PowerPoint Presentation on Distributed Operating Systems,reasons for opting for distributed systems over centralized systems,types of Distributed Systems,Process Migration and its advantages.
Overview of Network Programming, Remote Procedure Calls, Remote Method Invocation, Message Oriented Communication, and web services in distributed systems
A multiprocessor is a computer system with two or more central processing units (CPUs), with each one sharing the common main memory as well as the peripherals. This helps in simultaneous processing of programs.
The key objective of using a multiprocessor is to boost the system’s execution speed, with other objectives being fault tolerance and application matching.
A good illustration of a multiprocessor is a single central tower attached to two computer systems. A multiprocessor is regarded as a means to improve computing speeds, performance and cost-effectiveness, as well as to provide enhanced availability and reliability.
PowerPoint Presentation on Distributed Operating Systems,reasons for opting for distributed systems over centralized systems,types of Distributed Systems,Process Migration and its advantages.
Overview of Network Programming, Remote Procedure Calls, Remote Method Invocation, Message Oriented Communication, and web services in distributed systems
A multiprocessor is a computer system with two or more central processing units (CPUs), with each one sharing the common main memory as well as the peripherals. This helps in simultaneous processing of programs.
The key objective of using a multiprocessor is to boost the system’s execution speed, with other objectives being fault tolerance and application matching.
A good illustration of a multiprocessor is a single central tower attached to two computer systems. A multiprocessor is regarded as a means to improve computing speeds, performance and cost-effectiveness, as well as to provide enhanced availability and reliability.
This presentation talks about Real Time Operating Systems (RTOS). Starting with fundamental concepts of OS, this presentation deep dives into Embedded, Real Time and related aspects of an OS. Appropriate examples are referred with Linux as a case-study. Ideal for a beginner to build understanding about RTOS.
INTRODUCTIONTO OPERATING SYSTEM
What is an Operating System?
Mainframe Systems
Desktop Systems
Multiprocessor Systems
Distributed Systems
Clustered System
Real -Time Systems
Handheld Systems
Computing Environments
A Distributed File System(DFS) is simply a classical model of a file system distributed across multiple machines.The purpose is to promote sharing of dispersed files.
A summary of the major events that brought about cloud computing, starting in the 1950s. You can find this information and much more in Oneserve's 'Ultimate Guide to the Cloud'.
INTRODUCTION
WHAT IS OSI?
OSI MODEL
TYPES OF LAYERS
PHYSICAL LAYER
DATA LINK LAYER
NETWORK LAYER
TRANSPORT LAYER
SESSION LAYER
PRESENTATION LAYER
APPLICATION LAYER
This presentation talks about Real Time Operating Systems (RTOS). Starting with fundamental concepts of OS, this presentation deep dives into Embedded, Real Time and related aspects of an OS. Appropriate examples are referred with Linux as a case-study. Ideal for a beginner to build understanding about RTOS.
INTRODUCTIONTO OPERATING SYSTEM
What is an Operating System?
Mainframe Systems
Desktop Systems
Multiprocessor Systems
Distributed Systems
Clustered System
Real -Time Systems
Handheld Systems
Computing Environments
A Distributed File System(DFS) is simply a classical model of a file system distributed across multiple machines.The purpose is to promote sharing of dispersed files.
A summary of the major events that brought about cloud computing, starting in the 1950s. You can find this information and much more in Oneserve's 'Ultimate Guide to the Cloud'.
INTRODUCTION
WHAT IS OSI?
OSI MODEL
TYPES OF LAYERS
PHYSICAL LAYER
DATA LINK LAYER
NETWORK LAYER
TRANSPORT LAYER
SESSION LAYER
PRESENTATION LAYER
APPLICATION LAYER
Parallel and Distributed Programming Paradigms
Introduction, Parallel and distributed system architectures, Strategies for Developing
Parallel and Distributed Applications, Methodical Design of Parallel and Distributed
Algorithms
Cloud Software Environments - Google App Engine, Amazon AWS, Azure
PARALLEL ARCHITECTURE AND COMPUTING - SHORT NOTESsuthi
Short Notes on Parallel Computing
Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time.
