File System Acceleration using Computational Storage for Efficient Data Storage
Abstract
We examine the benefits of using computational storage devices like Xilinx SmartSSD to offload the compression to achieve an ideal compression scheme where higher compression ratios are achieved with lower CPU resources. This offloading of compute intensive task of compression frees up the CPU to cater to real customer applications. The scheme proposed in this paper comprises of Xilinx Storage Services (XSS) with Xilinx Runtime (XRT) software and HLS based GZIP compression kernel that runs on the FPGA. The hardware platform chosen is Xilinx SmartSSD which also has a unique feature of P2P data transfer where the data input/output to/from the FPGA is directly moved from/to the storage device without moving it back to the host system (x86) memory. This further helps in improving the overall system efficiency by reducing the DDR memory traffic by moving computation closer to where data resides. There are different places in the application/OS software stack where data compression can be offloaded to hardware. We have chosen to do this at the file system level because this will enable all the applications using the filesystem to benefit without necessarily making any changes to the application itself. We have selected the Linux ZFS filesystem as this is the most widely used and popular file system today.
Learning Objectives
- We examine the benefits of using computational storage devices like Xilinx SmartSSD to offload the compression to achieve an ideal compression
- Peer to Peer data flow and it's advantages
- Advantages of offloading at File System
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