COMP30023编程设计写作、辅导Java

” COMP30023编程设计写作、辅导JavaCOMP30023 Project 1Process* SchedulingOut date: March 15, 2021Due date: No later than 14:59 March 30, 2021 AEDTWeight: 15% of the final markBackgroundIn this project you will familiarise yourself with process scheduling in a multi-processor environment.You will write a simulator that allocates CPU (or processor) to the running processes.Many details on how scheduling works have been omitted to make the project fit the timeline. Pleasenote that you do not need multiple processes or threads (e.g., no need for fork or pthread) to implementthis project. We strongly advise you to start working on the project as soon as possible.The program will be invoked via the command line. It will be given a description of arriving processesincluding their arrival time, execution time in seconds, their id, and whether they are parallelisable ornot. You do not have to worry about how processes get created or executed in this simulation. The firstprocess always arrives at time 0, which is when the simulation begins.1 Single processor schedulerProcesses will be allocated CPU time According to shortest-time-remaining algorithm, a preemptivescheduling algorithm. When a new process arrives, it is scheduled if there is no other process running.If, when process j arrives, there is a process i running, then i is postponed and added to a queue if andonly if j has a shorter execution time than the remaining time of i. Process i is resumed where it leftoff, if it is the process with the shortest remaining time left among all other processes in the queue (i.e.,including those that may have arrived after j). Process ids are used to break ties, giving preference toprocesses with smaller ids. Since there is only one CPU, you can ignore the information on whether aprocess is parallelisable or not.The simulation should terminate once all processes have run to completion.2 Two processor schedulerIn this section you are asked to extend your scheduler to work with 2 processors: processors numbered 0and 1. This will simulate (1) a Situation where processes can run truly in parallel and (2) a process thatcan run faster with more computational resources (e.g., by creating child/sub processes).If the process that arrives is not parallelisable, it is assigned to the queue of the CPU with the smallestamount of remaining execution time for all processes and subprocesses (defined below) allocated to it,using CPU id to break ties, giving preference to CPU 0. After that the simulation for this processbehaves same as in Section 1. In this project, once a process is assigned to a CPU it cannot be movedto another CPU. (Think of why it may not be a good idea to migrate processes between CPUs.)If arriving process with id i and execution time x is parallelisable, two subprocesses are created, i.0and i.1, each with execution time dx/2e + 1. The extra time simulates the cost of synchronisation. Forexample, a parallelisable process that runs on a single CPU in 6 seconds, can finish within 4 seconds ifboth CPUs are idle when it arrives.1Once subprocesses are created, subprocess i.0 is added to the queue of CPU 0 and i.1 is added to CPU 1.After that they are treated as regular processes when scheduling them on each CPU. A parallelisableprocess is considered finished when both of its subprocesses have finished.3 N processor schedulerIn this task we generalise the 2 processor setting to N 3 processors. Similar to above, a nonparallelisableprocess is assigned to a CPU that has the shortest remaining time to complete all processesand subprocesses assigned to it so far.A parallelisable process is split into k N subproceses, where k is the largest value for which x/k 1.Each subprocess is then assigned execution time of dx/ke + 1. Subprocesses follow a similar namingconvention as above: a Process with id i is split into subprocesses with ids i.0, i.1, . . ., i.k0, wherek0 = k 1. Subprocesses are then assigned to k processors with shortest time left to complete suchthat subprocess i.0 is assigned to the CPU that can finish its processes the fastest, i.1 is assigned to thesecond fastest processor and so on. Use CPU ids to break ties, giving preference to smaller processornumbers.Example: consider a scenario with 4 CPUs, each with one process left to complete; processes on CPU0,1,2,3 have remaining time of 30,20,20,10, respectively. Then for a process i with execution time of 2,k is set to 2. Its subprocess i.0 and i.1 will be assigned to CPU 3 and 1 respectively.Once a process or subprocess is assigned to a CPU it cannot migrate to another CPU. A parallelisableprocess is considered finished when all of its subprocesses have finished.4 Challenge: Improve the performanceYou will be asked to measure the overall time of your simulation (Makespan). The challenge task is tocome up with an algorithm that has a shorter makespan on a set of tests (see details in Section 7). Forthis task the choice of k when splitting a parallelisable process is left to you. You are also allowed tolook into the future and see what processes will be arriving and use this information if you choose to.(Think of whether it is possible and how one would obtain such information in real life.) You will berequired to explain why your algorithm is more efficient in a short report.5 Program SpecificationYour program must be called allocate and take the following command line arguments. The argumentscan be passed in any order but you can assume that they will be passed exactly once.-f filename will specify the name of the file describing the processes.-p processors where processors is one of {1,2,N}, N 1024.