The document discusses processes, threads, and multithreading in operating systems. It defines processes as having virtual address spaces and execution paths, while threads are the unit of dispatching. Multithreading allows multiple concurrent execution paths within a single process. Early systems only supported single threading, while modern systems support multiple processes and threads. Threads share resources within a process and have execution states. User-level threads are managed by applications while kernel-level threads are scheduled by the kernel. Symmetric multiprocessing allows threads to execute in parallel on multiple processors.
Operating system: threads(mulithreading,benefits of threads, types of thread)sonuu__
Hello techies, this is a presentation by my team on operating system threads..
Reference::Galvin
Hope this reference makes your learning experience well.
Operating system: threads(mulithreading,benefits of threads, types of thread)sonuu__
Hello techies, this is a presentation by my team on operating system threads..
Reference::Galvin
Hope this reference makes your learning experience well.
In this presentation, I am explaining about Threads, types of threads, its advantages and disadvantages, difference between Process and Threads, multithreading and its type.
"Like the ppt if you liked the ppt"
LinkedIn - https://in.linkedin.com/in/prakharmaurya
A thread is the smallest unit of processing that can be performed in an OS.
A thread is a flow of execution through the process code, with its own program counter that keeps track of which instruction to execute next, system registers which hold its current working variables, and a stack which contains the execution history.
Each thread belongs to exactly one process and no thread can exist outside a process.
Threads are also known as Lightweight processes.
For example, in a browser, many tabs can be viewed as threads. MS Word uses many threads - formatting text from one thread, processing input from another thread, etc.
This is the twelfth set of slightly updated slides from a Perl programming course that I held some years ago.
I want to share it with everyone looking for intransitive Perl-knowledge.
A table of content for all presentations can be found at i-can.eu.
The source code for the examples and the presentations in ODP format are on https://github.com/kberov/PerlProgrammingCourse
In this presentation, I am explaining about Threads, types of threads, its advantages and disadvantages, difference between Process and Threads, multithreading and its type.
"Like the ppt if you liked the ppt"
LinkedIn - https://in.linkedin.com/in/prakharmaurya
A thread is the smallest unit of processing that can be performed in an OS.
A thread is a flow of execution through the process code, with its own program counter that keeps track of which instruction to execute next, system registers which hold its current working variables, and a stack which contains the execution history.
Each thread belongs to exactly one process and no thread can exist outside a process.
Threads are also known as Lightweight processes.
For example, in a browser, many tabs can be viewed as threads. MS Word uses many threads - formatting text from one thread, processing input from another thread, etc.
This is the twelfth set of slightly updated slides from a Perl programming course that I held some years ago.
I want to share it with everyone looking for intransitive Perl-knowledge.
A table of content for all presentations can be found at i-can.eu.
The source code for the examples and the presentations in ODP format are on https://github.com/kberov/PerlProgrammingCourse
Scheduler Activations - Effective Kernel Support for the User-Level Managemen...Kasun Gajasinghe
Presentation slides presented by Kasun Gajasinghe and Nisansa de Silva at Dept. of Computer Science & Engineering, University of Moratuwa. Slides are for the paper titled “Scheduler Activations - Effective Kernel Support for the User-Level Management of Parallelism” by Thomas E. Anderson et.al.
Memory Management
Swapping
Fragmentation
Types of Fragmentation
Paging
Demand Paging
Segmentation
Virtual Memory
Von Neumann Architecture
overlay
Process and Thread
Process Synchronization
Deadlock
CPU Scheduling
process scheduling
Memory Management
Swapping
Fragmentation
Types of Fragmentation
Paging
Demand Paging
Segmentation
Virtual Memory
Von Neumann Architecture
overlay
Process and Thread
Process Synchronization
Deadlock
CPU Scheduling
process scheduling
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
These slides are intended to help a teacher develop a presentation. This PowerPoint covers the entire chapter and includes too many slides for a single delivery. Professors are encouraged to adapt this presentation in ways which are best suited for their students and environment.
Multithreading refers to the ability of an OS to support multiple, concurrent paths of execution within a single process.
Animated Slide Onload Enlarges top-left to discuss DOS Click1: Enlarges bottom-left for Unix Single Threaded approach: The traditional approach of a single thread of execution per process, in which the concept of a thread is not recognized, examples are MS DOS (single process, single thread) Unix (multiple, single threaded processes)
Animated Slide Onload: Emphasis on top-right and JRE (single process, multiple thread), Click 1: Emphasis on multiple processes with multiple threads – this is the main topic of this chapter JRE is an example of a system of one process with multiple threads. Of main interest in this chapter is the use of multiple processes, each of which support multiple threads. Examples include: Windows, Solaris, and many modern versions of UNIX.
