Comparative assessment of GPGPU technologies to accelerate objective functions: A case study on parsimony

Author:

Santander-Jiménez Sergio,Vega-Rodríguez Miguel A.,Vicente-Viola Jorge,Sousa LeonelORCID

Funder

AEI

ERDF (European Regional Development Fund, EU)

FCT (Fundação para a Ciência e a Tecnologia, Portugal)

FCT, Portugal

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference56 articles.

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3. A. Andersch, J. Lucas, M. Álvarez-Mesa, B. Juurlink, Analyzing GPGPU pipeline latency, in: ACACES 2014, 2014, pp. 57–60.

4. BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics;Ayres;Syst. Biol.,2012

5. Computational grand challenges in assembling the tree of life: problems and solutions;Bader,2006

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1. A Survey of Processing Systems for Phylogenetics and Population Genetics;ACM Transactions on Reconfigurable Technology and Systems;2023-06-20

2. Combined kernel for fast GPU computation of Zernike moments;Journal of Real-Time Image Processing;2020-05-01

3. GPU acceleration of Fitch’s parsimony on protein data: from Kepler to Turing;The Journal of Supercomputing;2020-03-04

4. Parallel Fast Pencil Drawing Generation Algorithm Based on GPU;IEEE Access;2019

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