TY - JOUR T1 - Türk Ulusal Bilim e-Altyapısı TRUBA’da Moleküler Dinamik Paketi GROMACS’in Performans Optimizasyonu AU - Karaca, Ezgi AU - Savaş, Büşra PY - 2021 DA - December DO - 10.7240/jeps.920227 JF - International Journal of Advances in Engineering and Pure Sciences JO - JEPS PB - Marmara University WT - DergiPark SN - 2636-8277 SP - 609 EP - 613 VL - 33 IS - 4 LA - tr AB - Yüksek performanslı hesaplama sistemlerinin kullanımının artmasıyla, bu sistemlerde çalıştırılan programların performans optimizasyonu öncelikli hale gelmiştir. Bu duruma istinaden, bu çalışmamızda, yaygın olarak kullanılan moleküler dinamik paketi GROMACS’in, TÜBİTAK ULAKBİM tarafından kullanıma sunulan TRUBA hesaplama kümelerindeki en iyi performans kriterlerini bulmayı hedefledik. Performans tarama çalışmamız sırasında, farklı hesaplama kümelerinde, farklı CPU/GPU çekirdek oranı ve GROMACS versiyonlarını denedik. Bu süreç sonunda en iyi performanslı hesaplama kümesi akya-cuda, en iyi CPU/GPU çekirdek sayı oranı 40/1 ve en hızlı GROMACS versiyonu GROMACS 2020 olarak tespit edilmiştir. Benzer bir çalışma yürütecek araştırmacıların yararlanması adına, performans optimizasyon dosyalarımız ve ayrıntılı sonuçlarımız https://github.com/CSB-KaracaLab/gmx_performance_on_HPC adresinde incelemeye açılmıştır. KW - Moleküler Dinamik KW - Yüksek Başarımlı Hesaplama Kümeleri KW - Optimizasyon KW - GROMACS CR - [1] Alder, B. J., & Wainwright, T. E. (1959). Studies in molecular dynamics. I. General method. The Journal of Chemical Physics, 31(2). https://doi.org/10.1063/1.1730376 CR - [2] Rahman, A. (1964). Correlations in the motion of atoms in liquid argon. Physical Review, 136(2A). https://doi.org/10.1103/PhysRev.136.A405 CR - [3] Páll, S., Abraham, M. J., Kutzner, C., Hess, B., & Lindahl, E. (2015). Tackling exascale software challenges in molecular dynamics simulations with GROMACS. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8759. https://doi.org/10.1007/978-3-319-15976-8_1 CR - [4] Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindah, E. (2015). Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1–2. https://doi.org/10.1016/j.softx.2015.06.001 CR - [5] Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., & Schulten, K. (2005). Scalable molecular dynamics with NAMD. In Journal of Computational Chemistry (Vol. 26, Issue 16). https://doi.org/10.1002/jcc.20289 CR - [6] Pearlman, D. A., Case, D. A., Caldwell, J. W., Ross, W. S., Cheatham, T. E., DeBolt, S., Ferguson, D., Seibel, G., & Kollman, P. (1995). AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Computer Physics Communications, 91(1–3). https://doi.org/10.1016/0010-4655(95)00041-D CR - [7] Bird, A. (2007). Perceptions of epigenetics. In Nature (Vol. 447, Issue 7143). https://doi.org/10.1038/nature05913 CR - [8] Mazzio, E. A., & Soliman, K. F. A. (2012). Basic concepts of epigenetics impact of environmental signals on gene expression. In Epigenetics (Vol. 7, Issue 2). https://doi.org/10.4161/epi.7.2.18764 CR - [9] Khavari, D. A., Sen, G. L., & Rinn, J. L. (2010). DNA methylation and epigenetic control of cellular differentiation. In Cell Cycle (Vol. 9, Issue 19). https://doi.org/10.4161/cc.9.19.13385 CR - [10] Lee, J. H., Hart, S. R. L., & Skalnik, D. G. (2004). Histone Deacetylase Activity Is Required for Embryonic Stem Cell Differentiation. Genesis, 38(1). https://doi.org/10.1002/gene.10250 CR - [11] Weinhold, B. (2006). Epigenetics: the science of change. Environmental Health Perspectives, 114(3). https://doi.org/10.1289/ehp.114-a160 CR - [12] Kulis, M., & Esteller, M. (2010). DNA Methylation and Cancer. In Advances in Genetics (Vol. 70, Issue C). https://doi.org/10.1016/B978-0-12-380866-0.60002-2 CR - [13] Law, J. A., & Jacobsen, S. E. (2010). Establishing, maintaining and modifying DNA methylation patterns in plants and animals. In Nature Reviews Genetics (Vol. 11, Issue 3). https://doi.org/10.1038/nrg2719 CR - [14] Chédin, F. (2011). The DNMT3 family of mammalian de novo DNA methyltransferases. In Progress in Molecular Biology and Translational Science (Vol. 101). https://doi.org/10.1016/B978-0-12-387685-0.00007-X CR - [15] Zhang, Z. M., Lu, R., Wang, P., Yu, Y., Chen, D., Gao, L., Liu, S., Ji, D., Rothbart, S. B., Wang, Y., Wang, G. G., & Song, J. (2018). Structural basis for DNMT3A-mediated de novo DNA methylation. Nature, 554(7692). https://doi.org/10.1038/nature25477 CR - [16] Norvil, A. B., Petell, C. J., Alabdi, L., Wu, L., Rossie, S., & Gowher, H. (2018). Dnmt3b Methylates DNA by a Noncooperative Mechanism, and Its Activity Is Unaffected by Manipulations at the Predicted Dimer Interface. Biochemistry, 57(29). https://doi.org/10.1021/acs.biochem.6b00964 CR - [17] TRUBA. https://www.truba.gov.tr/index.php/en/main-page/ CR - [18] TRUBA Wiki Sayfası. http://wiki.truba.gov.tr/index.php/Ana_sayfa CR - [19] Ivani, I., Dans, P. D., Noy, A., Pérez, A., Faustino, I., Hospital, A., Walther, J., Andrio, P., Goñi, R., Balaceanu, A., Portella, G., Battistini, F., Gelpí, J. L., González, C., Vendruscolo, M., Laughton, C. A., Harris, S. A., Case, D. A., & Orozco, M. (2015). Parmbsc1: A refined force field for DNA simulations. Nature Methods, 13(1). https://doi.org/10.1038/nmeth.3658 UR - https://doi.org/10.7240/jeps.920227 L1 - https://dergipark.org.tr/en/download/article-file/1716291 ER -