This talk is a look into some of the surprising performance cases in Java -- with the goal of illustrating a few simple truths about the nature of compilers.
JVM Mechanics: Understanding the JIT's TricksDoug Hawkins
In this talk, we'll walkthrough how the JIT optimizes a piece Java code step-by-step. In doing so, you'll learn some of the amazing feats of optimization that JVMs can perform, but also some surprisingly simple things that prevent your code from running fast.
This talk is a look into some of the surprising performance cases in Java -- with the goal of illustrating a few simple truths about the nature of compilers.
JVM Mechanics: Understanding the JIT's TricksDoug Hawkins
In this talk, we'll walkthrough how the JIT optimizes a piece Java code step-by-step. In doing so, you'll learn some of the amazing feats of optimization that JVMs can perform, but also some surprisingly simple things that prevent your code from running fast.
An overview of the inner-workings of OpenJDK - with emphasis on...
- what triggers the just-in-time compiler (JIT)
- types of speculative optimizations performed by the JIT
- aspects of the Java language & ecosystem that make ahead-of-time (AOT) compilation challenging
서버 개발자가 바라 본 Functional Reactive Programming with RxJava - SpringCamp2015NAVER / MusicPlatform
youtube : https://youtu.be/E_Bgv9upahI
비동기 이벤트 기반의 라이브러리로만 생각 했던 RxJava가 지금 이 시대 프로그래머에게 닥쳐 올 커다란 메시지라는 사실을 알게 된 지금. 현장에서 직접 느낀 RxJava의 본질인 Function Reactive Programming(FRP)에 대해 우리가 잘 아는 Java 이야기로 풀어 보고 ReactiveX(RxJava) 개발을 위한 서버 환경에 대한 이해와 SpringFramework, Netty에서의 RxJava를 어떻게 이용 하고 개발 했는지 공유 하고자 합니다.
Being functional in PHP (PHPDay Italy 2016)David de Boer
Functional programming, though far from new, has gained much traction recently. Functional programming characteristics have started to appear in the PHP world, too. Microframeworks such as Silex and Slim, middleware architectures such as Stack and even standards such as PSR-7 rely on concepts such as lambdas, referential transparency and immutability, all of which come from functional programming. I’ll give you a crash course in Erlang, a pragmatic functional language to make you feel familiar with the functional paradigm. By comparing code samples between Erlang and PHP, you’ll find out how you can employ functional programming in your PHP applications where appropriate. You’ll see that functional programming is nothing to be scared of. On the contrary, understanding its concepts broadens your programming horizon and provides you with valuable solutions to your problems.
Rainer Grimm, “Functional Programming in C++11”Platonov Sergey
C++ это мультипарадигменный язык, поэтому программист сам может выбирать и совмещать структурный, объектно-ориентированный, обобщенный и функциональный подходы. Функциональный аспект C++ особенно расширился стандартом C++11: лямбда-функции, variadic templates, std::function, std::bind. (язык доклада: английский).
Characteristics of Java and basic programming constructs like Data types, Variables, Operators, Control Statements, Arrays are discussed with relevant examples
EdSketch: Execution-Driven Sketching for JavaLisa Hua
Sketching is a relatively recent approach to program synthesis, which has shown much promise. The key idea in sketching is to allow users to write partial programs that have “holes” and provide test harnesses or reference implementations, and let synthesis tools create program fragments that the holes such that the resulting complete program has the desired functionality. Traditional solutions to the sketching problem perform a translation to SAT and employ CEGIS. While e ective for a range of programs, when applied to real applications, such translation-based approaches have a key limitation: they require either translating all relevant libraries that are invoked directly or indirectly by the given sketch – which can lead to impractical SAT problems – or creating models of those libraries – which can require much manual effort.
is paper introduces execution-driven sketching, a novel approach for synthesis of Java programs using a backtracking search that is commonly employed in so ware model checkers. e key novelty of our work is to introduce effective pruning strategies to effciently explore the actual program behaviors in presence of libraries and to provide a practical solution to sketching small parts of real-world applications, which may use complex constructs of modern languages, such as reflection or native calls. Our tool EdSketch embodies our approach in two forms: a stateful search based on the Java PathFinder model checker; and a stateless search based on re-execution inspired by the VeriSoft model checker. Experimental results show that EdSketch’s performance compares well with the well-known SAT-based Sketch system for a range of small but complex programs, and moreover, that EdSketch can complete some sketches that require handling complex constructs.
An overview of the inner-workings of OpenJDK - with emphasis on...
