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Enabling Fast and Energy-Efficient FM-index Exact Matching using Processing-Near-Memory Herruzo-Ruiz, José Manuel Fernández, Iván González-Navarro, Sonia Óscar, Plata Informática - Aplicaciones Memory bandwidth and latency constitutes a major performance bottleneck for many data-intensive applications. While high-locality access patterns take advantage of the deep cache hierarchies available in modern processors, unpredictable low-locality patterns cause a significant part of the execution time to be wasted waiting for data. An example of those memory bound applications is the exact matching algorithm based on FM-index, used in some well-known sequence alignment applications. Processing-Near-Memory (PNM) has been proposed as a strategy to overcome the memory wall problem, by placing computation close to data, speeding up memory bound workloads by reducing data movements. This paper presents a performance and energy evaluation of two classes of processor architectures when executing the FM-index exact matching algorithm, as a reference algorithm for exact sequence alignment. One architecture class is processor-centric, based on complex cores and DDR3/4 SDRAM memory technology. The other architecture class is memory-centric, based on simple cores and ultra high-bandwidth Hybrid Memory Cube (HMC) 3D-stacked memory technology. The results show that the PNM solution improves performance between 1.26× and 3.7× and the energy consumption per operation is reduced between 21× and 40×. In addition, a synthetic benchmark RANDOM was developed that mimics the memory access pattern of the FM-index exact matching algorithm, but with a user configurable operational intensity. This benchmark allows us to extend the evaluation to the class of algorithms with similar memory behaviour but running over a range of operational intensity values. 2024-02-02T07:23:06Z 2024-02-02T07:23:06Z 2024-02-02T07:23:06Z 2021-09 journal article Herruzo, J.M., Fernandez, I., González-Navarro , S. et al. Enabling fast and energy-efficient FM-index exact matching using processing-near-memory. J Supercomput 77, 10226–10251 (2021). https://doi.org/10.1007/s11227-021-03661-3 https://hdl.handle.net/10630/29657 10.1007/s11227-021-03661-3 eng open access Springer