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COMP 310 Operating Systems Assignment
Creation date：2024-07-30 14:29:39
Belonging category：计算机computer science
Operating Systems Assignment
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ECSE 427/COMP 310 – Operating Systems Assignment 01 – Simple RPC Service
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High-Level Description
Consider a simple calculator. It has a read-eval-print-loop (REPL), where you enter something like
the following.
The calculator is structured as two programs: frontend and backend. The frontend does not do the
actual calculations. It just prints the prompt, get the input from the user, parses the input into a
message. The frontend passes the message to the backend that does the actual calculations and
passes the result back to the frontend, where it is printed to the user. We write two programs
backend.c and frontend.c. The backend has some functions it wants to expose for the frontend.
The frontend needs to call those functions that are exposed by the backend. The remote procedure
call service (RPCServ) is responsible for linking the two. You are expected to develop such a
RPCServ as part of this assignment. We start with a very simple implementation. The frontend
issues an execution command and backend runs it and returns the result. This simple structure
would work even with multiple frontends if the commands issued by the frontends can be executed
very quickly. If some commands can hold the backend for a long time (like seconds), we have a
problem. When a frontend is running a long command, other frontends will find the backend
unavailable. That is, you run sleep 5 in the frontend and the backend is held by that frontend for 5
seconds. If other frontends try to run a calculation, they will not get any results. To solve this
problem, you will use multi-processing. That is the backend will create a serving process for each
frontend. In this configuration, as soon as the frontend connects to the backend, we create a new
serving process that is dedicated to the frontend and let it serve the frontend’s requests. Even if the
frontend does a sleep 5, it would not cause problems for other frontends. The backend is still
available for requests from other frontends. To keep things simple, we limit the number of
concurrent frontends to 5.
Frontend Requirements
The pseudo code shown below for the frontend is not complete. It shows the bare essentials. You
need to add the missing functions to make the frontend meet all the requirements and make it work
with RPCServ and the backend.
backend = RPC_Connect(backendIP, backendPort)
while(no_exit) {
print_prompt()
line = read_line()
cmd = parse_line(line)
RPC_Call(backend, cmd.name, cmd.args)
}
RPC_Close(backend)
The frontend does not implement any of the commands the user enters into the shell. It simply
relays them to the backend. You will notice that the command entered by the user looks like the
following: command (string) and parameters. We will restrict the parameters to 2 or less. You can
have commands with no parameters. The parameters can be integers or floating-point numbers.
You need to have an RPCServ interface to send the command and parameters to the backend. In
the pseudo code, we show such an interface – RPC_Call(). The frontend will check if the user
has entered the exit command. If that is the case, the frontend will stop reading the next command
and terminate the association with the backend. The backend is a separate process, so it keeps
running even after the frontend has stopped running. The user can enter the shutdown command
in the frontend to terminate the backend. With multiple frontends connecting to the backend, the
shutdown can be tricky. More on this in the backend requirements. Some commands entered by
the user in the frontend may not be recognized by the backend, in that case the backend will send
the NOT_FOUND error message. The front needs to display this to the user. We can also have
error message for certain operations such as division by zero errors. These error messages need to
be displayed as well.
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CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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