Flexcore: Massively parallel and flexible processing for large MIMO access points

TY - GEN

T1 - Flexcore

T2 - 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017

AU - Husmann, Christopher

AU - Georgis, Georgios

AU - Nikitopoulos, Konstantinos

AU - Jamieson, Kyle

N1 - Funding Information: This material is based upon work supported by the UK’s Engineering and Physical Sciences Research Council (EPSRC Ref. EP/M029441/1), by the National Science Foundation under Grant No. 1617161 and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement No. 279976. The Authors would like to thank the members of University of Surrey 5GIC (http://www.surrey.ac.uk/5GIC) for their support. Finally, we thank our shepherd Lin Zhong and the anonymous reviewers for their insightful feedback. Funding Information: This material is based upon work supported by the UK?s Engineering and Physical Sciences Research Council (EPSRC Ref. EP/M029441/1), by the National Science Foundation under Grant No. 1617161 and the European Research Council under the European Union?s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement No. 279976. The Authors would like to thank the members of University of Surrey 5GIC (http://www.Surrey.ac.uk/5GIC) for their support. Finally, we thank our shepherd Lin Zhong and the anonymous reviewers for their insightful feedback.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Large MIMO base stations remain among wireless network designers’ best tools for increasing wireless throughput while serving many clients, but current system designs, sacrifice throughput with simple linear MIMO detection algorithms. Higher-performance detection techniques are known, but remain off the table because these systems parallelize their computation at the level of a whole OFDM subcarrier, sufficing only for the less-demanding linear detection approaches they opt for. This paper presents FlexCore, the first computational architecture capable of parallelizing the detection of large numbers of mutually-interfering information streams at a granularity below individual OFDM subcarriers, in a nearly-embarrassingly parallel manner while utilizing any number of available processing elements. For 12 clients sending 64-QAM symbols to a 12-antenna base station, our WARP testbed evaluation shows similar network throughput to the state-of-the-art while using an order of magnitude fewer processing elements. For the same scenario, our combined WARP-GPU testbed evaluation demonstrates a 19× computational speedup, with 97% increased energy efficiency when compared with the state of the art. Finally, for the same scenario, an FPGA-based comparison between FlexCore and the state of the art shows that FlexCore can achieve up to 96% better energy efficiency, and can offer up to 32× the processing throughput.

AB - Large MIMO base stations remain among wireless network designers’ best tools for increasing wireless throughput while serving many clients, but current system designs, sacrifice throughput with simple linear MIMO detection algorithms. Higher-performance detection techniques are known, but remain off the table because these systems parallelize their computation at the level of a whole OFDM subcarrier, sufficing only for the less-demanding linear detection approaches they opt for. This paper presents FlexCore, the first computational architecture capable of parallelizing the detection of large numbers of mutually-interfering information streams at a granularity below individual OFDM subcarriers, in a nearly-embarrassingly parallel manner while utilizing any number of available processing elements. For 12 clients sending 64-QAM symbols to a 12-antenna base station, our WARP testbed evaluation shows similar network throughput to the state-of-the-art while using an order of magnitude fewer processing elements. For the same scenario, our combined WARP-GPU testbed evaluation demonstrates a 19× computational speedup, with 97% increased energy efficiency when compared with the state of the art. Finally, for the same scenario, an FPGA-based comparison between FlexCore and the state of the art shows that FlexCore can achieve up to 96% better energy efficiency, and can offer up to 32× the processing throughput.

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M3 - Conference contribution

T3 - Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017

SP - 197

EP - 211

BT - Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017

PB - USENIX Association

Y2 - 27 March 2017 through 29 March 2017

ER -