These are the slides for my Code One 2018 talk on profiling and diagnostics on the JVM. The talk goes through various serviceability technologies built into the JVM, but with a focus on the production time use cases.
JVM Mechanics: When Does the JVM JIT & Deoptimize?Doug Hawkins
HotSpot promises to do the "right" thing for us by identifying our hot code and compiling "just-in-time", but how does HotSpot make those decisions?
This presentation aims to detail how HotSpot makes those decisions and how it corrects its mistakes through a series of demos that you run yourself.
Java Performance: Speedup your application with hardware countersSergey Kuksenko
A modern CPU looks under the cover to understand what performance. What about hardware for Java application performance? Let's understand Performance Monitoring Unit works, Hardware Counters & using them to speeding up Java apps.
Runtime Code Generation and Data Management for Heterogeneous Computing in JavaJuan Fumero
This document discusses runtime and data management techniques for heterogeneous computing in Java. It presents an approach that uses three levels of abstraction: parallel skeletons API based on functional programming, a high-level optimizing library that rewrites operations to target specific hardware, and OpenCL code generation and runtime with data management for heterogeneous architectures. It describes how the runtime performs type inference, IR generation, optimizations, and kernel generation to compile Java code into OpenCL kernels. It also discusses how custom array types are used to reduce data marshaling overhead between the Java and OpenCL runtimes.
This document outlines the motivation and design of Java 8 streams. Streams were introduced to simplify working with collections by allowing operations to be pipelined in a declarative style. The key aspects are:
- Streams represent a sequence of values and operations are deferred
- Common patterns of filtering, mapping, sorting collections can be expressed concisely in a stream pipeline
- Sources include collections, arrays, generators. Intermediate operations transform the stream, while a terminal operation produces the result.
Nowadays, CPU microarchitecture is concealed from developers by compilers, VMs, etc.
Do Java developers need to know microarchitecture details of modern processors?
Or, does it like to learn quantum mechanics for cooking?
Are Java developers safe from leaking low-level microarchitecture details into high level application performance behaviour?
We will try to answer these questions by analyzing several Java examples.
With a new release of Java every six-months, we are getting new features at a faster rate than ever before. In this session, we'll review all the main additions from JDK 9 to JDK 14.
Speculative Execution of Parallel Programs with Precise Exception Semantics ...Akihiro Hayashi
Akihiro Hayashi, Max Grossman, Jisheng Zhao, Jun Shirako, Vivek Sarkar. The 26th International Workshop on Languages and Compilers for Parallel Computing (LCPC2013), September 25-27, 2013 Qualcomm Research Silicon Valley, Santa Clara, CA (co-located with CnC-2013).
There are now several providers of builds of OpenJDK. In this presentation, we look at what aspects of a JDK distribution you should consider when making a choice.
Nowadays, CPU microarchitecture is concealed from developers by compilers, VMs, etc. Do Java developers need to know microarchitecture details of modern processors? Or, does it like to learn quantum mechanics for cooking? Are Java developers safe from leaking low-level microarchitecture details into high level application performance behaviour? We will try to answer these questions by analyzing several Java example.
This document describes a portlet for job management that allows submitting and tracking jobs on distributed computing infrastructures. It discusses the portlet lifecycle and interfaces, how it handles different modes like view, edit, and help. It also explains how the portlet exchanges parameters between Java and JSP pages using request attributes and parameters. Finally, it provides details of an example hostname portlet implementation, covering initialization, action/view handling, and job submission parameters.
