HPC (HIGH PERFORMANCE COMPUTING) YONDASHUVLARIDA GETEROGEN MA’LUMOTLAR BILAN ISHLASH STRATEGIYALARI
Keywords:
Yuqori samarali hisoblash, geterogen ma’lumotlar, parallellik, ma’lumotlarni qayta ishlash, optimallashtirish, algoritmlar, HPC arxitekturasi.Abstract
shbu maqola yuqori samarali hisoblash (HPC) tizimlarida
geterogen ma’lumotlar bilan ishlash strategiyalariga bag‘ishlangan. Maqolada turli xil
ma’lumot turlari va formatlarini samarali boshqarish, ularga moslashuvchan
algoritmlar va arxitekturalar, shuningdek, parallellik va resurslarni optimallashtirish
usullari ko‘rib chiqiladi. Geterogen ma’lumotlarning o‘sib borayotgan hajmi va
murakkabligi hisobga olinib, maqola HPC tizimlarida ma’lumotlarni qayta ishlash
samaradorligini oshirishga qaratilgan zamonaviy yondashuvlarni tahlil qiladi.
References
1.
Amaral, M., Jääskeläinen, P., & Marttinen, P. (2021). Heterogeneous computing
with OpenMP and Hydra: Improving performance on HPC systems. Journal of Parallel
and Distributed Computing, 147, 123-135. https://doi.org/10.1016/j.jpdc.2020.09.0052.
Asanovic, K., Bodik, R., & Catanzaro, B. (2020). The landscape of parallel
computing research: A view from Berkeley. University of California, Berkeley,
Technical Report No. UCB/EECS-2020-183.
3.
Dongarra, J., Foster, I., & Fox, G. (2019). High Performance Computing:
Modern Systems and Practices. Morgan Kaufmann Publishers.
4.
Gropp, W., Lusk, E., & Skjellum, A. (2022). Using MPI: Portable Parallel
Programming with the Message Passing Interface (4th ed.). MIT Press.
5.
Kirk, D. B., & Hwu, W. W. (2021). Programming Massively Parallel
Processors: A Hands-on Approach (4th ed.). Morgan Kaufmann.
6.
Liu, Y., Zhang, J., & Wang, X. (2023). Dynamic load balancing for
heterogeneous data processing in HPC clusters. IEEE Transactions on Parallel and
Distributed Systems, 34(3), 789-801. https://doi.org/10.1109/TPDS.2022.3214567
7.
Mittal, S., & Vetter, J. S. (2020). A survey of CPU-GPU heterogeneous
computing
techniques.
ACM
https://doi.org/10.1145/3397372
8.
Computing
Surveys,
53(3),
1-35.
NVIDIA Corporation. (2023). CUDA Toolkit Documentation. Retrieved from
