Low Latency Hardware Accelerators for File Systems

Low Latency Hardware Accelerators for File Systems

Low Latency Hardware Accelerators for File Systems Zacodi Labs OpenZFS Summit 2014 Motivation ● Compute intensive tasks ● Cryptographic hash SHA256 ● Data compression ● Encryption ● Used in many applications: storage, networking, etc. ● Existing hardware acceleration solutions ● High overheads and latency ● A lot of parallelism/concurrency required to achieve throughput ● Not usable for latency sensitive applications Compute Intensive Tasks ZFS example: SHA256 ● Cryptographically strong hash function ● Provides checksum for data integrity ● Aids redundancy detection and deduplication ● Uses almost all CPU time: ○ 6-core Sandy Bridge ○ 0.6-0.7 GB/s Hardware Acceleration Approach Offload compute intensive tasks to FPGA PCIe CPU FPGA DRAM Hardware/Software Interface ● Low overhead/Low latency ○ minimum number of PCIe round trips ○ overlap DMA and SHA256 computation ● Zero copy ○ no additional buffers/copies ○ no buffer management, allocation, de-allocation, etc. ● No DMA descriptors in memory ○ no descriptor management, synchronization, etc. ● Interface optimized for multi-core CPU architecture Integration with ZFS ● Open source ZFS (Linux, Illumos) ● PCIe driver for FPGA - both Illumos and Linux are supported ● Driver modifies SHA256 function pointer in ZFS ● SHA256 function is a callback into driver ● No ZFS source code changes required ZFS performance comparison CPU only CPU + Arria V FPGA Latency comparison ● SHA256 computation latency of 4KB and 64KB blocks of data ● Comparing CPU and accelerator 4KB 64KB Sandy Bridge Xeon CPU 40.5 usec 650 usec Arria V FPGA 38.5 usec 500 usec Stratix V FPGA 21.5 usec 250 usec Latency vs. Throughput Further extensions ● Compression ● Sliding window hashes ○ Rabin fingerprints, used for advanced deduplication ● Encryption ● Combinations of the above ○ e.g. parallel checksumming and compression Conclusions ● High throughput hardware accelerator ● Low overhead, low latency ● Simple integration with ZFS ○ no changes in file system necessary ● Demonstrated 3x throughput improvement ● Interested? Write us at [email protected].

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