Wednesday, 21 August 2013

OS Lab2

OBJECTIVE (AIM) OF THE EXPERIMENT


To write a ‘C’ program to perform priority scheduling.

FACILITIES REQUIRED AND PROCEDURE

a) Facilities required to do the experiment:

Sl.No. Facilities required Quantity


1 System 1

2 Tel net, UNIX OS -

b) Procedure for doing the experiment:

Step

no. Details of the step


1 Start the program.

2 Read burst time, waiting time, turn the around time and priority.

3 Initialize the waiting time for process 1 and 0.

4 Based up on the priority process are arranged.

5 The waiting time for other processes are calculated based on priority.

6 The waiting time of all the processes is summed and then the average waiting time is

calculated.

7 The waiting time of each process and average waiting time are displayed based on the

priority.

8 Stop the program.

Output:


enter the no of process:3
enter the burst time:2
enter the priority:3
enter the burst time:4
enter the priority:1
enter the burst time:6
enter the priority:2
process to bt wt tt
1 4 0 4 4
1 6 4 10 14


OBJECTIVE (AIM) OF THE EXPERIMENT


To write a program to implement cpu scheduling for Round Robin Scheduling.

FACILITIES REQUIRED AND PROCEDURE

a) Facilities required to do the experiment:

Sl.No. Facilities required Quantity


1 System 1

2 Tel net, UNIX OS -

b) Procedure for doing the experiment:

Step

no. Details of the step


1 Get the number of process and their burst time.

2 Initialize the array for Round Robin circular queue as ‘0’.

3 The burst time of each process is divided by quantum and the quotients are stored on the round

robin array.

4 According to the array value the waiting time for each process and the average time

are calculated as like the other scheduling.

5 The waiting time for each process and average times are displayed.

6 Stop the program.

Output:


enter the no of process3
enter the burst time3
enter the burst time5
enter the burst time7
total burst time : 15

enter the time slice: 2

process id wt tt

1 0 2

2 2 4

3 4 6

1 6 7

2 7 9

3 9 11

2 11 12

3 12 14

3 14 15

avg waiting time: 21.666666

avg turnaround time: 26.666666
 

Thursday, 15 December 2011

Cluster and Grid Computing


Subject Description:
The growing popularity of the Internet along with the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we do parallel and distributed computing (PDC). The PDC  on local-area-networks is called  "cluster computing " and wide-area networks is called " grid computing" . Clusters employ cost-effective commodity components for building powerful computers within local-area networks, and Grids allow to share and aggregate geographically distributed resources ( such as supercomputers, storage systems, data sources, and special classes of devices) across the Internet.  They serve as cost-effective parallel and distributed computing platforms for solving large-scale resource (data and compute) intensive applications in science, commerce, and industry.
Some example of scientific and industrial applications that use these computing platforms are: system simulations, molecular modelling for drug design, brain analysis, weather forecasting, climate prediction, automobile modelling and design, structural engineering, high-energy physics, large-scale network simulation, and earth simulation.
Some examples of commercial applications that use these platforms: web servers (e.g.,  hotmail.com, yahoo.com), search engines (e.g., google.com is driven by a 4500 nodes Linux PC cluster), database engines (e.g., high-end oracle database server), financial modelling, peer-to-peer content sharing (e.g., napster) , and  web-content delivery (e.g., Akamai's world wide network of clusters delivers major web contents, e.g., cnn.com, from the nearest webserver transparently).

The IEEE/ACM Computing Curriculum 2001 has recognised the importance of net-centric computing (parallel and distributed computing) and recommended/proposed the introduction of cluster computing at senior under-graduate or post graduate level.
A coverage of topics in these two fields is discussed below:



Topic
Literature to Read
PART A: Foundations - START


Information Session


Socket  Programming in Java & Client Server Computing 
(**R**) Sockets in Java (Chapter 13 of Java Book)
Multi-Threading in Java
(**R**) Thread Programming in Java (Chapter 14 of Java Book)
Parallel Computing Overview 
(**R**) parintro
PART B: Cluster Computing - START


Cluster Computing: Introduction and System Architecture
  • (**R**) Mark Baker and Rajkumar Buyya, Cluster Computing at a Glance, High Performance Cluster Computing: Architectures and Systems (Vol. 1), Prentice Hall, NJ, USA, 1999.
Single System Image
Parallel Pogramming Models and Paradigms
  • (**R**) Luis Silva and Rajkumar Buyya, Parallel Programming Paradigms, High Performance Cluster Computing: Programming and Applications (Vol. 2), Prentice Hall, NJ, USA, 1999.
MPI Programming  and Excuting MPI using PBS
PART C: Grid Computing - START


