Qing Zheng Presents at Fifth Annual Storage Technology Showcase

Qing Zheng Presents at Fifth Annual Storage Technology Showcase

Qing Zheng Presents at Fifth Annual Storage Technology Showcase

Qing Zheng, a Scientist at Los Alamos National Laboratory’s High-Performance Computing Design Group and the New Mexico Consortium, recently gave a presentation at the Fifth Annual Storage Technology Showcase.

Storage Technology Showcase, STS, is the premier and only annual vendor neutral symposium for high volume digital and long term storage engineers and executives. STS addresses the current and future challenges of fast moving storage technologies. Specially curated attendance and vendors consists of thought leadership from around the globe, with installations of 100s of Petabytes of local cloud or on premise storage. Subjects discussed range from best practices, use cases, current challenges, site surveys and technology road maps.

Qing’s talk was titled, “Leveraging Computational Storage for Simulation Science Storage System Design”.

High-performance computing data centers supporting large-scale simulation applications can routinely generate a large amount of data. To promptly unlock the scientific insight buried within it, this data must be efficiently absorbed, processed, and indexed with minimal processing delays. Currently, despite a transition from HDDs to using all-flash based storage systems in hot storage tiers for a boost in raw storage bandwidth as many recently deployed systems have done, bottlenecks still exist due to legacy software, severe server CPU and memory bandwidth limitations for certain data-intensive operations such as compression, and excessive data movement.

Computational storage, with its ability to map and distribute storage functions to various computing units along the data processing pathway, provides opportunities to overcome existing storage system bottlenecks to vastly improve performance and cost.

Qing’s presentation delved into several computational storage initiatives undertaken at Los Alamos National Laboratory in partnership with industry leaders such as Aeon, Eideticom, NVIDIA, SK hynix, and Seagate. His presentation explored topics such as transparent ZFS I/O pipeline offloads, analytics acceleration with flash key-value based storage devices, and in-drive SQL like query processing in an erasure coded data lake tier.

Qing wrapped up his discussion with key takeaways and future directions stemming from these exploratory projects.

Qing Zheng is a Scientist at Los Alamos National Laboratory’s High-Performance Computing Design Group and with the New Mexico Consortium. Qing performs I/O and storage research that guides the Lab’s future computing platform and storage infrastructure designs. He received his PhD in Computer Science from Carnegie Mellon University in 2021. Qing’s work has been exhibited at local science museums, reported by national media, and recognized with multiple R&D 100 and Supercomputing Best Paper Awards.

To learn more about this conference see: https://storagetechshow.com/