KLASTERLI MUHITDA DASTURLASH TILLARINI O'QITISH METODIKASI
Keywords:
Kalit soʻzlar: Klasterli muhit, Parallel dasturlash, MPI (Message Passing Interface), OpenMP, Dasturlash tillarini o‘qitish metodikasi, Yuqori unumli hisoblash (HPC), Distributiv algoritmlarAbstract
Annotatsiya
Klasterli muhitda dasturlash tillarini o‘qitish – zamonaviy yuqori unumli
hisoblash (HPC) va katta maʼlumotlar tahlili sohalariga mutaxassislar tayyorlashning
asosiy omilidir. Ushbu maqolada klaster arxitekturasi (bosh tugun, hisoblash tugunlari,
SLURM, MPI) asosida dasturlashni o‘qitishning metodik jihatlari tahlil qilinadi.
Parallel dasturlash tillari (MPI, OpenMP, Python kutubxonalari) va ularni
o‘zlashtirishda qo‘llaniladigan bosqichma-bosqich yondashuv korsatilgan: klaster
tuzilishini tushunishdan tortib, algoritmlarni parallelashtirishgacha. Maqolada amaliy
misollar orqali:
1. MPI yordamida massiv yig‘indisini hisoblash (C),
2. OpenMP bilan matritsalarni ko‘paytirish (C),
3. mpi4py va Monte-Karlo usuli orqali π hisoblash (Python)
kabi real vazifalar batafsil yoritiladi. Taʼlim jarayonini tashkil etishda laboratoriya
mashgʻulotlari, modulli loyihalar, virtual muhitlarning ahamiyati vurg‘ulanadi.
Qiyinchiliklar (debugging, resurslar boshqaruvi) va ularning yechimlari keltirilgan,
shuningdek, klasterli muhit boshqa platformalar (oddiy PC, bulut xizmatlar)
bilan taqqoslanadi. Xulosada, ushbu metodikaning HPC mutaxassislarini
tayyorlashdagi strategik roli taʼkidlangan.
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