Introduction and Overview of Grid Computing: Trends, Challenges, Technologies, and Applications
n
Industry Speaker: Microsoft HPC Server Lecture
Term Paper Topics and Projects
Style Format
   1. Grid Resource Management and Grid Economy
   2. Enterprise Grids and the Aneka Middleware    3. Nimrod-G Grid Resource Broker
   4. Economic Scheduling Algorithms

GridRM.ppt
Grid Brokering and Scheduling: with Nimrod-G and Gridbus Brokers Case Studes
Cloud Computing and Aneka
Globus Toolkit: Basics, Components, and Services
Globus paper & its website, Globus GIS, Globus Usage
Subject Review 
Conclusion and Future




Scientific Data Management

Instructors:  Dr. Laura Bright

 Course Description:

Scientists today face an avalanche of data.  Oceanographers generate Terabytes with daily forecasts of temperature, elevation, and velocity. Astronomers acquire hundreds of millions of images from increasingly powerful telescopes. Physicists are already discussing Petabyte-scale datasets collected from particle accelerators. Biologists have sequenced the Human genome, itself a large dataset, and are now describing the complex interactions between all 20,000 - 80,000 protein-encoding genes, not to mention the interactions between the proteins they encode. In all cases, scientists' ability to collect data has outpaced their ability to manage it. Complicate matters with non-standard data types, extreme performance demands, and ever-changing requirements, and you have one of the major data management challenges of today.
What do these applications have in common, and what new challenges do they present? In this course, we will investigate this question from the perspective of modern database research. We will survey the literature in this area and work with practical tools, such as the Kepler workflow system, the Visualization Toolkit, and relational databases.
The instructors will emphasize case studies from specific domains. We will work with online resources such as the Sloan Digital Sky Survey (SDSS), the Northwest Association of Networked Ocean Observing Systems (NANOOS), and biological databases such as Swiss-prot/TrEMBL.
The instructors will also emphasize overarching computer science themes that stand out in each of these domains: relational, object-relational, and non-relational databases; grid computing; workflow systems; data models; visualization; metadata management.

Schedule (subject to change!)

Week/Day Lecture Reading Due Assignment Handed Out Assignment Due
1/Thur: 7/6 Lecture 1 (ppt) None None None
2/Tue: 7/11 Intro to Relational Databases (ppt) Ramakrishnan and Gehrke 3.1, 3.2, 3.4, 4.1, 4.2, 5.1, 5.2 (Handout) Homework 1 (sample answers) None
2/Thur: 7/13 Relational 2(ppt)Lecture 3 (ppt) Working with Scientists; Section 9 from SkyServer None Study Questions 1
3/Tue: 7/18 Web Services(ppt) Service-Oriented Science Paper Milestone 1 Homework 1 (sample answers)
3/Thur: 7/20 Introduction to XML (ppt) XML Tutorial,XSLT vs XQuery

4/Tue: 7/25 Geographic Information Systems and Spatial Databases (ppt) A Survey on Multidimensional Access Methods
Study Questions 2
4/Thur: 7/27 Introduction to Computational Biology(ppt) Homework 1 review (ppt) O'Reilly BLAST C2 (handout) Paper Milestone 2 Paper Milestone 1
5/Tue: 8/1 Biology Applications with Web Services(ppt) O'Reilly BLAST C3,C5 (handout)
Study Questions 3
5/Thur: 8/3 Scientific Workflows(ppt) Kepler User Guide Homework 2(Kepler Exercise)(html)
6/Tue: 8/8 Scientific Workflows(ppt) Kepler
Study Questions 4
6/Thur: 8/10 Grid Computing(ppt) Computational Grids Kepler Mini-Project(html) Homework 2
7/Tue: 8/15 Data Grids(ppt) Taxonomy
Study Questions 5
7/Thur: 8/17 Images and Multidimensional Arrays Iterator-based Prefetching
OR
Tiling Arrays
Paper Milestone 3Paper Milestone 2
8/Tues: 8/22 Scientific Visualization (ppt) VisTrails Homework 3 (Visualization with VTK and Python) Study Questions 6
8/Thurs: 8/24 High-dimensional Data (3MB) (ppt - 13MB) HD Access Methods
Kepler Mini-project
9/Tue: 8/29 Resource Description Framework (RDF)


9/Thur: 8/31 Ontologies in Science(ppt) Science and the Semantic Web Brief Owl Intro
Homework 3
10/Tue: 9/5 Metadata
Final Paper; Homework 4 (Protege Exercise)Paper Milestone 3
10/Thur: 9/7 Provenance and Lineage Provenance Survey
Study Questions 7
11/Tue: 9/12 TBA TBA TBA Homework 4
11/Thur: 9/14 TBA TBA
Final Paper