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Assignment #2 Simulator for a computer

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BLG 252E – Object Oriented Programming
Assignment #2
Introduction
In this assignment, you are expected to implement a simplified version of a simulator for a computer. Computer entities would execute operations using CPU (Central Processing Unit) and GPU (Graphics Processing
Unit) entities which use ALU (Arithmetic Logic Unit) and CUDA cores, respectively. This assignment aims
to support the understanding of the relationships between classes.
For any issues regarding the assignment, please contact Erhan Biçer (bicer21@itu.edu.tr).
Implementation Notes
The implementation details below are included in the grading:
1. Please follow a consistent coding style (indentation, variable names, etc.) with comments.
2. Do not use any pre-compiled header files or STL commands.
3. You may (and should) implement any getter and setter methods.
4. Make sure that there is no memory leak in your code.
5. Define required methods and variables as const in all necessary cases.
6. Do not make any modifications in the given main.cpp. Your code will be evaluated using the given
main.cpp.
7. Ensure that your outputs match with the sample scenario for given inputs. You will be provided with
a calico file to check your assignment output.
Submission Notes
1. Your program should compile and run on Linux environment. You should code and test your program
on Docker’s Virtual Environment.
2. As source code submission, send only Computer.h and Computer.cpp that contain all necessary
declarations and definitions. Along with source codes, you should submit report and log file.
3. Do not change included libraries and path to header files.
4. Submissions are made through only the Ninova system and have a strict deadline. Assignments
submitted after the deadline will not be accepted.
5. This is not a group assignment, and getting involved in any kind of cheating is subject to disciplinary actions. Your homework should not include any copy-paste material (from the Internet or
from someone else’s paper/thesis/project).
1
Operations Unit
add CPU
subtract CPU
multiply CPU
render GPU
trainModel GPU
Table 1: Operations and responsible components
1 Implementation Details
You are expected to implement five classes; Computer, CPU, GPU, ALU, and CUDA.
1.1 Computer
The computer can perform five operations using its components, as given in Table 1.
1. Computer class has two attributes, attachedCPU and attachedGPU that point to attached CPU and
GPU, respectively. The computer never modifies the internal states of the attached CPU and GPU.
2. CPU and GPU can be attached to a computer using the “+” operator. Operands should be a computer
class object and reference to CPU or GPU class object. Adding new entities to a computer is
not possible if other entities are already attached.
3. To execute an operation on the computer, execute method is called by giving the operation name as
an argument. Defined operation types and the responsible unit are stated in Table 1. The computer
sends the operation as an argument to the relevant component’s execute method according to the
given table and prints the result. Execution does not change the attributes of the CPU and GPU.
1.2 CPU
1. CPU class contains an ALU object. CPU initializes ALU’s numPerCores attribute.
2. A CPU can execute relevant operations with execute method. It reads two integers from the
keyboard, delegates the operation to the ALU, and returns the result.
1.3 GPU
1. A GPU contains a CUDA object. GPU initializes CUDA’s numCores variable.
2. A GPU can execute operations with execute method. Within this method, it uses its cuda for operations and returns the result.
1.4 ALU
1. ALU contains an integer numPerCores variable representing the number of ALUs per CPU core.
2. ALU contains add, subtract and multiply methods. These methods take two integers as arguments
and returns the result.
1.5 CUDA
1. CUDA contains an integer numCores variable, representing the number of CUDA cores.
2. CUDA cores can be used to render a video by calling its render method. This method will return the
result as: “Video is rendered”.
3. CUDA cores can be used to train an AI model by calling its trainModel method. This method will
return the result as: “AI Model is trained”.
2
Notice: Member variables should not be accessed directly outside of the class.
!
2 Main method
Your output should be like the below after running the given main.cpp:
Command Line
Computer is ready
ALU is ready
CPU is ready
CUDA is ready
GPU is ready
CPU is attached
GPU is attached
ALU is ready
CPU is ready
CUDA is ready
GPU is ready
There is already a CPU
There is already a GPU
Operation type is:
subtract
Enter two integers
5
3
2
Operation type is:
render
Video is rendered
Operation type is:
trainModel
AI Model is trained
Operation type is:
add
Enter two integers
1
2
3
Operation type is:
multiply
Enter two integers
4
5
20
3 Report
Draw a UML class diagram that represents the association between the classes. Show special type of
associations if there is any. You can use this website to draw a UML diagram. Below the diagram, write
down all of the associations. Also, write examples of parameter visibility if there is any.
3
4 How to compile, run and test your code:
You can build and run your code with the below commands. Otherwise, you can work with VSCode
for debugging and running the code. In VSCode, ensure that the assignment folder is opened in the
explorer.
$ g ++ – Wall – Werror src / Computer . cpp src / main . cpp -I include -o assignment2
$ ./ assignment2
Given yaml file checks both for memory leak using Valgrind and test the outputs using calico. To check
your code, run the below command and send the log through Ninova:
$ calico assignment2_eval . yaml — debug |& tee calico_log . txt
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