@inproceedings{kim2014a,
author = {Kim, Joo-Young and Hauck, Scott and Burger, Doug},
title = {A Scalable Multi-engine Xpress9 Compressor with Asynchronous Data Transfer},
booktitle = {IEEE 22nd International Symposium on Field-Programmable Custom Computing Machines},
year = {2014},
month = {May},
abstract = {Data compression is crucial in large-scale storage servers to save both storage and network bandwidth, but it suffers from high computational cost. In this work, we present a high throughput FPGA based compressor as a PCIe accelerator to achieve CPU resource saving and high power efficiency. The proposed compressor is differentiated from previous hardware compressors by the following features:

Targeting Xpress9 algorithm, whose compression quality is comparable to the best Gzip implementation (level 9);
A scalable multi-engine architecture with various IP blocks to handle algorithmic complexity as well as to achieve high throughput;
Supporting a heavily multi-threaded server environment with an asynchronous data transfer interface between the host and the accelerator.

The implemented Xpress9 compressor on Altera Stratix V GS performs 1.6-2.4Gbps throughput with 7 engines on various compression benchmarks, supporting up to 128 thread contexts.},
url = {http://approjects.co.za/?big=en-us/research/publication/a-scalable-multi-engine-xpress9-compressor-with-asynchronous-data-transfer/},
}