Bridge TensorFlow to run on Intel nGraph backends (v0.4)Mr. Vengineer
This document discusses bridging TensorFlow to run on Intel nGraph backends. It summarizes various optimization passes used in the nGraph-TensorFlow integration, including passes to liberate nodes from placement constraints, confirm placement, cluster the graph, and encapsulate clusters. Key points:
- NGraphLiberatePass and NGraphConfirmPass run during the PRE_PLACEMENT phase to handle nGraph placement
- NGraphClusterPass runs during POST_REWRITE_FOR_EXEC to cluster the graph into subgraphs, similar to XLA partitioning
- NGraphEncapsulatePass encapsulates clusters into NGraphEncapsulateOp nodes, analogous to XLA's use of _XlaLaunchOp
-
This document discusses building a virtual platform for the OpenRISC architecture using SystemC and transaction-level modeling. It covers setting up the toolchain, writing test programs, and simulating the platform using event-driven or cycle-accurate simulation with Icarus Verilog or the Vorpsoc simulator. The virtual platform allows fast development and debugging of OpenRISC code without requiring physical hardware.
This document discusses event tracing using VampirTrace and Vampir. It provides an overview of event tracing, including instrumentation, run-time measurement, and visualization. Event tracing involves instrumenting code to record events, running the instrumented code to generate trace files, and using tools like Vampir to analyze and visualize the trace files.
TensorFlow XLAの中では、
XLA Client を Pythonで利用できるようになっています。
また、2018年2月に開催されたSysMLの論文(JAX@Google)についても追記しました。
In TensorFlow XLA,
XLA Client is now available in Python.
Also added about SysML's paper (JAX @ Google) held in February 2018.
A Future for R: Parallel and Distributed Processing in R for Everyoneinside-BigData.com
In this deck from the 2018 European R Users Meeting, Henrik Bengtsson from the University of California San Francisco presents: A Future for R: Parallel and Distributed Processing in R for Everyone.
In this video from the European R Users Meeting, Henrik Bengtsson from the University of California San Francisco presents: A Future for R: Parallel and Distributed Processing in R for Everyone.
"The future package is a powerful and elegant cross-platform framework for orchestrating asynchronous computations in R. It's ideal for working with computations that take a long time to complete; that would benefit from using distributed, parallel frameworks to make them complete faster; and that you'd rather not have locking up your interactive R session."
Watch the video: https://wp.me/p3RLHQ-jJ4
Learn more: https://blog.revolutionanalytics.com/2019/01/future-package.html
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Despite all of the recent interest, concurrency in standard C++ is still barely in its infancy. This talk uses the primitives supplied by C++14 to build a simple, reference, implementation of a task system. The goal is to learn to write software that doesn’t wait.
Improving Java performance at JBCNConf 2015Raimon Ràfols
The document discusses ways to improve Java performance. It begins by explaining how the Java compiler (javac) does not optimize code and leaves all optimizations to the Java Virtual Machine (JVM). It then provides examples of how the C compiler can optimize simple code better than javac. The document also discusses language features like autoboxing that add overhead and provides recommendations to improve loops, string concatenation, and method calls. Finally, it discusses tools for disassembling and profiling Java bytecode.
Pythonによるカスタム可能な高位設計技術 (Design Solution Forum 2016@新横浜)Shinya Takamaeda-Y
Veriloggen is a Python library that allows users to generate Verilog HDL code from Python. It provides objects and methods to define RTL modules in Python, including module inputs/outputs, registers, assignments, always blocks, etc. When the Veriloggen object is passed to the to_verilog() method, it traverses the object and generates equivalent Verilog HDL code. This allows rapid prototyping of RTL designs in Python without having to write low-level Verilog code directly.
Improving Android Performance at Mobiconf 2014Raimon Ràfols
The document provides an overview of improving Android performance by discussing Java virtual machines, examples of code optimizations and anti-patterns, and tools for measuring and optimizing performance. It covers topics like avoiding autoboxing when possible, using arrays over lists for loops, caching array lengths, and using StringBuilder instead of string concatenation. Tooling discussed includes using a disassembler to view bytecode, code obfuscation with Proguard, and best practices for performance measurement.
Intel IPP Samples for Windows - error correctionPVS-Studio
This is one of my posts on how PVS-Studio makes programs safer. That is where and what types of errors it detects. This time it is samples demonstrating handling of the IPP 7.0 library (Intel Performance Primitives Library) we are going to examine.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2015-embedded-vision-summit-opencv
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Gary Bradski, President and CEO of the OpenCV Foundation, presents the "OpenCV Open Source Computer Vision Library: Latest Developments" tutorial at the May 2015 Embedded Vision Summit.
