Hardware Accelerated ZFS using Computational Storage

Time: Thu Sep 15 | 8:15am - 9:05am


As hardware layers in storage systems (such as network and storage devices) continue to increase in performance, it is vital that the IO software stack does not fall behind and become the bottleneck. Leveraging the capabilities of computational storage devices, such data processing units (DPUs), allows for the IO software stack to accelerate CPU and memory bandwidth constrained operations in order to fully take advantage of the storage hardware in the system. DPUs offer the ability to make storage systems more efficient but has proven difficult to integrate them into IO software stacks to produce production-quality accelerated storage systems. Los Alamos National Laboratory (LANL) has worked on streamlining the process of integrating DPUs in order to improve file system performance and reduce the storage footprint on storage devices. The Data Processing Unit Services Module (DPU-SVC) was created in order to provide a standardized interface for DPUs to interface with, as well as a standardized interface for DPU consumers to use. The initial DPU consumer targeted was the open-source Zettabyte File System (ZFS). ZFS is a commonly used backend for LANL’s parallel filesystems due to the rich feature set available for data transformations (compression, deduplication) and data integrity functions (checksums, erasure coding). The ZFS Interface for Accelerators (Z.I.A.), which uses the consumer facing standard interface of the DPU-SVC, was added into ZFS to allow for data to be moved out of ZFS and into DPUs. These changes allow for transparent acceleration of ZFS operations: users do not have to modify their applications in order to enjoy the benefits provided by DPUs in the storage system. Using DPUs in coordination with the ZFS code base can increase overall write throughput to LANL storage systems by a factor of 10 to 30 times current storage system performance. This increase in performance is achieved through moving ZFS operations that were originally implemented in software such as compression, checksumming, and erasure coding to hardware accelerated implementations, which in turn frees up CPU and memory bandwidth for user applications. This talk will present technical details of how the DPU-SVC and Z.I.A. accelerate the ZFS IO stack through attached DPUs. Results will also be presented showing write performance improvements from using these layers with LANL scientific data sets and storage systems. Some background knowledge of computational storage, ZFS, and kernel modules would be beneficial to the audience.

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