##plugins.themes.academic_pro.article.main##

Abstract

The main function of graphics processors since their inception has been graphics processing. Subsequently, after it became possible to program the processing of model vertices and pixels of rendered three-dimensional scenes using special programs, the architecture of graphic processors changed significantly. After the advent of the first general-purpose programmable graphics processors, it became possible to process commands not only for graphic data in vector form, but also to perform ordinary calculations for arbitrary data on a variety of special cores, while implementing data parallelism. Therefore, Graphics Processing Units show high efficiency rates when parallelizing programs that process a lot of data of the same type. Such programs include shaders: a vertex shader processes 3D vertices with different parameters, a pixel shader processes 2D pixels on the screen using interpolated data. Even before the advent of general-purpose kernels, there were attempts to simulate the processing of arbitrary data of the same type written into textures using pixel shaders, which, of course, gave a performance boost compared to the CPU. To develop an abstract model of the GPU, consider the general structure of modern GPUs, as well as models designed for their programming

Keywords

Graphics Processing Units pixels architecture of graphic processors processor

##plugins.themes.academic_pro.article.details##

How to Cite
Rakhimov Bakhtiyar Saidovich, Saidov Atabek Bakhtiyarovich, Babajanov Boburbek Farkhodovich, Karimov Doston Alisher Ugli, & Musaeva Mukhtasar Zayirjon Qizi. (2022). Analysis And Using of the Features Graphics Processors for Medical Problems. Texas Journal of Medical Science, 7, 105–110. https://doi.org/10.62480/tjms.2022.vol7.pp105-110

References

  1. Brodtkorb A.R., Dyken C., Hagen T.R., Hjelmervik J.M., Storaasli O.O. State-of-the-art in heterogeneous computing / A.R. Brodtkorb, C. Dyken, T.R. Hagen, J.M. Hjelmervik, O.O. Storaasli // Scientific Programming, T. 18, 2010. - S. 1-33Forsyth DA, Pons, J. Computer vision. Modern approach / D.A. Forsyth, J. Pons: Trans. from English - M .: Publishing house "Williams", 2004. - 928 p .: ill. - Parallel. tit. English
  2. Frolov V. Solution of systems of linear algebraic equations by the preconditioning method on graphic processor devices
  3. P. P. Kudryashov Algorithms for detecting a human face for solving applied problems of image analysis and processing: author. dis. Cand. tech. Sciences: 05.13.01. - M, 2007.
  4. Rakhimov, B.S., Rakhimova, F.B., Sobirova, S.K. Modeling database management systems in medicine, Journal of Physics: Conference Seriesthis link is disabled, 2021, 1889(2), 022028
  5. Rakhimov, B.S., Mekhmanov, M.S., Bekchanov, B.G. Parallel algorithms for the creation of medical database, Journal of Physics: Conference Seriesthis link is disabled, 2021, 1889(2), 022090
  6. Tanenbaum E. Modern operating systems. 2nd ed. - SPb .: Peter, 2002 .-- 1040 p .: ill.
  7. Zaynidinov H., Mallayev O., Kuchkarov M. Parallel algorithm for modeling temperature fields using the splines method 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings, 2021, 9422645
  8. Zaynidinov H., Makhmudjanov S., Rajabov F., Singh D. IoT-Enabled Mobile Device for Electrogastrography Signal Processing Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021, 12616 LNCS, стр. 346–356
  9. Zaynidinov H.N., Yusupov I., Juraev J.U., Singh D. Digital Processing of Blood Image by Applying Two-Dimensional Haar Wavelets Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in bioinformatics), 2021, 12615 LNCS, стр. 83–94