Multithreading Design Patterns

Quarkus offers a great development experience. In this session, I’ll introduce you to the power of Quarkus Live Coding and tools that are useful to developers for debugging, deploying, and testing Quarkus applications.

This document provides an overview of developing a web application using Spring Boot that connects to a MySQL database. It discusses setting up the development environment, the benefits of Spring Boot, basic project structure, integrating Spring MVC and JPA/Hibernate for database access. Code examples and links are provided to help get started with a Spring Boot application that reads from a MySQL database and displays the employee data on a web page.

This document discusses several design patterns including Singleton, Observer, Delegation, Adapter, Facade, Immutable, Read-Only Interface, Proxy, and Factory. For each pattern, the document describes the context, problem, forces, and solution. The patterns provide reusable solutions to common programming problems by separating interfaces from implementations.

Rasheed Amir presents on Spring Boot. He discusses how Spring Boot aims to help developers build production-grade Spring applications quickly with minimal configuration. It provides default functionality for tasks like embedding servers and externalizing configuration. Spring Boot favors convention over configuration and aims to get developers started quickly with a single focus. It also exposes auto-configuration for common Spring and related technologies so that applications can take advantage of them without needing to explicitly configure them.

Spend some time working with OpenAPI and gRPC and you’ll notice that these two technologies have a lot in common. Both are open source efforts, both describe APIs, and both promise better experiences for API producers and consumers. So why do we need both? If we do, what value does each provide? What can each project learn from the other? We’ll bring the two together for a side-by-side comparison and pose answers to these and other questions about two API methodologies that will do much to influence the future of networked APIs.

This document discusses how to handle merge conflicts in Git version control. It begins by explaining that Git can automatically resolve most merge conflicts and that conflicts only occur locally on a user's machine. It then describes how a conflict happens when two people modify the same line of the same file differently. The document explains that a conflict is simply different versions of a file represented by funny letters. It advises understanding what caused the conflict by determining that two developers modified the same file and lines. Finally, it provides instructions for solving a conflict by editing the file, using a merge tool, or GUI client and then staging and committing the resolved changes.

This document provides an introduction to using Git and GitHub for version control of documents and collaboration. It explains the basic workflow of creating, editing, and saving files individually. It then introduces Git as a tool to track changes to documents over time, including who made each change and when. The document outlines setting up Git locally and using basic commands like commit, diff, log, branch, merge, and push/pull to the remote GitHub repository. It highlights key GitHub features like the profile page, repository page, pull requests, and hosting websites for free using GitHub Pages.

* What is different GitHub Flow and Git Flow? * What is GitHub Actions? * How to write the simple workflow? * What's problem in GitHub Actions UI? * What's problem with Secrets in GitHub Actions? * How to write your first GitHub Actions and upload to the marketplace? * What's a problem with environment variables in GitHub Actions?

An introduction to reactive programming concepts and basics. I aim here to show what's reactive programming, why it's used and show some frameworks and benchmarks that support it.

Java concurrency allows applications to make use of multiple processors and handle asynchronous operations through the use of threads. While concurrency provides benefits like improved performance, it also introduces risks like race conditions and deadlocks if threads access shared resources unsafely. The Java threading APIs provide tools for safely managing concurrent operations through mechanisms like synchronization, locks, and concurrent collections.

This document provides an overview of the Laravel PHP framework. It discusses Laravel's history and evolution from version 1 to the current version 5.3. Key Laravel concepts are explained such as routing, controllers, models, views, Artisan commands, and architectural changes in version 5 like the directory structure and environment detection. Additional Laravel tools and resources are also mentioned like Laravel Elixir, Homestead, and Laracasts.

This is very basic laravel presentation. I tried to cover all the topics in this presentation. For more information, please feel free to email me - toufiqist@gmail.com

Vert.x is a toolkit for building reactive microservices applications on the JVM. It uses the reactor pattern with a single-threaded event loop to avoid the C10K problem. Verticles are lightweight concurrent units that communicate asynchronously via an event bus. This allows building scalable and reactive microservices. Vert.x supports websockets, clustering, reactive programming with RxJava, and can be deployed to production environments like AWS. It also integrates with Spring for dependency injection and configuration.

Slides for a presentation given at the Go MN meetup https://www.meetup.com/golangmn/ given on 4/15/2020. The associated code is available at https://github.com/andreburgaud/meetup-golang-lua. The topic is about the interoperability between Go and Lua, or Lua and Go.