OpenCV is an enormously popular open source computer vision library, with over 9 million downloads. Originally used mainly for research and prototyping, in recent years OpenCV has increasingly been used in deployed products on a wide range of platforms from cloud to mobile.
The latest version, OpenCV 3.0 is currently in beta, and is a major overhaul, bringing OpenCV up to modern C++ standards and incorporating expanded support for 3D vision. The new release also introduces a modular “contrib” facility that enables independently developed modules to be quickly integrated with OpenCV as needed, providing a flexible mechanism to allow developers to experiment with new techniques before they are officially integrated into the library.
In this talk, Gary Bradski, head of the OpenCV Foundation, provides an insider’s perspective on the new version of OpenCV and how developers can utilize it to maximum advantage for vision research, prototyping, and product development.
This document discusses code metrics and refactoring. It begins with an introduction to metrics and how they can be used to evaluate code quality by measuring attributes like complexity, coupling, and cohesion. Several specific metrics are discussed like CBO, CC, and LCOM. The document then discusses refactoring and how metrics can help identify areas of code that need improvement. Refactoring is presented as an important process to prevent software decay and allow code to be improved over time through iterative testing and modification.
This document provides an overview of a tutorial on VHDL synthesis, place and route for FPGA and ASIC technologies. The tutorial covers VHDL coding styles, FPGA synthesis, place and route, a demo of FPGA synthesis and place and route, ASIC synthesis, place and route, and a demo of ASIC synthesis and place and route. The outline indicates it will also cover conclusions and further reading.
This document provides an introduction to Verilog, a hardware description language (HDL). It describes the main purposes of HDLs as allowing designers to describe circuits at both the algorithmic and gate levels, enabling simulation and synthesis. The document then discusses some Verilog basics, including modules as building blocks, ports, parameters, variables, instantiation, and structural vs procedural code. It provides examples of module declarations and typical module components.
The document describes the design and simulation of half adders, full adders, multiplexers, and demultiplexers using VHDL. It includes block diagrams, truth tables, and VHDL code for implementing these circuits using dataflow, behavioral, and structural modeling in Xilinx ISE. Code examples and output waveforms are provided for half adders, full adders, 4-to-1 multiplexers, and 1-to-4 demultiplexers. The aim is to learn how to design and simulate basic digital circuits using different VHDL modeling approaches.
This document summarizes key features introduced in Java SE 5.0 (Tiger) including generics, autoboxing/unboxing, enhanced for loops, type-safe enums, varargs, static imports, and annotations. It also discusses performance enhancements in the virtual machine as well as new concurrency utilities like Executors and ScheduledExecutorService that make multi-threaded programming easier and more robust.
This slides cover overview of Project Helidon (Java libraries for creating microservices), implementation tips, and running applications on custom JRE. This slides are in Japanese.
Nowadays, CPU microarchitecture is concealed from developers by compilers, VMs, etc. Do Java developers need to know microarchitecture details of modern processors? Or, does it like to learn quantum mechanics for cooking? Are Java developers safe from leaking low-level microarchitecture details into high level application performance behaviour? We will try to answer these questions by analyzing several Java example.
This document describes a portlet for job management that allows submitting and tracking jobs on distributed computing infrastructures. It discusses the portlet lifecycle and interfaces, how it handles different modes like view, edit, and help. It also explains how the portlet exchanges parameters between Java and JSP pages using request attributes and parameters. Finally, it provides details of an example hostname portlet implementation, covering initialization, action/view handling, and job submission parameters.
