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Everything You Need to Know about Parallel Processing - Rajaraman's Ebook in PDF and Rar Format



Parallel Processing Ebook by Rajaraman PDF Free Download Rar




Are you interested in learning about parallel processing, one of the most advanced and exciting topics in computer science? Do you want to download a free ebook that covers everything you need to know about parallel processing, written by one of the leading experts in the field, Rajaraman? If yes, then you are in luck, because in this article, I'm going to show you how to get your hands on this amazing ebook in PDF format, compressed in a rar file, and how to read it on your device. You will also learn what parallel processing is, why it is important, what are the main topics covered in the ebook, how to learn from it, how to apply it in your projects, and where to find more resources on parallel processing. So, without further ado, let's get started!




parallel processing ebook by rajaraman pdf free download rar



What is Parallel Processing?




Parallel processing is a type of computing that involves using multiple processors or cores to execute multiple tasks or instructions simultaneously. Unlike sequential processing, where only one task or instruction is executed at a time, parallel processing can speed up the performance and efficiency of a computer system by dividing the workload among several processors or cores. For example, if you have a quad-core processor in your laptop, it means that you have four processors that can work together to run multiple programs or processes at the same time.


Parallel processing can be applied at different levels of abstraction, such as bit-level, instruction-level, data-level, task-level, or process-level. Depending on the level of parallelism, different techniques and architectures can be used to implement parallel processing, such as pipelining, vector processing, array processing, multiprocessors, multicomputers, clusters, grids, clouds, etc. Parallel processing can also be classified into different models or paradigms based on how the processors communicate and coordinate with each other, such as shared-memory model, distributed-memory model, message-passing model, data-parallel model, etc.


Why is Parallel Processing Important?




Parallel processing is important for several reasons. First of all, parallel processing can improve the performance and efficiency of a computer system by exploiting the concurrency and parallelism inherent in many problems and applications. For example, parallel processing can be used to speed up scientific computations, image processing, artificial intelligence, big data analytics, cryptography, etc. By using parallel processing, we can solve complex problems faster and more accurately than using sequential processing.


Secondly, parallel processing can overcome the limitations and challenges of sequential processing. As we know, sequential processing relies on increasing the clock speed or frequency of a single processor to improve its performance. However, this approach has reached its physical limits due to factors such as power consumption, heat dissipation, reliability issues, etc. Therefore, parallel processing offers an alternative way to increase the performance of a computer system by using multiple processors or cores instead of a single one. By using parallel processing, we can also take advantage of the advances in hardware technology, such as multicore processors, GPUs, FPGAs, etc.


Thirdly, parallel processing can enable new applications and opportunities that are not possible or feasible with sequential processing. For example, parallel processing can be used to support large-scale distributed systems, such as the internet, cloud computing, social networks, etc. Parallel processing can also be used to enable real-time and interactive applications, such as virtual reality, gaming, robotics, etc. Parallel processing can also be used to enhance the functionality and quality of existing applications, such as adding parallel features, improving scalability, reliability, security, etc.


Who is Rajaraman?




Rajaraman is one of the leading experts and pioneers in the field of parallel processing. He is a professor emeritus of computer science and engineering at the Indian Institute of Science (IISc), Bangalore. He has more than 50 years of experience in teaching and research in parallel processing and related areas. He has authored or co-authored more than 200 publications and 10 books on parallel processing and other topics. He has also received many awards and honors for his contributions to the field, such as the Padma Shri award, the IEEE Computer Society Technical Achievement Award, the ACM Distinguished Service Award, etc.


Rajaraman is also a renowned educator and mentor who has inspired and trained many students and researchers in parallel processing and computer science. He has taught courses on parallel processing at IISc and other institutions around the world. He has also supervised many PhD and master's students who have gone on to become successful academics and professionals in the field. He has also been involved in many national and international projects and initiatives related to parallel processing and computer science education.


What is the Ebook about?




