Search Results for "benchmark test"

Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it...

MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN...

1m-go-tcp-server is a benchmark collection for studying Go TCP server designs that can support one million connections. It compares different server architectures instead of presenting a single production framework. The repository includes implementations based on goroutines per connection, single epoll, multiple epoll loops, prefork design, worker pools, and Reactor-style event handling. It also includes client implementations and specialized benchmarks for throughput, latency, I/O-bound...

This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. ...

C1000K-Servers is a benchmark and prototype collection for high-performance WebSocket servers. It compares implementations built with frameworks and runtimes such as Spray, Netty, Undertow, Jetty, Vert.x, Grizzly, Node.js, Go, and Go-fasthttp. The project focuses on large-scale long-lived WebSocket connections and documents tests reaching more than one million active connections.

This project is now maintained at GitHub: https://github.com/DigitalInBlue/Celero Celero is a cross-platform open source C++ benchmarking library. Written with an API similar to Google Test, Celero utilizes C++11 features, offers tested benchmarking capabilities with microsecond precision, baselining, fixtures, and easy test setup. Use the baseline feature to measure/benchmark algorithm performance against a known case to more accurately rate performance of solutions.