下一代移动设备协议栈处理的实时硬件加速

David Szczesny, S. Hessel, Felix Bruns, A. Bilgic
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引用次数: 11

摘要

在本文中,我们提出了一种新的实时硬件加速方法,基于智能直接存储器访问(sDMA)控制器,用于长期演进(LTE)和超越移动设备的第2层(L2)下行链路协议堆栈处理。我们使用虚拟原型来模拟基于ARM1176处理器的硬件平台以及包含LTE协议栈模型的执行软件。针对协议栈中的时间关键型算法,采用不同硬件加速单元的sDMA控制器实现并集成在硬件平台上。通过测量sDMA控制器中不同激活的动态硬件加速阶段协议栈中每个传输块的平均执行时间,我们证明了我们针对LTE L2的新硬件/软件分区概念。在100mbit /s的LTE数据速率下,通过在协议栈中启用sDMA硬件支持报头处理,与纯软件实现相比,我们实现了24%的加速。此外,在sDMA控制器中激活完整的实时硬件加速,包括实时解码,导致加速超过50%。最后,在具有更多计算需求和高达320 Mbit/s的数据速率的传输条件下,我们获得了几乎80%的加速比。调查表明,我们新的sDMA实时硬件加速方法与单核处理器相结合,可以为下一代移动设备提供所需的计算能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-the-fly hardware acceleration for protocol stack processing in next generation mobile devices
In this paper we present a new on-the-fly hardware acceleration approach, based on a smart Direct Memory Access (sDMA) controller, for the layer 2 (L2) downlink protocol stack processing in Long Term Evolution (LTE) and beyond mobile devices. We use virtual prototyping in order to simulate an ARM1176 processor based hardware platform together with the executed software comprising an LTE protocol stack model. The sDMA controller with diff erent hardware accelerator units for the time critical algorithms in the protocol stack is implemented and integrated in the hardware platform. We prove our new hardware/software partitioning concept for the LTE L2 by measuring the average execution time per transport block in the protocol stack at di fferent activated on-the-fly hardware acceleration stages in the sDMA controller. At LTE data rates of 100 Mbit/s, we achieve a speedup of 24% compared to a pure software implementation by enabling the sDMA hardware support for header processing in the protocol stack. Furthermore, an activation of the complete on-the-fly hardware acceleration in the sDMA controller, including on-the-fly deciphering, leads to a speedup of more than 50 %. Finally, at transmission conditions with more computational demands and data rates up to 320 Mbit/s, we obtain acceleration ratios of almost 80 %. Investigations show that our new sDMA on-the-fly hardware acceleration approach in combination with a single-core processor off ers the required computational power for next generation mobile devices.
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