Bridge TensorFlow to run on Intel nGraph backends (v0.4)Mr. Vengineer
This document discusses bridging TensorFlow to run on Intel nGraph backends. It summarizes various optimization passes used in the nGraph-TensorFlow integration, including passes to liberate nodes from placement constraints, confirm placement, cluster the graph, and encapsulate clusters. Key points:
- NGraphLiberatePass and NGraphConfirmPass run during the PRE_PLACEMENT phase to handle nGraph placement
- NGraphClusterPass runs during POST_REWRITE_FOR_EXEC to cluster the graph into subgraphs, similar to XLA partitioning
- NGraphEncapsulatePass encapsulates clusters into NGraphEncapsulateOp nodes, analogous to XLA's use of _XlaLaunchOp
-
This document discusses building a virtual platform for the OpenRISC architecture using SystemC and transaction-level modeling. It covers setting up the toolchain, writing test programs, and simulating the platform using event-driven or cycle-accurate simulation with Icarus Verilog or the Vorpsoc simulator. The virtual platform allows fast development and debugging of OpenRISC code without requiring physical hardware.
This document discusses event tracing using VampirTrace and Vampir. It provides an overview of event tracing, including instrumentation, run-time measurement, and visualization. Event tracing involves instrumenting code to record events, running the instrumented code to generate trace files, and using tools like Vampir to analyze and visualize the trace files.
TensorFlow XLAの中では、
XLA Client を Pythonで利用できるようになっています。
また、2018年2月に開催されたSysMLの論文(JAX@Google)についても追記しました。
In TensorFlow XLA,
XLA Client is now available in Python.
Also added about SysML's paper (JAX @ Google) held in February 2018.
A Future for R: Parallel and Distributed Processing in R for Everyoneinside-BigData.com
In this deck from the 2018 European R Users Meeting, Henrik Bengtsson from the University of California San Francisco presents: A Future for R: Parallel and Distributed Processing in R for Everyone.
In this video from the European R Users Meeting, Henrik Bengtsson from the University of California San Francisco presents: A Future for R: Parallel and Distributed Processing in R for Everyone.
"The future package is a powerful and elegant cross-platform framework for orchestrating asynchronous computations in R. It's ideal for working with computations that take a long time to complete; that would benefit from using distributed, parallel frameworks to make them complete faster; and that you'd rather not have locking up your interactive R session."
Watch the video: https://wp.me/p3RLHQ-jJ4
Learn more: https://blog.revolutionanalytics.com/2019/01/future-package.html
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Despite all of the recent interest, concurrency in standard C++ is still barely in its infancy. This talk uses the primitives supplied by C++14 to build a simple, reference, implementation of a task system. The goal is to learn to write software that doesn’t wait.
Improving Java performance at JBCNConf 2015Raimon Ràfols
The document discusses ways to improve Java performance. It begins by explaining how the Java compiler (javac) does not optimize code and leaves all optimizations to the Java Virtual Machine (JVM). It then provides examples of how the C compiler can optimize simple code better than javac. The document also discusses language features like autoboxing that add overhead and provides recommendations to improve loops, string concatenation, and method calls. Finally, it discusses tools for disassembling and profiling Java bytecode.
Pythonによるカスタム可能な高位設計技術 (Design Solution Forum 2016@新横浜)Shinya Takamaeda-Y
Veriloggen is a Python library that allows users to generate Verilog HDL code from Python. It provides objects and methods to define RTL modules in Python, including module inputs/outputs, registers, assignments, always blocks, etc. When the Veriloggen object is passed to the to_verilog() method, it traverses the object and generates equivalent Verilog HDL code. This allows rapid prototyping of RTL designs in Python without having to write low-level Verilog code directly.
Improving Android Performance at Mobiconf 2014Raimon Ràfols
The document provides an overview of improving Android performance by discussing Java virtual machines, examples of code optimizations and anti-patterns, and tools for measuring and optimizing performance. It covers topics like avoiding autoboxing when possible, using arrays over lists for loops, caching array lengths, and using StringBuilder instead of string concatenation. Tooling discussed includes using a disassembler to view bytecode, code obfuscation with Proguard, and best practices for performance measurement.
