ECE 459: Programming for Performance, Winter 2015
Repository Index
47,133 repositories indexed
49–65 of 65 · Most stars
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.
- chrome-devtools
- chrome-devtools-mcp
- react-devtools
- redux-devtools
Froggit-Go is a universal Go library, allowing to perform actions on VCS providers.
A collection of modules, tools and resources for play1
A curated, opinionated collection of tools and resources dedicated to Performance Engineering, covering both Observability and Performance Testing.
An example of pixel-perfect yet smooth camera for GameMaker Studio 2
Linux tuning for CouchDB performance
- couchdb-performance
- couchdb
- linux-tuning
This playground demonstrates how to perform physics collision detection using Swift and Sprite Kit.
A collection of resources covering all aspects of Tsung usage for load testing.
- tsung
- tsung-plugin
- load-testing
- awesome
A book that demonstrates how to perform typical table data operations using PRQL and DuckDB.
A port of ping crm demo to Imba, node and edgedb using imba and node inertia adapters
ActualLab.Fusion Samples are here. Skip SignalR and gRPC. Build real-time Blazor and MAUI apps while writing just 0.1% of the usual real-time update code. Handle 10× more API requests with the ActualLab.Rpc protocol—or 1000× more with Fusion’s transparent and perfectly coherent caching.
Tired of screen fragmentation? AppDimens is the unified solution for responsive, pixel-perfect UI across all platforms and devices. It offers adaptive scaling (SDP, SSP, Dynamic, Fixed) for Kotlin, Compose, XML Views, Swift, and SwiftUI, ensuring layouts and fonts scale perfectly from the smallest to the largest device.
Simple networking example, which mimics how 39dll network games were working (actions performed basing on first byte in buffer).
Demo of high performance AI model (pmml export) evaluator api base on Vert.x, Supports dynamic routing configuration for multiple pmml models via JSON
- pmml
- ai
- java-pmml
- verticle
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.
Test script & demo use case for Perfjankie