- what triggers the just-in-time compiler (JIT)
- types of speculative optimizations performed by the JIT
- aspects of the Java language & ecosystem that make ahead-of-time (AOT) compilation challenging
서버 개발자가 바라 본 Functional Reactive Programming with RxJava - SpringCamp2015NAVER / MusicPlatform
youtube : https://youtu.be/E_Bgv9upahI
비동기 이벤트 기반의 라이브러리로만 생각 했던 RxJava가 지금 이 시대 프로그래머에게 닥쳐 올 커다란 메시지라는 사실을 알게 된 지금. 현장에서 직접 느낀 RxJava의 본질인 Function Reactive Programming(FRP)에 대해 우리가 잘 아는 Java 이야기로 풀어 보고 ReactiveX(RxJava) 개발을 위한 서버 환경에 대한 이해와 SpringFramework, Netty에서의 RxJava를 어떻게 이용 하고 개발 했는지 공유 하고자 합니다.
Being functional in PHP (PHPDay Italy 2016)David de Boer
Functional programming, though far from new, has gained much traction recently. Functional programming characteristics have started to appear in the PHP world, too. Microframeworks such as Silex and Slim, middleware architectures such as Stack and even standards such as PSR-7 rely on concepts such as lambdas, referential transparency and immutability, all of which come from functional programming. I’ll give you a crash course in Erlang, a pragmatic functional language to make you feel familiar with the functional paradigm. By comparing code samples between Erlang and PHP, you’ll find out how you can employ functional programming in your PHP applications where appropriate. You’ll see that functional programming is nothing to be scared of. On the contrary, understanding its concepts broadens your programming horizon and provides you with valuable solutions to your problems.
Rainer Grimm, “Functional Programming in C++11”Platonov Sergey
C++ это мультипарадигменный язык, поэтому программист сам может выбирать и совмещать структурный, объектно-ориентированный, обобщенный и функциональный подходы. Функциональный аспект C++ особенно расширился стандартом C++11: лямбда-функции, variadic templates, std::function, std::bind. (язык доклада: английский).
Characteristics of Java and basic programming constructs like Data types, Variables, Operators, Control Statements, Arrays are discussed with relevant examples
EdSketch: Execution-Driven Sketching for JavaLisa Hua
Sketching is a relatively recent approach to program synthesis, which has shown much promise. The key idea in sketching is to allow users to write partial programs that have “holes” and provide test harnesses or reference implementations, and let synthesis tools create program fragments that the holes such that the resulting complete program has the desired functionality. Traditional solutions to the sketching problem perform a translation to SAT and employ CEGIS. While e ective for a range of programs, when applied to real applications, such translation-based approaches have a key limitation: they require either translating all relevant libraries that are invoked directly or indirectly by the given sketch – which can lead to impractical SAT problems – or creating models of those libraries – which can require much manual effort.
is paper introduces execution-driven sketching, a novel approach for synthesis of Java programs using a backtracking search that is commonly employed in so ware model checkers. e key novelty of our work is to introduce effective pruning strategies to effciently explore the actual program behaviors in presence of libraries and to provide a practical solution to sketching small parts of real-world applications, which may use complex constructs of modern languages, such as reflection or native calls. Our tool EdSketch embodies our approach in two forms: a stateful search based on the Java PathFinder model checker; and a stateless search based on re-execution inspired by the VeriSoft model checker. Experimental results show that EdSketch’s performance compares well with the well-known SAT-based Sketch system for a range of small but complex programs, and moreover, that EdSketch can complete some sketches that require handling complex constructs.
Basic concept of Deep Learning with explaining its structure and backpropagation method and understanding autograd in PyTorch. (+ Data parallism in PyTorch)
Current Score – 0 Due Wednesday, November 19 2014 0400 .docxfaithxdunce63732
Current Score : – / 0 Due : Wednesday, November 19 2014 04:00 PM CST
1. –/0 pointsSEssCalcET2 13.2.002.
Evaluate the line integral, where C is the given curve.
2. –/0 pointsSEssCalcET2 13.2.003.MI.SA.
This question has several parts that must be completed sequentially. If you skip a part of the
question, you will not receive any points for the skipped part, and you will not be able to come
back to the skipped part.
Tutorial Exercise
Evaluate the line integral, where C is the given curve.
is the right half of the circle x2 + y2 = 25 oriented counterclockwise
3. –/0 pointsSEssCalcET2 13.2.007.
Evaluate the line integral, where C is the given curve.
C consists of line segments from (0, 0) to (5, 1) and from (5, 1)
to (6, 0)
Review Problems for Test #2 (Homework)
Rustom Hamouri
Math 344, section 11795, Fall 2014
Instructor: Buma Fridman
WebAssign
xy ds, C: x = t2, y = 2t, 0 ≤ t ≤ 1
C
xy4 ds, C
C
(x + 5y) dx + x2 dy,
C
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
4. –/0 pointsSEssCalcET2 13.2.010.
Evaluate the line integral, where C is the given curve.
is the line segment from
5. –/0 pointsSEssCalcET2 13.2.020.
Evaluate the line integral where C is given by the vector function r(t).