Intel IPP Samples for Windows - error correctionPVS-Studio
This is one of my posts on how PVS-Studio makes programs safer. That is where and what types of errors it detects. This time it is samples demonstrating handling of the IPP 7.0 library (Intel Performance Primitives Library) we are going to examine.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2015-embedded-vision-summit-opencv
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Gary Bradski, President and CEO of the OpenCV Foundation, presents the "OpenCV Open Source Computer Vision Library: Latest Developments" tutorial at the May 2015 Embedded Vision Summit.
OpenCV is an enormously popular open source computer vision library, with over 9 million downloads. Originally used mainly for research and prototyping, in recent years OpenCV has increasingly been used in deployed products on a wide range of platforms from cloud to mobile.
The latest version, OpenCV 3.0 is currently in beta, and is a major overhaul, bringing OpenCV up to modern C++ standards and incorporating expanded support for 3D vision. The new release also introduces a modular “contrib” facility that enables independently developed modules to be quickly integrated with OpenCV as needed, providing a flexible mechanism to allow developers to experiment with new techniques before they are officially integrated into the library.
In this talk, Gary Bradski, head of the OpenCV Foundation, provides an insider’s perspective on the new version of OpenCV and how developers can utilize it to maximum advantage for vision research, prototyping, and product development.
This document discusses code metrics and refactoring. It begins with an introduction to metrics and how they can be used to evaluate code quality by measuring attributes like complexity, coupling, and cohesion. Several specific metrics are discussed like CBO, CC, and LCOM. The document then discusses refactoring and how metrics can help identify areas of code that need improvement. Refactoring is presented as an important process to prevent software decay and allow code to be improved over time through iterative testing and modification.
This document provides an overview of a tutorial on VHDL synthesis, place and route for FPGA and ASIC technologies. The tutorial covers VHDL coding styles, FPGA synthesis, place and route, a demo of FPGA synthesis and place and route, ASIC synthesis, place and route, and a demo of ASIC synthesis and place and route. The outline indicates it will also cover conclusions and further reading.
This document provides an introduction to Verilog, a hardware description language (HDL). It describes the main purposes of HDLs as allowing designers to describe circuits at both the algorithmic and gate levels, enabling simulation and synthesis. The document then discusses some Verilog basics, including modules as building blocks, ports, parameters, variables, instantiation, and structural vs procedural code. It provides examples of module declarations and typical module components.
The document describes the design and simulation of half adders, full adders, multiplexers, and demultiplexers using VHDL. It includes block diagrams, truth tables, and VHDL code for implementing these circuits using dataflow, behavioral, and structural modeling in Xilinx ISE. Code examples and output waveforms are provided for half adders, full adders, 4-to-1 multiplexers, and 1-to-4 demultiplexers. The aim is to learn how to design and simulate basic digital circuits using different VHDL modeling approaches.
This document summarizes key features introduced in Java SE 5.0 (Tiger) including generics, autoboxing/unboxing, enhanced for loops, type-safe enums, varargs, static imports, and annotations. It also discusses performance enhancements in the virtual machine as well as new concurrency utilities like Executors and ScheduledExecutorService that make multi-threaded programming easier and more robust.
This slides cover overview of Project Helidon (Java libraries for creating microservices), implementation tips, and running applications on custom JRE. This slides are in Japanese.
These are the slides for the talk I did together with John Sullivan on how to use various open source technologies, like JFR and Open Tracing together to facilitate deep tracing of microservices written in Java. We also showed how these technologies are used in the Oracle Management Cloud APM solution.
Production Time Profiling Out of the BoxMarcus Hirt
The document introduces Java Mission Control (JMC), a tools suite for production monitoring and diagnostics of Java applications. It provides an overview of JMC's components including the JMX Console for real-time monitoring and the Java Flight Recorder for low-overhead profiling. The document demonstrates JMC's installation and how to use the JMX Console and Flight Recorder. It also discusses JMC's experimental plugins and roadmap for future versions.
