InfoQ Homepage Optimization Content on InfoQ
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Optimization Strategies for the New Facebook.com - Ashley Watkins at React Conf
Ashley Watkins discussed at React Conf some of the technologies and strategies powering FB5, the new facebook.com, addressing topics such as data-driven dependencies, phased code and data downloading, and more.
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Google Releases Quantization Aware Training for TensorFlow Model Optimization
Google announced the release of the Quantization Aware Training (QAT) API for their TensorFlow Model Optimization Toolkit. QAT simulates low-precision hardware during the neural-network training process, adding the quantization error into the overall network loss metric, which causes the training process to minimize the effects of post-training quantization.
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Google Propeller Squeezes Extra Performance from Large-Scale LLVM Binaries
Google Propeller is able to improve the performance of LLVM binaries by relinking and optimizing them based on a profile of their behaviour at runtime. Propeller can bring 2-9% improvements on key performance benchmarks for binaries that were previously highly optimized by LLVM, say Google engineers.
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Simulating Agile Strategies with the Lazy Stopping Model
Simulation can be used to compare agile strategies and increase understanding of their strengths and weaknesses in different organisational and project contexts. The Lazy Stopping Model derived from the idea that we often fail to gather sufficient information to get an optimal result. Agile strategies can be simulated in the model as more or less effective defences against this “lazy stopping.”
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Snowpack Releases 1.0, Seeks to Speed Up App Development by Removing the Need for Bundlers
The Pika package registry recently released the first major version of Snowpack. Snowpack seeks to streamline the developer experience by leveraging web standards and modern browsers. Developers who restricts themselves to using ES modules, and standard features of the JavaScript language may no longer need to go through an often complex build chain to build, run and debug their applications.
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WebExpo 2019: More Than You Ever Wanted to Know About Resource Hints
Harry Roberts, consultant front-end architect at CSS Wizardry, discussed how web pages can be made faster with Resource Hints in a recent talk at WebExpo 2019 in Prague.
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Optimized Lazy Image Loading with Progressive JPEG and HTTP Range Requests
Christoph Erdmann recently detailed an interesting technique for image lazy loading using Progressive JPEG and HTTP range requests. Unlike other image placeholder and lazy loading techniques, using range requests do not result in downloading extra image data while still providing a small preview image similar to the original.
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ART Cloud Profiling to Improve Android App Performance
First introduced in Android Pie, ART optimizing profiles are a feature that leverages data sent to Play Cloud to optimize an app startup time on install or update. Data disclosed by Google show apps start 15% faster on average, with special cases reaching a 30% improvement.
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Webhint Open Source Linting Tool for Detecting Issues with Accessibility, Performance, and Security
The webhint project provides an open source linting tool to check for issues with accessibility, performance, and security. The creation of websites and web apps has an increasing number of details to perfect, and webhint strives to help developers remember these details.
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Performance of Structs in C# 7.2
The C# compiler, under some circumstances involving readonly, creates defensive copies of a struct. While this issue is well known and documented, it’s worth revisiting as it’s tied to several features of C# 7.2. The in and ref readonly keywords make occurrences of the issue more frequent, while readonly structs offer a way to fix it.
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MIT Extended LLVM IR to Enable Better Optimization of Parallel Programs
Researchers at MIT have been working on a fork of LLVM to explore a new approach to optimizing parallel code by embedding fork-join parallelism directly into the compiler’s intermediate representation (IR). This, the researchers maintain, makes it possible to leverage most of the IR-level serial optimizations for parallel programs.
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Mathieu Ripert on Instacart's Machine Learning Optimizations
Instacart is an online delivery service for groceries under one hour. Customers order the items on the website or using the mobile app, and a group of Instacart’s shoppers go to local stores, purchase the items and deliver them to the customer. InfoQ interviewed Mathieu Ripert, data scientist at Instacart, to find out how machine learning is leveraged to guarantee a better customer experience.
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AFK-MC² Algorithm Speeds up k-Means Clustering Algorithm Seeding
“Fast and Probably Good Seedings for k-Means” by Olivier Bachem et al. was presented on 2016’s Neural Information Processing Systems (NIPS) conference and describes AFK-MC2, an alternative method to generate initial seedings for k-Means clustering algorithm that is several orders of magnitude faster than the state of art method k-Means++.
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Addressing Visual Studio 15’s Memory Usage
As software projects grow in complexity and size, it has increased the resource demands imposed on programmer's toolsets. Visual Studio is no exception, and these increased demands combined with its ever-growing feature set means that it is feeling constrained. In this article we will examine how Microsoft is trying to overcome the 32-bit nature of VS15's main process.
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Profiling and Optimizing V8 Memory Consumption
For the last few months, the V8 team has focused on reducing the memory consumed by the V8 engine, including work on the new Ignition interpreter, and improvements to V8’s parser and compilers. A key enabler of this process was profiling V8 memory usage using specific tools against a benchmark, as explained by V8 engineers Ulan Degenbaev, Michael Lippautz, Hannes Payer, and Toon Verwaest.