Application Requirements for Wider Adoption of Computational Storage Technology

As humanity embraces digital technologies at a rapid pace, data generation and consumption is growing at very high rate. In modern IT infrastructure, humongous amounts of data are being generated by various applications, devices and processes such as autonomous vehicles, social networks, genomics, and smart sensors. New AI and ML algorithms are being developed to effectively analyze the collected data and use it to achieve even greater efficiencies and productivity of applications. In traditional system architectures, data is fetched from persistent storage to high performance servers using high performance networks. Moving such large amounts of raw data to CPU for processing and analyzing is expensive in terms of amount of energy consumed, as well as compute and network resources deployed. Computational Storage (CS) technology promises to alleviate some of these inefficiencies in the system architecture by processing some of the data closer to the storage and thereby reducing large, unnecessary data movements. This evolution of system architectures must address application needs and requirements to achieve a viable and feasible CS solution. This presentation discusses some of the common application requirements that must be addressed by CS solutions for successful and wider adoption of CS technology.