A short introduction to a powerful Design by Contract technique and its implementation in ruby contracts.ruby. Design by Contract allows one to do defensive programming in very elegant fashion, allows to set contracts on methods (expectations on input - arguments; and on output - return result) and invariants on classes. This allows to reason about code much much better.

Git is a free and open source distributed version control system that allows tracking changes to projects, enabling reversion to previous versions and collaboration. It runs locally, keeping track of file histories, and remote hosts like GitHub can be used to host projects and histories, enabling collaboration through pushing and pulling changes. Git provides functionality, performance, security and flexibility needed for both individual and team development.

The document discusses object-oriented programming (OOP) and functional programming (FP). It argues that OOP and FP are not opposites and can be effectively combined. It addresses common myths about FP, such as that it is new, hard, or only suitable for mathematical problems. The document also compares how OOP and FP approach concepts like decomposition, composition, error handling, and mutability/referential transparency. While both approaches have merits, the document concludes there is no single best approach and the choice depends on the problem and programmer preferences.

This document discusses design pattern automation and the use of pattern-aware compilers. It provides a history of programming languages and patterns, defines design pattern automation as using tools to optimize productivity in implementing software based on patterns. It discusses how pattern-oriented software development involves implementing patterns at multiple levels of abstraction. It also addresses myths around why patterns cannot be automated and argues that emerging design and agile methodologies allow patterns to naturally emerge from iterative design processes. An example of applying automation to the Reader-Writer pattern through code generation and verification is also provided.

Multicore processors are becoming prevalent due to the limitations of increasing single core clock speeds. This presents challenges for software to effectively utilize multiple cores. Functional programming is one option that avoids shared state and parallel access issues, but requires a significant mindset shift. Refactoring existing code using tools is another option to incrementally introduce parallelism. Hybrid approaches combining paradigms may also help transition. Key application areas currently benefiting include servers, scientific computing, and packet processing. However, significant existing code is not easily parallelized and performance gains have yet to be fully realized.

There are a lot of upcoming performance changes in .NET. Starting from code generation (JIT, AOT) and optimizations that can be performed by the compiler (inlining, flowgraph & loop analysis, dead code elimination, SIMD, stack allocation and so on). In this talk we will cover some features of C# 7 are going towards making low level optimization. I will share not only how we can improve performance with the next version of .NET, but how we can do it today using different techniques and tools like Roslyn analyzers, Channels (Push based Streams), System.Slices, System.Buffers and System.Runtime.CompilerServices.Unsafe.

Everybody knows the lock keyword, but how does it implemented? What are its performance characteristics. Gael Fraiteur scratches the surface of multithreaded programming in .NET and goes deep through the Windows Kernel down to CPU microarchitecture.

Paper: Type-preserving Heap Profiler for C++ Authors: József Mihalicza, Zoltán Porkoláb and Ábel Gábor Session: "Industry Track Session 4: Program analysis and Verification"

The document discusses modern Java concurrency. It introduces the topic and explains why developers may want to utilize modern Java concurrency features. It discusses the java.util.concurrent library and how it provides building blocks for concurrent and thread-safe code like ReentrantLock, Condition, ConcurrentHashMap. It provides examples of using constructs like CountDownLatch, ThreadPoolExecutor, ForkJoin to write concurrent applications in a safer and more performant way compared to traditional locking approaches.

Twitter processes over 500 million tweets per day and more than 2 billion search queries per day. The company uses a search architecture based on Lucene with custom extensions. This includes an in-memory real-time index optimized for concurrency without locks, and a schema-based document factory. Future work includes support for parallel index segments and additional Lucene features.

The document discusses modern Java concurrency and provides examples of how to write concurrent code safely and take advantage of modern hardware. It introduces key concepts like the java.util.concurrent package, locks, conditions, concurrent data structures, executors and fork/join. Examples are provided for using constructs like CountDownLatch, LinkedBlockingQueue, thread pools and fork/join tasks. The overall message is that modern Java concurrency allows safer and faster concurrent programming compared to traditional approaches.

This document discusses concurrency and parallelism in Ruby. It defines concurrency as performing two operations in tandem, while parallelism refers to performing two operations literally at the same time using multiple cores. The document examines traditional approaches to concurrency like threads and locks in Ruby and their limitations. It advocates for adopting models from other languages like actors and software transactional memory that can provide safer concurrency through message passing and transactions rather than shared mutable state and locks. The document reviews several Ruby libraries that implement actors and proposes areas for further improvement in Ruby's core support for concurrent programming.