Graal is a dynamic meta-circular research compiler for Java that is designed for extensibility and modularity. One of its main distinguishing elements is the handling of optimistic assumptions obtained via profiling feedback and the representation of deoptimization guards in the compiled code. Truffle is a self-optimizing runtime system on top of Graal that uses partial evaluation to derive compiled code from interpreters. Truffle is suitable for creating high-performance implementations for dynamic languages with only moderate effort. The presentation includes a description of the Truffle multi-language API and performance comparisons within the industry of current prototype Truffle language implementations (JavaScript, Ruby, and R). Both Graal and Truffle are open source and form themselves research platforms in the area of virtual machine and programming language implementation (http://openjdk.java.net/projects/graal/).
- The document summarizes key announcements and projects from JavaOne 2010, including Project Coin, Project Lambda, and Project Jigsaw which focus on language enhancements for productivity, closures, and modularity.
- It also discusses case studies from various companies on architectures using technologies like Spring, Hibernate, caching, and NoSQL databases to handle large-scale applications.
- Trends highlighted include focus on asynchronous and event-driven architectures, partitioning, and monitoring to handle thousands of servers and billions of requests per day.
This chapter discusses message-passing programming using MPI. It covers the message-passing model, how MPI programs execute, fundamental MPI functions, coding, compiling, running and benchmarking MPI programs. The document provides examples of coding a circuit satisfiability program in MPI using concepts like determining the number of processes, cyclic allocation of work, and reducing results across processes.
Netronome's half-day tutorial on host data plane acceleration at ACM SIGCOMM 2018 introduced attendees to models for host data plane acceleration and provided an in-depth understanding of SmartNIC deployment models at hyperscale cloud vendors and telecom service providers.
Presenter Bio
Jaco Joubert is a Software Engineer at Netronome focusing on P4 and its applications on the Netronome SmartNIC. He recently started investigating network acceleration for Deep Learning on distributed systems. Prior to Netronome he worked on mobile application development and was a researcher at Telkom SA focusing on the mobile core after completing his Masters Degree in Computer, Electronic Engineering in 2014.
The document discusses various techniques for testing large, distributed systems beyond traditional unit testing. It recommends embracing virtualization to simulate production environments and deploying applications and tests across multiple virtual machines. Various tools are presented to help with distributed, automated testing including Cactus for in-container testing, Selenium and jsUnit for browser testing, and SmartFrog as a framework for describing, deploying and managing distributed service components and tests. The document calls for a focus on system-level tests that simulate the full production environment and integrate testing across distributed systems.
Ingesting streaming data for analysis in apache ignite (stream sets theme)Tom Diederich
Apache Ignite provides a distributed platform for a wide variety of workloads, but often the issue is simply in getting data into the database in the first place. The wide variety of data sources and formats presents a challenge to any data engineer; in addition, 'data drift', the constant and inevitable mutation of the incoming data's structure and semantics, can break even the most well-engineered integration.
This session, aimed at data architects, data engineers and developers, will explore how we can use the open source StreamSets Data Collector to build robust data pipelines. Attendees will learn how to collect data from cloud platforms such as Amazon and Salesforce, devices, relational databases and other sources, continuously stream it to Ignite, and then use features such as Ignite's continuous queries to perform streaming analysis.
We'll start by covering the basics of reading files from disk, move on to relational databases, then look at more challenging sources such as APIs and message queues. You will learn how to:
* Build data pipelines to ingest a wide variety of data into Apache Ignite
* Anticipate and manage data drift to ensure that data keeps flowing
* Perform simple and complex ad-hoc queries in Ignite via SQL
* Write applications using Ignite to run continuous queries, combining data from multiple sources
Taking Jenkins Pipeline to the Extremeyinonavraham
Slide deck from Jenkins User Conference Tel Aviv 2018.
Talking about suggested (best?) practices, tips and tricks, using Jenkins pipeline scripts with shared libraries, managing shared libraries, using docker compose, and more.
