Abstract
Pattern matching algorithms are used in several areas such as network security, bioinformatics and text mining. In order to provide real-time response for large inputs, high-performance systems should be used. However, this requires adapting the algorithm to the underlying architecture. Intel Xeon Phi processors have attracted attention in recent years because they offer massive parallelism, good programmability and portability. In this paper, we present a pattern matching algorithm that exploits the full computational power of Intel Xeon Phi processors by using both SIMD and thread parallelism. We evaluate our algorithm on a Xeon Phi 7230 Knights Landing processor and measure its performance as the data size and the number of threads increase. The results reveal that both parallelism methods provide performance gains. Also they indicate that our algorithm is up to 63x faster than its serial counterpart and behaves well as the workload is increased.
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Notes
- 1.
The Speedup of B over A is defined as \(\frac{T_{A}}{T_{B}}\), where \(T_{A}\) is the execution time of Algorithm A and \(T_{B}\) is the execution time of Algorithm B.
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Sanz, V., Pousa, A., Naiouf, M., De Giusti, A. (2020). Accelerating Pattern Matching on Intel Xeon Phi Processors. In: Qiu, M. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Lecture Notes in Computer Science(), vol 12452. Springer, Cham. https://doi.org/10.1007/978-3-030-60245-1_18
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