Subject: Subject Sylbus: Concurrent and Distribute Programming for Data Procesing and Machine Learning - 2363

Concurrent and Distribute Programming for Data Procesing and Machine Learning - 236370
Credit
Points
3.0
Given In
Semester
a
Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
2 1 1 4
Possibility to guided reading

Determination of the grade according to progress during the semester and a final examination.


Prerequisites Structure of Operating Systems 046209
or Operating Systems 234123


Overview of Parallel Programming Languages, Synchronizations and Communications Mechanisms Between Processes, Memory Models, Debugging Methods, Vector Clocks, Parallel Hardware and Vector Accelerators. the Course Includes Programming Assignments. the Course Places Special Emphasis on the Use of All These Tools for Data Processing of Parallel and Distributed Information, and for the Purposes of Machine Use Cases of Parallel and Distributed Computing Today.
By the End of the Course the Student Will Be Able to:
1. Understand How to Utilize Parallel and Distributed Resources, and Especially for Measure the Effectiveness of Such Utilization.
2. Know the Various Possibilities in Processing of Parallel and Distributed Technologies, and the Modern Trends in the Field.




Times and places of examinations 01/2022 2202/2023 Winter Semester
examination timedaydateSeason
Sunday12.02.2023
Sunday05.03.2023

Timetable to semester 01/2022 2202/2023 Winter Semester
RoomBuildingHourdayLecturerExercise
Lecture
no.Registering
Group
711:30-13:30SundayProf. Schuster AssafLecture1011
Project11
310:30-11:30SundayExercise11
711:30-13:30SundayProf. Schuster AssafLecture1012
Project12
613:30-14:30TuesdayExercise12

Created in 29/09/2022 Time 01:17:41