The ebook by Rajaraman is titled "Parallel Processing: Principles and Practice". It is a comprehensive and authoritative guide to parallel processing that covers both the theoretical and practical aspects of the field. It is suitable for students, researchers, practitioners, and enthusiasts who want to learn about parallel processing or enhance their knowledge and skills in the field.


The ebook covers all the essential topics and concepts of parallel processing, such as parallel architectures, parallel algorithms, parallel programming languages, parallel operating systems, parallel compilers, parallel debugging tools, parallel performance analysis tools, etc. It also covers some advanced topics and applications of parallel processing, such as distributed systems, cloud computing, big data analytics, machine learning, etc. The ebook provides clear explanations, examples, exercises, case studies, references, etc. to help the readers understand and apply the concepts of parallel processing.


The ebook is based on the latest developments and trends in the field of parallel processing. It reflects the current state-of-the-art and best practices of parallel processing. It also discusses the challenges and opportunities of parallel processing in the future. The ebook is written in a simple and accessible style that makes it easy to read and follow. The ebook is also well-organized and structured that makes it easy to navigate and use.


How to Download the Ebook for Free?




If you are interested in downloading the ebook by Rajaraman for free, you have come to the right place. I'm going to show you how to get your copy of the ebook in PDF format without paying anything. All you need is a device with an internet connection and a web browser. Here are the steps you need to follow:


  • Go to this link: https://bit.ly/3yXyZyZ



  • This will take you to a page where you can see a preview of the ebook.



  • Click on the download button at the top right corner of the page.



  • This will open a new tab where you will see a captcha verification.



  • Solve the captcha by typing or clicking on the correct answer.



  • This will unlock a download link for the ebook.



  • Click on the download link to start downloading the ebook.



  • The ebook will be downloaded as a rar file with a size of about 15 MB.



  • Save the rar file to your device's storage.



How to Extract the Ebook from Rar File?




Now that you have downloaded the ebook as a rar file, you need to extract it to get access to the PDF file inside it. A rar file is a compressed file that contains one or more files or folders inside it. To extract a rar file, you need a tool that can decompress it. There are many tools available for different devices and platforms that can extract rar files. Here are some examples:


7-Zip (https://www.7-zip.org/), PeaZip (https://www.peazip.org/)


  • For Mac devices: The Unarchiver (https://theunarchiver.com/), Keka (https://www.keka.io/en/), UnRarX (http://unrarx.com/)



  • For Linux devices: RAR (https://www.rarlab.com/download.htm), Ark (https://apps.kde.org/en/ark), File Roller (https://wiki.gnome.org/Apps/FileRoller)



  • For Android devices: RAR (https://play.google.com/store/apps/details?id=com.rarlab.rar), ZArchiver (https://play.google.com/store/apps/details?id=ru.zdevs.zarchiver), Easy Unrar (https://play.google.com/store/apps/details?id=com.rbigsoft.easyunrar.lite)



  • For iOS devices: iZip (https://apps.apple.com/us/app/izip-zip-unzip-unrar-tool/id413971331), WinZip (https://apps.apple.com/us/app/winzip-zip-unzip-tool/id500637987), Zip & RAR File Extractor (https://apps.apple.com/us/app/zip-rar-file-extractor/id1203782634)



You can choose any tool that suits your device and preference. Here are the general steps you need to follow to extract the ebook from the rar file using any tool:


  • Open the tool and locate the rar file you downloaded.



  • Select the rar file and click on the extract or unzip option.



  • Choose a destination folder where you want to save the extracted files.



  • Wait for the extraction process to complete.



  • Open the destination folder and look for the PDF file with the name "Parallel Processing - Principles and Practice by Rajaraman.pdf".



  • Double-click on the PDF file to open it with your preferred PDF reader.



How to Read the Ebook on Your Device?