6. –/0 pointsSEssCalcET2 13.3.004.
Determine whether or not F is a conservative vector field. If it is, find a function f such that F =
∇f. If it is not, enter NONE.
f(x, y) = + K
xyz2 ds, C
C
(−2, 6, 0) to (0, 7, 1)
F · dr,
C
F(x, y, z) = (x + y)i + (y − z)j + z3k
r(t) = t2 i + t3 j + t2 k, 0 ≤ t ≤ 1
F(x, y) = ex sin y i + ex cos y j
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
javascript:open_bc_enhanced('watch_it_player', '/bc_enhanced/sesscalcet2_w_player/scalcet6_16_03_005.html', 0)
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
7. –/0 pointsSEssCalcET2 13.3.005.
Determine whether or not F is a conservative vector field. If it is, find a function f such that F =
∇f. If it is not, enter NONE.
f(x, y) = + K
8. –/0 pointsSEssCalcET2 13.3.011.
Consider F and C below.
(a) Find a function f such that F = ∇f.
(b) Use part (a) to evaluate along the given curve C.
F(x, y) = ex cos y i + ex sin y j
F(x, y) = 4xy2 i + 4x2y j
C: r(t) = t + sin πt, t + cos πt , 0 ≤ t ≤ 11
2
1
2
f(x, y) =
∇f · dr
C
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
javascript:open_bc_enhanced('watch_it_player', '/bc_enhanced/sesscalcet2_w_player/scalcet6_16_03_013.html', 0)
javascript:open_bc_enhanced('chat_about_it', '273494~~~396311')
9. –/0 pointsSEssCalcET2 13.3.015.
Consider F and C below.
(a) Find a function f such that F = ∇f.
(b) Use part (a) to evaluate along the given curve C.
10.–/0 pointsSEssCalcET2 13.3.020.
Find the wor.
The slide of the talk in http://www.meetup.com/R-Users-Sydney/events/223867196/
There is a web version here: http://wush978.github.io/FeatureHashing/index.html
This tutor introduces the basic idea of machine learning with a very simple example. Machine learning teaches machines (and me too) to learn to carry out tasks and concepts by themselves. It is that simple, so here is an overview:
http://www.softwareschule.ch/examples/machinelearning.jpg
Processing large-scale graphs with Google(TM) Pregel by MICHAEL HACKSTEIN at...Big Data Spain
This talk will give a good overview over the complex architecture of the Pregel framework and will give some insights where there are potential bottlenecks when writing a Pregel algorithm.
⭐⭐⭐⭐⭐ Device Free Indoor Localization in the 28 GHz band based on machine lea...Victor Asanza
By exploiting the received power change in a communication link produced by the presence of a human body in an otherwise empty room, this work evaluates indoor free device localization methods in the 28 GHz band using machine learning techniques. For this objective, a database is built using results from ray tracing simulations of a system comprised of 4 receivers and up to 2 transmitters, while a person is standing within the room. Transmitters are equipped with uniform linear arrays that switch their main beams sequentially at 21 angles, whereas the receivers operate with omnidirectional antennas. Statistical localization error reduction of at least 16% over a global-based classification technique can be obtained through the combination of two independent classifiers using one transmitter and a reduction of at least 19% for 2 transmitters. An additional improvement is achieved by combining each independent classifier with a regression algorithm. Results also suggest that the number of examples per class and size of the blocks (strips) in which the study area is partitioned play a role in the localization error.
Mobility insights at Swisscom - Understanding collective mobility in SwitzerlandFrançois Garillot
Swisscom is the leading mobile-service provider in Switzerland, with a market share high enough to enable us to model and understand the collective mobility in every area of the country. To accomplish that, we built an urban planning tool that helps cities better manage their infrastructure based on data-based insights, produced with Apache Spark, YARN, Kafka and a good dose of machine learning. In this talk, we will explain how building such a tool involves mining a massive amount of raw data (1.5E9 records/day) to extract fine-grained mobility features from raw network traces. These features are obtained using different machine learning algorithms. For example, we built an algorithm that segments a trajectory into mobile and static periods and trained classifiers that enable us to distinguish between different means of transport. As we sketch the different algorithmic components, we will present our approach to continuously run and test them, which involves complex pipelines managed with Oozie and fuelled with ground truth data. Finally, we will delve into the streaming part of our analytics and see how network events allow Swisscom to understand the characteristics of the flow of people on roads and paths of interest. This requires making a link between network coverage information and geographical positioning in the space of milliseconds and using Spark streaming with libraries that were originally designed for batch processing. We will conclude on the advantages and pitfalls of Spark involved in running this kind of pipeline on a multi-tenant cluster. Audiences should come back from this talk with an overall picture of the use of Apache Spark and related components of its ecosystem in the field of trajectory mining.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
