Memory-side acceleration for XML parsing
NPC'11 Proceedings of the 8th IFIP international conference on Network and parallel computing
Benefits of using parallelized non-progressive network coding
Journal of Network and Computer Applications
Exploiting SIMD parallelism on dynamically partitioned parallel network coding for P2P systems
Computers and Electrical Engineering
Design and evaluation of random linear network coding Accelerators on FPGAs
ACM Transactions on Embedded Computing Systems (TECS)
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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.