Aspect-oriented programming (AOP) is a programming paradigm that aims to modularize cross-cutting concerns in code. AOP was developed by Gregor Kiczales and colleagues at Xerox PARC. AspectJ is a popular implementation of AOP for Java that uses pointcuts, advice, and inter-type declarations to inject additional behavior into existing code by means of weaving. Pointcuts define where advice should be applied, advice is the additional code to execute, and weaving is the process of applying aspects to code.
Oleksandr Smoktal "Parallel Seismic Data Processing Using OpenMP"LogeekNightUkraine
This document discusses parallelizing seismic data processing using OpenMP. It begins with an overview of OpenMP and its core syntax including compiler directives and runtime functions. An example is given showing how to parallelize a loop to process seismic data. Processing time was reduced from 80 seconds to 40 seconds by adding OpenMP parallelization to the noise burst removal algorithm. Further OpenMP features are described such as execution control directives, sections, tasks, SIMD, and locks.
In our everyday Java programming, we rely on familiar APIs without fully realizing their hidden performance impacts. This session aims to unveil the concealed performance aspects of common Java APIs and shed light on how they can influence your application's performance.
Join us to explore the unnoticed performance effects of these APIs and learn strategies to mitigate their impact. Whether you're a seasoned developer or new to Java, this paper equips you with essential knowledge to optimize your applications.
Reactive programming allows for non-blocking and concurrent executions. It is designed to be more efficient by using fewer threads and less memory. This makes applications more resilient and scalable to handle high connection volumes and traffic variability. The developer experience is improved through actionable stacktraces and debugging of reactive flows.
How to lock a Python in a cage? Managing Python environment inside an R projectWLOG Solutions
Presentation from a workshop delivered by Piotr Chaberski during PyData Warsaw Meetup on Feb. 06, 2018.
Imagine that you are developing a project using R and your big corporate customer, after weeks of processing requests to establish open-source analytical environment, finally managed to install R on their production machines. Now you realized, that it would be nice to use some Python library in your solution...
How would you tell the client to switch to Python for a while?
Beyond Breakpoints: A Tour of Dynamic AnalysisFastly
Despite advances in software design and static analysis techniques, software remains incredibly complicated and difficult to reason about. Understanding highly-concurrent, kernel-level, and intentionally-obfuscated programs are among the problem domains that spawned the field of dynamic program analysis. More than mere debuggers, the challenge of dynamic analysis tools is to be able record, analyze, and replay execution without sacrificing performance. This talk will provide an introduction to the dynamic analysis research space and hopefully inspire you to consider integrating these techniques into your own internal tools.
The magic behind your Lyft ride prices: A case study on machine learning and ...Karthik Murugesan
Rakesh Kumar and Thomas Weise explore how Lyft dynamically prices its rides with a combination of various data sources, ML models, and streaming infrastructure for low latency, reliability, and scalability—allowing the pricing system to be more adaptable to real-world changes.
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...Yuji Kubota
The document discusses a new runtime monitoring tool called HeapStats that provides a lightweight Java agent for collecting troubleshooting information from a Java application. It summarizes problems with current troubleshooting approaches like insufficient logging and complicated settings. HeapStats aims to collect required information continuously with low overhead, and provide easy-to-use visualization of the collected data to help with troubleshooting memory and performance issues. The document demonstrates how HeapStats hooks into garbage collection to gather heap statistics without extra stop-the-world pauses.
Not So Common Memory Leaks in Java WebinarTier1 app
This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers
Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
Read More:- https://www.esofttools.com/nsf-to-pst-converter.html
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
Here's a more detailed explanation:
Key Features and Capabilities:
Vector-Based Design:
Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
Scalability:
This vector-based approach allows for designs to be resized without any loss of resolution or quality, making it suitable for various print and digital applications.
Design Creation:
Illustrator is used for a wide variety of design purposes, including:
Logos and Brand Identity: Creating logos, icons, and other brand assets.
