum from the market actors which can best leverage this technology.
This group consists of 13 founding members: Arm, Eideticom, Inspur, Lenovo, Micron Technology, Inc., NetApp, NGD Systems, Inc., Nyriad, Samsung Electronics Co. LTD., Scaleflux, SK Hynix, Western Digital Corporation, and Xilinx. The group contains not only pure computational storage vendors, but also broader actors from the industry delivering solid-state memory solutions or CPU/FPGA solutions, and thus represents a comprehensive spectrum of interest parties. We did cover Scaleflux and NGD Systems in our research paper and are thrilled that more industry actors are joining this Technical Working Group (TWG).