⚡️ Web Performance Research
- web
- performance
- react
- javascript
47,133 repositories indexed
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⚡️ Web Performance Research
C++ template library for high performance SIMD based sorting algorithms
A curated list of webpack tools for web performance
A collection of resources covering different aspects of JMeter usage.
A curated list of awesome tools, content and projects using k6
⚡Metrics to help understand page speed and user experience
A curated list of awesome resources for Graal, GraalVM, Truffle and related topics
Collection of open-source tools for debugging, benchmarking, load and stress testing your code or services.
Demo app for learning observability with Grafana and performance testing with k6.
A curated collection of publicly available resources on how companies around the world perform load testing
A curated list of excellent books to learn PostgreSQL — from beginner‑friendly introductions to advanced internals, administration, and performance tuning.
TranslatedC++ matrix multiplication performance experiments: from triple loops to blocking optimization and systolic arrays — an undergraduate introductory showcase project in the AI chip (NPU) direction
Suricata Extreme Performance Tuning guide - Mark II
A collection of resources covering different aspects of Locust load testing tool usage.
high performance computing related nix resources
A collection of resources covering different aspects of Gatling load testing tool usage.
Fast cartesian product
ECE 459: Programming for Performance, Winter 2015
A comprehensive guide to debugging tools for modern, complex front-end applications. This handbook provides practical, real-world guidance on a complete suite of tools, from Chrome DevTools and framework extensions to integrated IDE debuggers.
A curated, opinionated collection of tools and resources dedicated to Performance Engineering, covering both Observability and Performance Testing.
Linux tuning for CouchDB performance
A collection of resources covering all aspects of Tsung usage for load testing.
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.