In a multithreaded environment, a process is defined as the unit of resource allocation and a unit of protection.
Within a process, there may be one or more threads, each with the following: • A thread execution state (Running, Ready, etc.). • A saved thread context when not running; one way to view a thread is as an independent program counter operating within a process.
Distinction between threads and processes from the point of view of process management. In a single-threaded process model, the representation of a process includes its process control block user address space, user and kernel stacks to manage the call/return behaviour of the execution of the process. While the process is running, it controls the processor registers. The contents of these registers are saved when the process is not running. In a multithreaded environment, there is still a single process control block and user address space associated with the process, but separate stacks for each thread, as well as a separate control block for each thread containing register values, priority, and other thread-related state information. Thus , all of the threads of a process share the state and resources of that process. They reside in the same address space and have access to the same data. When one thread alters an item of data in memory, other threads see the results if and when they access that item. If one thread opens a file with read privileges, other threads in the same process can also read from that file.
If there is an application or function that should be implemented as a set of related units of execution, it is far more efficient to do so as a collection of threads - rather than a collection of separate processes.
Foreground and background work e.g. Spreadsheet – one thread looking after display Another thread updating results of formulae Asynchronous processing E.G. protection against power failure within a word processor, A thread writes random access memory (RAM) buffer to disk once every minute. this thread schedules itself directly with the OS; no need for fancy code in the main program to provide for time checks or to coordinate input and output. Speed of execution - On thread can compute one batch of data while another thread reading the next batch from a device. On a multiprocessor system, multiple threads from the same process may be able to execute simultaneously. Even though one thread may be blocked for an I/O operation to read in a batch of data, another thread may be executing. Modular program structure - Threads make it easier to design programs which involve a variety of activities or a variety of sources and destinations of input and output.
Suspension involves swapping the address space of one process out of main memory to make room for the address space of another process. Because all threads in a process share the same address space , all threads are suspended at the same time. Similarly, termination of a process terminates all threads within that process.
A significant issue is whether the blocking of a thread results in the blocking of the entire process. If one thread in a process is blocked, does this prevent the running of any other thread in the same process even if that other thread is in a ready state? Clearly, some of the flexibility and power of threads is lost if the one blocked thread blocks an entire process.
On a uniprocessor, multiprogramming enables the interleaving of multiple threads within multiple processes. In the example, - three threads in two processes are interleaved on the processor. - Execution passes from one thread to another either when the currently running thread is blocked or its time slice is exhausted.
An example of the use of threads is the Adobe PageMaker application running under a shared system. Three threads are always active: an event-handling thread, a screen-redraw thread, a service thread.
The kernel maintains context information for the process as a whole and for individual threads within the process. Scheduling by the kernel is done on a thread basis. -
In a combined approach, multiple threads within the same application can run in parallel on multiple processors, and a blocking system call need not block the entire process. If properly designed, this approach should combine the advantages of the pure ULT and KLT approaches while minimizing the disadvantages.
The concepts of resource allocation and dispatching unit have traditionally been embodied in the single concept of the process; that is, as a 1 : 1 relationship between threads and processes. There has been much interest in providing for multiple threads within a single process, which is a many-to-one relationship . However, as the table shows, the other two combinations have also been investigated, namely, a many-to-many relationship and a one-to-many relationship.
With the MIMD organization, the processors are general purpose, because they must be able to process all of the instructions necessary to perform the appropriate data transformation. MIMDs can be subdivided by the means in which the processors communicate. If the processors each have a dedicated memory, then each processing element is a self-contained computer. Such a system is known as a cluster, or multicomputer. If the processors share a common memory, then each processor accesses programs and data stored in the shared memory, and processors communicate with each other via that memory; sucha system is known as a shared-memory multiprocessor.
In a symmetric multiprocessor (SMP), the kernel can execute on any processor, and typically each processor does self-scheduling from the pool of available processes or threads. The kernel can be constructed as multiple processes or multiple threads, allowing portions of the kernel to execute in parallel. This complicates the OS. It must ensure that two processors do not choose the same process and that processes are not somehow lost from the queue. Techniques must be employed to resolve and synchronize claims to resources.
There are multiple processors, each of which contains its own control unit, arithmetic-logic unit, and registers. Each processor has access to a shared main memory and the I/O devices through some form of interconnection mechanism; a shared bus is a common facility. The processors can communicate with each other through memory (messages and status information left in shared address spaces). It may also be possible for processors to exchange signals directly. The memory is often organized so that multiple simultaneous accesses to separate blocks of memory are possible.