Name
Abstract | ||
|---|---|---|
The rapid development of nonvolatile memory technologies such as flash, PCM, and Memristor has made processing in storage (PIS) a viable approach. We present an FPGA module augmented to an SSD storage controller that provides wire-speed object deserialization, referred to as HODS for hardware object deserialization in SSD. A pipelined circuit structure was designed to tailor to high-speed data conversion specifically. HODS is capable of conducting deserialization while data is being transferred on I/O bus from the storage device to host. The FPGA module has been integrated with our newly designed NVM-e SSD. The working prototype demonstrated significant performance benefits. The FPGA module can process data in line speed at 100MHz on 16 Byte data stream. For integer benchmarks, HODS showed deserialization speedup of 8~12× as compared to the traditional deserialization on a high-end host CPU. The speedup can reach 17~21× for floating-point datasets. The measured object deserialization throughput is 1GB/s on average at a clock speed of 100MHz. The overall performance improvements at the application level range from 10% to a factor of 4.3× depending on the proportion of deserialization time over total application running time. Compared to traditional SSD on the same server, HODS showed visible differences regarding application execution time while running Matlab, 3D modeling, and scientific computations. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/FCCM.2018.00033 | 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM) |
Keywords | Field | DocType |
Processing In Storage (PIS),Object Deserialization,NVM-e SSD | Byte,Serialization,Data stream,Computer science,Field-programmable gate array,Data conversion,Computer hardware,Clock rate,Benchmark (computing),Speedup | Conference |
ISBN | Citations | PageRank |
978-1-5386-5523-8 | 0 | 0.34 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongyang Li | 1 | 1 | 1.38 |
| Fei Wu | 2 | 104 | 35.76 |
| qingan | 3 | 122 | 12.38 |
| Qing Yang | 4 | 49 | 2.90 |
| Changsheng Xie | 5 | 366 | 66.54 |