Rohan Patil bridgesign

Constructing a System call that gives the count of how many times System call Read was called.

We will be using xv6 OS for this exercise. In this exercise, we will construct a system call that can give read counts on per process basis and then modify it to obtain a system call that will give read counts of all processes since the start of kernel.

Adding the counter

To add a system call that can get the number of times the system call 'read' was used in a specific program, we require to make a variable that stores this count for each process.

So, we first start by looking at the files proc.c and proc.h
These files are associated with creating a process. We need to store the count on a per process basis so we will have to add something to the structure that is created for a process.
For that, open proc.h. In this file, the structure for a process is defined. Find struct proc and then add an integer to keep account for the read calls. eg. int readid;

	# This is a modified version of the original file from the Modulus repository (NVIDIA)
	# The original file can be found at:
	# https://github.com/NVIDIA/modulus-sym/blob/main/modulus/sym/utils/sympy/torch_printer.py
	# The original file is licensed under the Apache License, Version 2.0
	# The modified file is provided under the same license
	# The original file disclaimer is provided below:

	# SPDX-FileCopyrightText: Copyright (c) 2023 - 2024 NVIDIA CORPORATION & AFFILIATES.
	# SPDX-FileCopyrightText: All rights reserved.
	# SPDX-License-Identifier: Apache-2.0

	import torch
	import warnings

	class BiCGSTAB():
	"""
	This is a pytorch implementation of BiCGSTAB or BCGSTAB, a stable version
	of the CGD method, published first by Van Der Vrost.

	For solving ``Ax = b`` system.

	class generator:
	"""
	The generator creates a single ad slot with a random user and
	makes the bidders to bid for the slot. Depending on the result,
	it sends back the result to the individual bidders.
	"""
	def __init__(self, users, bidders):
	self.users = users
	self.bidders = bidders
	self.bidders_num = len(bidders)

	class bidmodel(nn.Module):
	"""
	This defines the neural model used by the bidder
	It gives teo vectors as output. The first is the vectors
	of bids and the second the probability of click vector over
	all the ads the bidder owns.
	"""
	def __init__(self, size, cuda=True):
	super(bidmodel, self).__init__()

	class user:
	"""
	The user class defines a user which are a part of the game
	It keeps the views and clicks vector for all the ads and shares the
	data to the bidder only about the ads the bidder owns

	It also determines whether it will see the ad or not depending on
	the overall clicks and views of all ads.

	It also updates the vectors based on the view and click. The data about

	#include <stdio.h>
	#include <stdlib.h>
	#include <sys/types.h>
	#include <unistd.h>
	#include <string.h>
	#include <sys/stat.h>
	#include <fcntl.h>
	#define _GNU_SOURCE

	void grep(int file, const char *pattern){