-c an optional parameter, when provided, invokes your own scheduler from Section 4.The filename contains the processes to be executed and has the following format. Each line of the filecorresponds to a process. The first line refers to the first process that needs to be executed, and the lastline refers to the last process to be executed. Each line consists of a space-separated tuple (time-arrived,process-id, execution-time, parallelisable). You can assume that the file will be sorted by time-arrivedwhich is an integer in [0, 232) indicating seconds; all process-ids will be distinct integers in the domainof [0, 232) and the first process will always have time-arrived set to 0; execution-time will be an integerin [1, 232) indicating seconds; Parallelisable is either n or p. If it is p, then the corresponding process isparallelisable; if it is n, it is not. You can ignore n/p when -p is 1. More than one process can arrive atthe same time.Example: ./allocate -f processes.txt -p 1.The allocation program is required to simulate execution of processes in the file processes.txt on asingle CPU.Given processes.txt with the following information:0 4 30 n23 2 40 n5 1 20 n20 3 30 nThe program should simulate execution of 4 processes where process 4 arrives at time 0, needs 30 secondsrunning time to finish; process 2 arrives at time 3 and needs 40 seconds of time to complete.Each line (including the last) will be terminated with a LF (ASCII 0x0a) control character.You can read the whole file before starting the simulation or read one line at a time. We will not givemalformed input (e.g., negative number of processors after -p or more than 4 columns in the processdescription file).6 Expected OutputIn order for us to verify that your code meets the above specification, it should print to standard output(stderr will be ignored) information regarding the states of the system and statistics of its performance.All times are to be printed in seconds.6.1 Execution transcriptFor the following events the code should print out a line in the following format: When a (sub)process starts and every time it resumes its execution:current-time,RUNNING,pid=process-id,remaining_time=T,cpu=cpu-id\nwhere:current-time refers to The time at which CPU is given to a process;process-id refers to the id of the process that is about to be run;T refers to the remaining execution time for this process;cpu-id refers to the processor where the process is scheduled on. It can be 0, 1, 2 . . . , N 1 when-p N for N 1;Sample output could be:20,RUNNING,pid=15,remaining_time=10,cpu=0 Every time a process finishes:current-time,FINISHED,pid=process-id,proc_remaining=num-proc-left\nwhere: current-time is as above for the RUNNING event; process-id refers to the id of the process that has just been completed; num-proc-left refers to the number of processes that are waiting to be executed over allprocessors (i.e., those that have already arrived but not yet completed, including those thathave unfinished subprocesses).If there is more than one event to be printed at the same time: print FINISHED before RUNNING and printevents for smaller CPU ids first.Example: Consider the last remaining process which has 10 seconds left to completion. Then the followinglines may be printed:20,RUNNING,pid=15,remaining_time=10,cpu=130,FINISHED,pid=15,proc_remaining=06.2 Performance statisticsWhen the simulation is completed, 3 lines with the following performance statistics about your simulationperformance should be printed:3 Turnaround time: average time (in seconds, rounded up to an integer) between the time when theprocess completed and when it arrived; Time overhead: maximum and average time overhead when running a process, both rounded to thefirst two decimal points, where overhead is defined as the turnaround time of the process dividedby its total execution time (i.e., the one specified in the process description file). Makespan: the time in Seconds when your simulation ended.Example: For the invocation with arguments -p 1 and the processes file as described above, the simulationwould printTurnaround time 62Time overhead 2.93 1.9Makespan 1207 Marking CriteriaThe marks are broken down as follows:Task # and description Marks1. Single processor (Section 1) 22. 2 processors, non-parallelisable processes only 23. 2 processors, parallelisable and non-parallelisable processes 24. N processors, non-parallelisable processes only 25. N processors, parallelisable and non-parallelisable processes 26. Performance statistics computation (Section 6.2) 17. Challenge task (Section 4) 28. Quality of software practices 19. Build quality 1Tasks 1-6. We will run all baseline algorithms against our test cases. You will be given access to halfof these test cases and their expected outputs. Half of your mark for the first 6 tasks will be based onthese known test cases. Hence, we strongly recommend you to test your code against them. The first 5tasks will be marked based on the execution transcript (Section 6.1) and task 6 based on performancestatistics (Section 6.2).Task 7. The challenge task, as described in Section 4, will be evaluated based on a set of 9 test casesprovided to you and your report. We will use these test cases to compare the Makespan of your schedulingalgorithm (with -c option) with the default one. A scheduling algorithm that improves Makespan (i.e.,results in a shorter Makespan) over the default algorithm on 2-4 of the 9 test cases will be awarded 0.5marks, 1 mark for improving on 5-7 test cases and 1.5 marks for improving on 8-9 test cases. We mayuse a verification algorithm on your transcript to verify that your scheduler is sound (e.g., that everyprocess is given CPU time as per its execution time requirements and does not start before its arrivaltime). You will not be provided with expected output of the default scheduler for test cases in this task.Please submit a report explaining your scheduling algorithm and why it performs better than the defaultone. Reports longer than 50 words will automatically get 0 marks. Hence, ensure that you get 50 or lesswords when you run wc -w report.txt. The report should be in ASCII format. The report will get .5of a mark if your algorithm improves a makespan on at least one of the 9 test cases.Task 8. Quality of software practices Factors considered include quality of code, based on thechoice of variable names, comments, indentation, abstraction, modularity, and proper use of versioncontrol, based on the regularity of commit and push events, their content and associated commitmessages (e.g., repositories With a single commit and push, non-informative commit messages will lose0.5 mark).4Task 9. Build quality Running make clean make -B ./allocate command line argumentsshould execute the submission. If this fails for any reason, you will be told the reason, and be allowedto resubmit (with the usual late penalty). Compiling using -Wall should yield no warnings.Do not commit allocate or any other executable file (see Practical 2). A 0.5 mark penalty will be appliedif your final commit contains any such files. Executable scripts (with .sh extension) are excepted.The automated test script expects allocate to exit/return with status code of 0 (i.e. it successfullyruns and terminates).We will not give partial marks or allow code edits for either known or hidden cases without applyinglate penalty (calculated from the deadline).8 SubmissionAll code must be written in C (e.g., it should not be a C-wrapper over non C-code) and cannot use anyexternal libraries. Your code will likely rely on data structures for managing processes and memory. Youwill be expected to write your own versions of these data structures. You may use standard libraries(e.g. to print, read files, sort, parse command line arguments1etc.). Your code must compile and runon the provided VMs and produce deterministic output.The repository must contain a Makefile which produces an executable named allocate, along with allsource files required to compile the executable. Place the Makefile at the root of your repository, andensure that running make places the executable there too. Make sure that all source code is committedand pushed. Executable files (that is, all files with the executable bit which are in your repository)will be removed before Marking. Hence, ensure that none of your source files have the executable bit.For your own protection, it is advisable to commit your code to git at least once per day. Be sure topush after you commit. You can push debugging branches if your code at the end of a day is in anunfinished state, but make sure that your final submission is on the master branch. The git historymay be considered for matters such as special consideration, extensions and potential plagiarism. Yourcommit messages should be a short-hand chronicle of your implementation progress and will be used forevaluation in the Quality of Software Practices criterion.You must submit the full 40-digit SHA1 hash of your chosen commit to the Project 1 Assignmenton LMS. You must also push your submission to the repository named comp30023-2021-project-1in the subgroup with your username of the group comp30023-2021-projects on gitlab.eng.unimelb.edu.au. You will be allowed to update your chosen commit. However, only the last commit hashsubmitted to LMS before the deadline will be marked without late penalty.You should ensure that the commit which you submitted is accessible from a fresh clone of your repository.For example (below … are added for aesthetic purposes to break the line):git clone httpss://gitlab.eng.unimelb.edu.au/comp30023-2021-projects/username/ …… comp30023-2021-project-1cd comp30023-2021-project-1git checkout commit-hash-submitted-to-lmsLate submissions will incur a deduction of 2 mark per day (or part thereof).Extension policy: If you believe you have a valid reason to require an extension, please fill in the formaccessible on Project 1 Assignment on LMS. Extensions will not be considered otherwise. Requests forextensions are not automatic and are considered on a case by case basis.9 TestingYou have access to several test cases and their expected outputs. However, these test cases are notexhaustive and Will not cover all edge cases. Hence, you are also encouraged to write more tests tofurther test your own implementation.1 httpss://www.gnu.org/software/libc/manual/html_node/Getopt.html5Testing Locally: You can clone the sample test cases to test locally, from:comp30023-2021-projects/project-1.Continuous Integration Testing: To provide you with feedback on your progress before the deadline,we have set up a Continuous Integration (CI) pipeline on Gitlab. Though you are strongly encouragedto use this service, the usage of CI is not assessed, i.e., we do not require CI tasks to complete for asubmission to be considered for marking.Note that the test cases which are available on Gitlab are the same as the set described above.The requisite .gitlab-ci.yml file has been provisioned and placed in your repository, but is also availablefrom the project-1 repository linked above. Please clone, commit and push to trigger.10 Collaboration and PlagiarismYou may discuss this project abstractly with your classmates but what gets typed into your programmust be individual work, not copied from anyone else. Do not share your code and do not ask othersto give you their programs. Do not post your code on subjects discussion board Piazza. The best wayto help your friends in this regard is to say a very firm no if they ask to see your program, pointingout that your no, and their acceptance of that decision, are the only way to preserve your friendship.See httpss://academicintegrity.unimelb.edu.au for more information.Note also that solicitation of solutions via posts to online forums, whether or not there is paymentinvolved, is also Academic Misconduct. You should not post your code to any public location (e.g.,github) while the Assignment is active or prior to the release of the assignment marks.If you use any code not written by you, you must attribute that code to the source you got it from (e.g.,a book or Stack Exchange).Plagiarism policy: You are reminded that all submitted project work in this subject is to be yourown individual work. Automated similarity checking software may be used to compare submissions. Itis University policy that Cheating by students in any form is not permitted, and that work submitted forassessment purposes must be the independent work of the student concerned.Using git is an important step in the verification of authorship.请加QQ：99515681 或邮箱：99515681@qq.com WX：codehelp

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