A short introduction to the more advanced python and programming in general. Intended for users that has already learned the basic coding skills but want to have a rapid tour of more in-depth capacities offered by Python and some general programming background. Execrices are available at: https://github.com/chiffa/Intermediate_Python_programming

Ruby is a wonderful language for rapid development, it is easy to learn, we have wonderful frameworks, an active and dynamic community. But when it comes to concurrency Ruby is plagued with problems, controversies and urban legends. A lot of people would know about green threads in Ruby, GIL and its inherent limitations. But that it only one part of the big picture. Ruby offers much more than threads to helps us with concurrency. This presentation explores other options of writing highly concurrent applications in Ruby and options available in it. We cover topics ranging from Actor like message passing concurrency in Ruby, dataflow concurrency of how we can coordinate across different threads, Event driven methods, coroutine based concurrency which never blocks ;) and finally Software Transactional Memory. We look at lots of code, some serious looking yet colorful performance graphs comparisons, and conditions at which each of these forms are concurrency are effective and ineffective.

Ruby is a wonderful language for rapid development, it is easy to learn, we have wonderful frameworks, an active and dynamic community. But when it comes to concurrency Ruby is plagued with problems, controversies and urban legends. A lot of people would know about green threads in Ruby, GIL and its inherent limitations. But that it only one part of the big picture. Ruby offers much more than threads to helps us with concurrency. This presentation explores other options of writing highly concurrent applications in Ruby and options available in it. We cover topics ranging from Actor like message passing concurrency in Ruby, dataflow concurrency of how we can coordinate across different threads, Event driven methods, coroutine based concurrency which never blocks ;) and finally Software Transactional Memory. We look at lots of code, some serious looking yet colorful performance graphs comparisons, and conditions at which each of these forms are concurrency are effective and ineffective.

This document provides an introduction to Jupyter Notebook and Azure Machine Learning Studio. It discusses popular programming languages like Python, R, and Julia that can be used with these tools. It also summarizes key features of Jupyter Notebook like code cells, kernels, and cloud deployment. Examples are given of using Python and R with Azure ML to fetch and transform data in Jupyter notebooks.

This document provides an introduction to Jupyter Notebook and Azure Machine Learning Studio. It discusses popular programming languages like Python, R, and Julia that can be used with these tools. It also summarizes key features of Jupyter Notebook like code cells, kernels, and cloud deployment. Demo code examples are shown for integrating Python and R with Azure ML to fetch and transform data.

More information, visit: http://www.godatadriven.com/accelerator.html Data scientists aren’t a nice-to-have anymore, they are a must-have. Businesses of all sizes are scooping up this new breed of engineering professional. But how do you find the right one for your business? The Data Science Accelerator Program is a one year program, delivered in Amsterdam by world-class industry practitioners. It provides your aspiring data scientists with intensive on- and off-site instruction, access to an extensive network of speakers and mentors and coaching. The Data Science Accelerator Program helps you assess and radically develop the skills of your data science staff or recruits. Our goal is to deliver you excellent data scientists that help you become a data driven enterprise. The right tools We teach your organisation the proven data science tools. The right hands We are trusted by many industry leading partners. The right experience We've done big data and data science at many clients, we know what the real world is like. The right experts We have a world class selection of lecturers that you will be working with. Vincent D. Warmerdam Jonathan Samoocha Ivo Everts Rogier van der Geer Ron van Weverwijk Giovanni Lanzani The right curriculum We meet twice a month. Once for a lecture, once for a hackathon. Lectures The RStudio stack. The art of simulation. The iPython stack. Linear modelling. Operations research. Nonlinear modelling. Clustering & ensemble methods. Natural language processing. Time series. Visualisation. Scaling to big data. Advanced topics. Hackathons Scrape and mine the internet. Solving multiarmed bandit problems. Webdev with flask and pandas as a backend. Build an automation script for linear models. Build a heuristic tsp solver. Code review your automation for nonlinear models. Build a method that outperforms random forests. Build a markov chain to generate song lyrics. Predict an optimal portfolio for the stock market. Create an interactive d3 app with backend. Start up a spark cluster with large s3 data. You pick! Interested? Ping us here. signal@godatadriven.com

Blocks is a cool concept and is very much needed for performance improvements and responsiveness. GCD helps run blocks effortlessly by scheduling on a desired queue, priority and lots more.