Illustrations: Designing detailed illustrations for books, magazines, web pages, and more.
Marketing Materials: Creating posters, flyers, banners, and other marketing visuals.
Web Design: Designing web graphics, including icons, buttons, and layouts.
Text Handling:
Illustrator offers sophisticated typography tools for manipulating and designing text within your graphics.
Brushes and Effects:
It provides a range of brushes and effects for adding artistic touches and visual styles to your designs.
Integration with Other Adobe Software:
Illustrator integrates seamlessly with other Adobe Creative Cloud apps like Photoshop, InDesign, and Dreamweaver, facilitating a smooth workflow.
Why Use Illustrator?
Professional-Grade Features:
Illustrator offers a comprehensive set of tools and features for professional design work.
Versatility:
It can be used for a wide range of design tasks and applications, making it a versatile tool for designers.
Industry Standard:
Illustrator is a widely used and recognized software in the graphic design industry.
Creative Freedom:
It empowers designers to create detailed, high-quality graphics with a high degree of control and precision.
Discover why Wi-Fi 7 is set to transform wireless networking and how Router Architects is leading the way with next-gen router designs built for speed, reliability, and innovation.
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
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Adobe After Effects is a software application used for creating motion graphics, special effects, and video compositing. It's widely used in TV and film post-production, as well as for creating visuals for online content, presentations, and more. While it can be used to create basic animations and designs, its primary strength lies in adding visual effects and motion to videos and graphics after they have been edited.
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After Effects is part of the Adobe Creative Cloud, a suite of software that includes other popular applications like Photoshop and Premiere Pro.
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After Effects is primarily used in the post-production phase, meaning it's used to enhance the visuals after the initial editing of footage has been completed.
How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik
This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements.
Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows.
We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure.
The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.
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Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185
GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
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PDF Reader Pro is a software application, often referred to as an AI-powered PDF editor and converter, designed for viewing, editing, annotating, and managing PDF files. It supports various PDF functionalities like merging, splitting, converting, and protecting PDFs. Additionally, it can handle tasks such as creating fillable forms, adding digital signatures, and performing optical character recognition (OCR).
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri
AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi
A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
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Maxon Cinema 4D 2025 is the latest version of the Maxon's 3D software, released in September 2024, and it builds upon previous versions with new tools for procedural modeling and animation, as well as enhancements to particle, Pyro, and rigid body simulations. CG Channel also mentions that Cinema 4D 2025.2, released in April 2025, focuses on spline tools and unified simulation enhancements.
Key improvements and features of Cinema 4D 2025 include:
Procedural Modeling: New tools and workflows for creating models procedurally, including fabric weave and constellation generators.
Procedural Animation: Field Driver tag for procedural animation.
Simulation Enhancements: Improved particle, Pyro, and rigid body simulations.
Spline Tools: Enhanced spline tools for motion graphics and animation, including spline modifiers from Rocket Lasso now included for all subscribers.
Unified Simulation & Particles: Refined physics-based effects and improved particle systems.
Boolean System: Modernized boolean system for precise 3D modeling.
Particle Node Modifier: New particle node modifier for creating particle scenes.
Learning Panel: Intuitive learning panel for new users.
Redshift Integration: Maxon now includes access to the full power of Redshift rendering for all new subscriptions.
In essence, Cinema 4D 2025 is a major update that provides artists with more powerful tools and workflows for creating 3D content, particularly in the fields of motion graphics, VFX, and visualization.
Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik
Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved?
Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security.
Talk from SciFiDevCon 2025
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Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025.
Key Takeaways:
Improved Salesforce CRM User Experience: Learn how self-service visibility enhances satisfaction.
Utilize Salesforce CRM Synch Dashboards: Explore real-time weekly activity data.
Monitor Performance Against Limits: See threshold limits for each product level.
Get Usage Over-Limit Alerts: Receive notifications for exceeding thresholds.
Learn About Improved Salesforce CRM Scale: Understand upcoming cloud-based incremental sync.