Theory related to OS :
It Includes:
1. Unit I (COMPONENTS OF COMPUTER SYSTEM)
2. Unit II (OPERATING SYSTEM STRUCTURE)
3. Unit III (PROCESS MANAGEMENT)
4. Unit IV (MEMORY MANAGEMENT)
5. Unit V (FILE SYSTEM)
6. Unit VI (INPUT OUTPUT SYSTEM)
Distributed system lectures
Engineering + education purpose
This series of lectures was prepared for the fourth class of computer engineering / Baghdad/ Iraq.
This series is not completed yet, it is just a few lectures in the object.
Forgive me for anything wrong by mistake, I wish you can profit from these lectures
My regard
Marwa Moutaz/ M.Sc. studies of Communication Engineering / University of Technology/ Bagdad / Iraq.
MODULE III Parallel Processors and Memory Organization 15 Hours
Parallel Processors: Introduction to parallel processors, Concurrent access to memory and cache
coherency. Introduction to multicore architecture. Memory system design: semiconductor memory
technologies, memory organization. Memory interleaving, concept of hierarchical memory
organization, cache memory, cache size vs. block size, mapping functions, replacement
algorithms, write policies.
Case Study: Instruction sets of some common CPUs - Design of a simple hypothetical CPU- A
sequential Y86-64 design-Sun Ultra SPARC II pipeline structure
Introduction to distributed systems
Architecture for Distributed System, Goals of Distributed system, Hardware and Software
concepts, Distributed Computing Model, Advantages & Disadvantage distributed system, Issues
in designing Distributed System,
Types of database processing,OLTP VS Data Warehouses(OLAP), Subject-oriented
Integrated
Time-variant
Non-volatile,
Functionalities of Data Warehouse,Roll-Up(Consolidation),
Drill-down,
Slicing,
Dicing,
Pivot,
KDD Process,Application of Data Mining
Data Warehouse Physical Design,Physical Data Model, Tablespaces, Integrity Constraints, ETL (Extract-Transform-Load) ,OLAP Server Architectures, MOLAP vs. ROLAP, Distributed Data Warehouse ,
Data marts,Types of Data Marts,Multidimensional Data Model,Fact table ,Dimension table ,Data Warehouse Schema,Star Schema,Snowflake Schema,Fact-Constellation Schema
Introduction to Electronic Commerce: Introduction of commerce, Electronic
commerce framework, electronic commerce and media convergence, the anatomy
of e-commerce application,The Network for Electronic Commerce: Need of network, market forces
influencing the I-way, components of I-way, network access equipment, and
global information distribution network.
The Internet as a Network Infrastructure: Introduction, the Internet terminology,
NSFNET: Architecture and Components, Internet governance: The Internet
Society.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
2. P ARALLEL P ROCESSING
The simultaneous use of more than one CPU to execute a program.
Ideally, parallel processing makes a program run faster because there
are more engines (CPUs) running it.
In practice, it is often difficult to divide a program in such a way that
separate CPUs can execute different portions without interfering with
each other.
In computers, parallel processing is the processing of program
instructions by dividing them among multiple processors with the
objective of running a program in less time. In the earliest computers,
only one program ran at a time
3. Types of Parallel Processor Systems
Parallel computing is an evolution of serial computing where the jobs
are broken into discrete parts that can be executed concurrently.
Each part is further broken down to a series of instructions.
Instructions from each part execute simultaneously on different
CPUs.
Flynn has classified the computer systems based on parallelism in the
instructions and in the data streams. These are:
4. Types of Parallel Processor Systems
1. Single instruction stream, single data stream (SISD).
2. Single instruction stream, multiple data stream (SIMD).
3. Multiple instruction streams, single data stream (MISD).
4. Multiple instruction stream, multiple data stream (MIMD).
5. Single instruction stream, single data
stream (SISD).
A single processor executes a single instruction stream to operate on
data stored in a single memory.
