Parallelized Progressive Network Coding With Hardware Acceleration

The fundamental insight of network coding is that information to be transmitted from the source in a session can be inferred, or decoded, by the intended receivers, and does not have to be transmitted verbatim. It is a well known result that network coding may achieve better network throughput in certain multicast topologies; however, the practicality of network coding has been questioned, due to its high computational complexity. This paper represents the first attempt towards a high performance implementation of network coding. We first propose to implement progressive decoding with Gauss-Jordan elimination, such that blocks can be decoded as they are received. We then employ hardware acceleration with SSE2 and AltiVec SIMD vector instructions on x86 and PowerPC processors, respectively. We then use a careful threading design to take advantage of symmetric multiprocessor (SMP) systems and multi-core processors. The objective of this work is to explore the computational limits of network coding in off-the-shelf modern processors, and to provide a solid reference implementation to facilitate commercial deployment of network coding. Our high-performance implementation is packaged as a C++ class library, and runs in Linux, Mac OS X and Windows, in Intel, AMD and IBM PowerPC processor families. On a Dual dual-core PowerPC G5 2.5 GHz server, the coding bandwidth of our implementation is able to reach 43 MB/second with 64 blocks of 32 KB each, achieving speedup of 21 over the baseline implementation.