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On Improving Parallelized Network Coding with Dynamic Partitioning

机译:动态分区改进并行网络编码的研究

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In this paper, we investigate parallel implementation techniques for network coding. It is known that network coding is useful for both wired and wireless networks and it also mitigates peer/piece selection problems in P2P file sharing systems. However, due to the decoding complexity of network coding, there have been concerns about adoption of network coding in practical network systems and to improve the decoding performance, the exploitation of parallelism has been proposed previously. In this paper, we argue that naive parallelization strategies of network coding may result in unbalanced workload distribution, and thus, limiting performance improvements. We further argue that a higher performance enhancement can be achieved through balanced partitioning methods in parallelized network coding and propose new parallelization techniques for network coding. Our experiments show that on a quad-core processor system, proposed algorithms exhibit up to 5.69 speedup which is better than the linear speedup with the influence of additional cache. Moreover, on an octal-core system, our algorithms even achieve speedup of 8.46 compared to a sequential network coding and 43.3 percent faster than an existing parallelized technique using 1 Mbytes data with 1,024 times 1,024 coefficient matrix size.
机译:在本文中,我们研究了网络编码的并行实现技术。众所周知,网络编码对于有线和无线网络都是有用的,并且还减轻了P2P文件共享系统中的对等/片段选择问题。但是,由于网络编码的解码复杂性,在实际的网络系统中采用网络编码成为关注点,为了提高解码性能,以往提出了并行性的开发方法。在本文中,我们认为网络编码的幼稚并行化策略可能会导致工作负载分配不平衡,从而限制性能的提高。我们进一步认为,可以通过并行化网络编码中的平衡分区方法来实现更高的性能增强,并提出用于网络编码的新并行化技术。我们的实验表明,在四核处理器系统上,所提出的算法显示出高达5.69的加速比在附加缓存影响下的线性加速更好。此外,在八核系统上,与顺序网络编码相比,我们的算法甚至可以实现8.46的加速,比使用1 Mbytes数据和1024乘以1024系数矩阵大小的现有并行化技术要快43.3%。

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