Uniprocessors fall into this category.
6. Single instruction stream, multiple data
stream (SIMD).
Single machine instruction controls the simultaneous execution of a
number of processing elements on a lockstep basis.
Each processing element has an associated data memory, so that
instructions are executed on different sets of data by different
processors.
Vector and array processors fall into this category
7. Multiple instruction, multiple data (MIMD)
stream
A set of processors simultaneously execute different instruction
sequences on different data sets.
SMPs, clusters, and NUMA systems fit into this category
8. Multiple instruction, single data (MISD)
stream
A sequence of data is transmitted to a set of processors, each of which
executes a different instruction sequence.
This structure is not commercially implemented
10. SYMMETRIC MULTIPROCESSORS
The term SMP refers to a computer hardware architecture and also to
the operating system behavior that reflects that architecture.
An SMP can be defined as a standalone computer system with the
following characteristics
1. There are two or more similar processors of comparable capability.
2. These processors share the same main memory and I/O facilities
and are inter-connected by a bus or other internal connection
scheme, such that memory access time is approximately the same
for each processor.
11. SYMMETRIC MULTIPROCESSORS
3. All processors share access to I/O devices, either through the same
channels or through different channels that provide paths to the same
device.
4. All processors can perform the same functions (hence the term
symmetric).
5. The system is controlled by an integrated operating system that
provides interaction between processors and their programs at the job,
task, file, and data element levels.
12. SYMMETRIC MULTIPROCESSORS
The operating system of an SMP schedules processes or threads
across all of the processors. An SMP organization has a number of
potential advantages over a uniprocessor organization, including the
following:
Performance: If the work to be done by a computer can be organized
so that some portions of the work can be done in parallel, then a
system with multiple processors will yield greater performance than
one with a single processor of the same type
Availability: In a symmetric multiprocessor, because all processors can
perform the same functions, the failure of a single processor does not
halt the machine. Instead, the system can continue to function at
reduced performance.
13. SYMMETRIC MULTIPROCESSORS
Incremental growth: A user can enhance the performance of a system
by adding an additional processor.
Scaling: Vendors can offer a range of products with different price and
performance characteristics based on the number of processors
configured in the system.
14. Cache Coherence and the MESI Protocol
1. In contemporary multiprocessor systems, it is customary to have
one or two levels of cache associated with each processor.
2. This organization is essential to achieve reasonable performance. It
does, however, create a problem known as the cache coherence
problem.
3. The essence of the problem is this: Multiple copies of the same data
can exist in different caches simultaneously, and if processors are
allowed to update their own copies freely, an inconsistent view of
memory can result
15. Cache Coherence and the MESI Protocol
1. Write back: Write operations are usually made only to the cache.
Main memory is only updated when the corresponding cache line is
flushed from the cache.
2. Write through: All write operations are made to main memory as
well as to the cache, ensuring that main memory is always valid.
3. If two caches contain the same line, and the line is updated in one
cache, the other cache will unknowingly have an invalid value.
Subsequent reads to that invalid line produce invalid results. Even
with the write-through policy, inconsistency can occur unless other
caches monitor the memory traffic or receive some direct
notification of the
16. Cache Coherence and the MESI Protocol
Cache coherence approaches have generally been divided into
software and hardware approaches. Some implementations adopt a
strategy that involves both software and hardware elements
Software Solutions:
Software cache coherence schemes attempt to avoid the need for
additional hardware circuitry and logic by relying on the compiler and
operating system to deal with the problem.
Software approaches are attractive because the overhead of detecting
potential problems is transferred from run time to compile time, and
the design complexity is transferred from hardware to software.
17. Cache Coherence and the MESI Protocol
Hardware Solutions:
Hardware-based solutions are generally referred to as cache coherence
protocols. These solutions provide dynamic recognition at run time of
potential inconsistency conditions. Because the problem is only dealt
with when it actually arises, there is more effective use of caches,
leading to improved performance over a software approach.
In addition, these approaches are transparent to the programmer and
the compiler, reducing the software development burden.