Talk on how to make codebases unmaintainable and a nightmare, increasing complexity and stumbling towards the eventually inevitable rewrite

The document discusses OpenCL for accelerating FPGA designs. It provides an overview of technology trends favoring parallelism and programmability. OpenCL is presented as a solution to bring FPGA design closer to software development by providing a standard programming model and faster compilation. The document describes how OpenCL maps to FPGAs by compiling kernels to hardware pipelines and discusses examples accelerated using OpenCL on FPGAs, including AES encryption, option pricing, document filtering, and video compression.

The ability of a system to respond gracefully to an unexpected hardware or software failure. There are many levels of fault tolerance, the lowest being the ability to continue operation in the event of a power failure. Many fault-tolerant computer systems mirror all operations -- that is, every operation is performed on two or more duplicate systems, so if one fails the other can take over. In most cases it could be achieved by redundancy in application design and set of patterns and approaches to software design.

This document discusses concurrency and parallelism techniques in Unreal Engine 4 (UE4). It covers synchronization primitives like atomics, locking, signaling, and waiting. It also discusses high level constructs like thread-safe containers and helpers. For parallelization, it discusses threading using runnables, task graphs, processes, and messaging. The goal is to provide tips for programming UE4 to take advantage of multiple CPU cores.

Structured exception handling and defensive programming are the two pillars of robust software. Both pillars fail however when it comes to handling internal faults, those that normally originate in software defects rather than in any external factors. In this webinar, Zoran Horvat demonstrates advanced defensive coding techniques that can bring the quality of your code to an entirely new level. Watch the webinar and learn: When throwing an exception is the right thing to do Why exceptions and defensive coding cannot be applied to recover from defects How to handle situations when internal software defect is causing the fault How to treat fault detection as an orthogonal concern to normal operation The webinar recording can be found here: http://www.postsharp.net/blog/post/webinar-recording-defensive-programming

Modern business applications rely heavily on rich domain classes, which in turn rely heavily on polymorphic execution, code reuse and similar concepts. How can we extend rich domain classes to support complex requirements? In this presentation, Zoran Horvat will show why an object composition approach is favored over class inheritance when it comes to code reuse and polymorphism. The presentation covers: How class inheritance can lead to combinatorial explosion of classes What the limitations of object composition are What design patterns help consume composed objects Techniques for creating rich features on composed objects Watch the webinar recording here: http://www.postsharp.net/blog/post/webinar-recording-object-composition

Starting with the premise that "Performance is a Feature", Matt Warren will show you how to measure, what to measure and how to get the best performance from your .NET code. We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed! The presentation covers: Why we should care about performance Pitfalls to avoid when measuring performance How the .NET Garbage Collector can hurt performance Real-world performance lessons from open-source code The webinar recording can be found here: http://www.postsharp.net/blog/post/webinar-recording-performance-is-a-feature

How do you avoid the dreaded "this is not what we asked for" and ensure customer satisfaction when building a new system? In this webinar, Dino Esposito demonstrates a top-down methodology, sometimes mistaken for plain common sense and often boldly ignored, called UX-Driven Design (UXDD). UXDD means coming to a visual agreement with customers by using wireframing tools to iterate on sketches of the new system before building it. Then, rather than building the system from the data model, you proceed in a top-down fashion instead. The resulting system may be slow or even inefficient but it will never be the “wrong” system! In addition, UXDD leads to clarity on a few of today’s most popular patterns that are sometimes difficult to understand like CQRS and Event Sourcing. The presentation covers: An introduction to Wireframing tools Proven ways to save on post-first deployment costs Insights into better customer relationships Better focus on development without 'analysis paralysis' You can watch the webinar recording here: http://www.postsharp.net/blog/post/webinar-recording-ux-driven-design

Localization is crucial for reaching out to a global audience, however, it’s often an afterthought for most developers and non-trivial to implement. Traditionally, game developers have outsourced this task due to its time consuming nature. But it doesn’t have to be this way. Yan Cui will show you a simple technique his team used at GameSys which allowed them to localize an entire story-driven, episodic MMORPG (with over 5000 items and 1500 quests) in under an hour of work and 50 lines of code, with the help of PostSharp.