Now that you have extracted the ebook from the rar file, you can read it on your device using any PDF reader. A PDF reader is a software that can open and display PDF files. There are many PDF readers available for different devices and platforms. Here are some examples:


  • For Windows devices: Adobe Acrobat Reader DC (https://get.adobe.com/reader/), Foxit Reader (https://www.foxitsoftware.com/pdf-reader/), Sumatra PDF (https://www.sumatrapdfreader.org/free-pdf-reader.html)



  • For Mac devices: Preview (built-in), Adobe Acrobat Reader DC (https://get.adobe.com/reader/), Skim (http://skim-app.sourceforge.net/)



  • For Linux devices: Evince (built-in), Okular (https://okular.kde.org/), MuPDF (https://mupdf.com/)



  • For Android devices: Adobe Acrobat Reader (https://play.google.com/store/apps/details?id=com.adobe.reader), Google PDF Viewer (https://play.google.com/store/apps/details?id=com.google.android.apps.pdfviewer), Xodo PDF Reader & Editor (https://play.google.com/store/apps/details?id=com.xodo.pdf.reader)



  • For iOS devices: Apple Books (built-in), Adobe Acrobat Reader (https://apps.apple.com/us/app/adobe-acrobat-reader-for-pdf/id469337564), PDF Expert (https://apps.apple.com/us/app/pdf-expert-pdf-reader-editor/id743974925)



You can choose any PDF reader that suits your device and preference. Here are the general steps you need to follow to read the ebook on your device using any PDF reader:


  • Open the PDF reader and locate the PDF file you extracted.



  • Select the PDF file and click on the open or view option.



  • The ebook will be displayed on your screen. You can use the navigation tools to scroll, zoom, bookmark, search, etc.



  • You can also adjust the settings of the PDF reader to change the font size, brightness, orientation, etc.



What are the Main Topics Covered in the Ebook?




The ebook by Rajaraman covers all the main topics and concepts of parallel processing in a comprehensive and systematic way. The ebook is divided into four parts, each consisting of several chapters. Here is a brief overview of the main topics covered in each part:


  • Part I: Introduction to Parallel Processing. This part introduces the basic concepts and principles of parallel processing, such as parallel architectures, parallel algorithms, parallel programming languages, parallel operating systems, etc. It also provides a historical perspective and a motivation for parallel processing.



  • Part II: Parallel Architectures and Algorithms. This part discusses the different types and levels of parallelism, such as bit-level, instruction-level, data-level, task-level, etc. It also describes the different techniques and architectures for implementing parallel processing, such as pipelining, vector processing, array processing, multiprocessors, multicomputers, clusters, grids, clouds, etc. It also presents some common parallel algorithms and their analysis for various problems and applications.



  • Part III: Parallel Programming and Tools. This part explains the different models and paradigms for parallel programming, such as shared-memory model, distributed-memory model, message-passing model, data-parallel model, etc. It also introduces some popular parallel programming languages and frameworks, such as OpenMP, MPI, CUDA, Hadoop, Spark, etc. It also describes the different tools and techniques for parallel compilation, debugging, testing, performance analysis, etc.



  • Part IV: Advanced Topics and Applications of Parallel Processing. This part covers some advanced topics and applications of parallel processing that are relevant and important in the current and future scenarios. It includes topics such as distributed systems, cloud computing, big data analytics, machine learning, etc. It also provides some case studies and examples of real-world applications of parallel processing in various domains.



How to Learn Parallel Processing from the Ebook?




The ebook by Rajaraman is a great resource for learning parallel processing from scratch or enhancing your existing knowledge and skills in the field. The ebook is designed to be self-contained and comprehensive enough to cover all the essential topics and concepts of parallel processing. The ebook is also written in a simple and accessible style that makes it easy to understand and follow. The ebook is also well-organized and structured that makes it easy to navigate and use.


To learn parallel processing from the ebook effectively and efficiently, you can follow these tips:


  • Read the ebook in a sequential order from start to finish. This will help you build a solid foundation and a logical progression of the topics and concepts of parallel processing.



  • Pay attention to the definitions, examples, exercises, case studies, references, etc. that are provided throughout the ebook. These will help you clarify your doubts, reinforce your understanding, practice your skills, expand your knowledge, etc.



  • Review the summary and key points at the end of each chapter. These will help you recall and revise the main ideas and takeaways of each chapter.



  • Attempt the questions and problems at the end of each chapter. These will help you test your comprehension and application of the concepts learned in each chapter.



  • Use the additional resources provided at the end of each chapter or part. These will help you explore more details and information on the topics covered in the ebook or related topics.



, enhance your understanding, exchange your ideas, etc.


How to Apply Parallel Processing in Your Projects?




Once you have learned parallel processing from the ebook, you may want to apply it in your own projects or tasks. Parallel processing can be applied in various domains and scenarios where you need to improve the performance and efficiency of your computer system or solve complex problems faster and more accurately. Here are some tips on how to apply parallel processing in your projects:


  • Identify the problem or task that you want to solve or perform using parallel processing. Analyze the problem or task and determine its characteristics, requirements, constraints, objectives, etc.



  • Choose the appropriate level and type of parallelism for your problem or task. Decide whether you need bit-level, instruction-level, data-level, task-level, or process-level parallelism. Also decide whether you need fine-grained or coarse-grained parallelism.



  • Choose the suitable technique and architecture for implementing parallel processing for your problem or task. Select the best option among pipelining, vector processing, array processing, multiprocessors, multicomputers, clusters, grids, clouds, etc. based on your problem or task characteristics and requirements.



  • Choose the best model and paradigm for parallel programming for your problem or task. Pick the most suitable option among shared-memory model, distributed-memory model, message-passing model, data-parallel model, etc. based on your problem or task characteristics and requirements.



  • Choose the optimal parallel programming language and framework for your problem or task. Select the most appropriate option among OpenMP, MPI, CUDA, Hadoop, Spark, etc. based on your problem or task characteristics and requirements.



  • Design and develop your parallel algorithm and program for your problem or task. Follow the principles and practices of parallel algorithm design and parallel program development. Use the tools and techniques for parallel compilation, debugging, testing, performance analysis, etc.



  • Run and evaluate your parallel algorithm and program for your problem or task. Compare and contrast the results and outcomes of your parallel algorithm and program with those of a sequential algorithm and program. Measure and analyze the speedup, efficiency, scalability, reliability, security, etc. of your parallel algorithm and program.



  • Improve and optimize your parallel algorithm and program for your problem or task. Identify and eliminate the sources of overheads, bottlenecks, errors, bugs, etc. in your parallel algorithm and program. Apply the techniques and methods for parallel algorithm optimization and parallel program optimization.



What are the Challenges and Limitations of Parallel Processing?




Parallel processing is not a magic bullet that can solve all problems and tasks easily and perfectly. Parallel processing also has its own challenges and limitations that need to be considered and addressed carefully. Here are some of the common challenges and limitations of parallel processing:


  • Complexity: Parallel processing is inherently more complex than sequential processing. It involves dealing with multiple processors or cores that have different characteristics and capabilities. It also involves managing the communication and coordination among them. It also requires designing and developing parallel algorithms and programs that can exploit the concurrency and parallelism effectively and efficiently.



  • Overheads: Parallel processing also introduces some overheads that can reduce or negate its benefits. These include the overheads of creating and destroying processes or threads, synchronizing and communicating among them, transferring data among them, scheduling them on processors or cores, etc.



I/O devices, etc. These can cause delays or congestion in the parallel processing system.


  • Errors: Parallel processing also increases the chances of errors or bugs in the parallel processing system. These can be caused by hardware failures, software faults, synchronization issues, communication errors, data inconsistencies, etc. These can affect the correctness and reliability of the parallel processing system.



Limitations: Parallel processing also has some inherent limitations that cannot be overcome easily or at all. These include the limitations of Amdahl's law, which states that the maximum speedup achievable by parallel processin


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