Search Results for "benchmark" - Page 11
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Showing 728 open source projects for "benchmark"
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hostscope
Linux system monitoring tool for multiple hosts
hostscope displays key system metrics of Linux hosts, such as detailed CPU load, speed and temperature, I/O rates of network interfaces, I/O rates of disks, and user process summary information. All metrics are multicast on the LAN, if wanted, and clients can switch between multiple hosts on the network. -
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution and post hoc analysis can be automated via the benchmarking and analysis workflow. The flexilibity to specifiy a large variety of docking configurations allows tailored protocols for diverse end applications. DockStream can also parallelize docking across CPU cores, increasing throughput. DockStream is integrated with the de novo design platform, REINVENT, allowing one... -
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CleverHans
An adversarial example library for constructing attacks
This repository contains the source code for CleverHans, a Python library to benchmark machine learning systems' vulnerability to adversarial examples. You can learn more about such vulnerabilities on the accompanying blog. The CleverHans library is under continual development, always welcoming contributions of the latest attacks and defenses. In particular, we always welcome help with resolving the issues currently open. -
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CalDOM
An agnostic, reactive & minimalist (3kb) JavaScript UI library
...The overall performance drop is about 0.04x compared to vanilla/pure JavaScript. This is based on averaged unit-level benchmarks in handling single & multiple-element instances: View Benchmark Results against Vanilla JS, jQuery, React JS, Vue & more. -
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1m-go-tcp-server
Benchmarks for implementation of servers
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. -
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CRSLab
CRSLab is an open-source toolkit
CRSLab is an open-source toolkit for building Conversational Recommender System (CRS). It is developed based on Python and PyTorch. CRSLab has the following highlights. Comprehensive benchmark models and datasets: We have integrated commonly-used 6 datasets and 18 models, including graph neural network and pre-training models such as R-GCN, BERT and GPT-2. We have preprocessed these datasets to support these models, and release for downloading. Extensive and standard evaluation protocols: We support a series of widely-adopted evaluation protocols for testing and comparing different CRS. ... -
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
...Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence labeling tasks such as XNLI, NER, and POS without target-language supervision. The repository provides preprocessing pipelines, training code, and fine-tuning scripts so you can reproduce benchmark results or adapt models to your own multilingual corpora. Pretrained checkpoints cover dozens of languages and multiple model sizes, balancing quality and compute needs. -
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wrk
Modern HTTP benchmarking tool
wrk is a modern, command-line HTTP benchmarking tool engineered for high performance, capable of generating substantial load using a single multi-core CPU by leveraging multithreading and scalable event notification systems. An optional LuaJIT script can perform HTTP request generation, response processing, and custom reporting. Details are available in SCRIPTING and several examples are located in scripts. The machine running wrk must have a sufficient number of ephemeral ports available... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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MachineLearningStocks
Using python and scikit-learn to make stock predictions
...Using libraries such as pandas and scikit-learn, the repository shows how historical financial indicators can be transformed into machine learning features. The model attempts to predict whether specific stocks will outperform a benchmark index such as the S&P 500. The repository includes scripts for parsing financial statistics, building training datasets, and performing backtesting to evaluate model performance over historical periods. Because it is structured as a template project, developers are encouraged to extend or modify the pipeline to test different algorithms, features, or investment strategies. -
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AmPEP and AxPEP
Sequence-based Antimicrobial Peptide Prediction by Random Forest
...Our optimal model, AmPEP with 1:3 data ratio achieved a very high accuracy of 96%, MCC of 0.9, AUC-ROC of 0.99 and Kappa statistic of 0.9. AmPEP outperforms existing methods with respect to accuracy, MCC, and AUC-ROC when tested using the benchmark datasets. Server online at https://cbbio.online/AxPEP -
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Protocol Buffers for Go with Gadgets
Protocol Buffers for Go with Gadgets
gogoprotobuf is a fork of golang/protobuf with extra code generation features. With this new release comes a new internal library version. This means any newly generated *pb.go files generated with the v1.3.0 library will not be compatible with the old library version (v1.2.1). However, current *pb.go files (generated with v1.2.1) should still work with the new library. Please make sure you manage your dependencies correctly when upgrading your project. If you are still using v1.2.1 and you... -
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gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
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Fast Elixir
Writing Fast Elixir. Collect Common Elixir idioms
Fast Elixir is a curated collection of performance-focused best practices, idioms, and code snippets for writing efficient Elixir programs. The project documents common patterns in Elixir and compares their relative performance using benchmarks to guide developers toward faster and more memory-friendly code. By showcasing side-by-side examples, it highlights not only which approaches are faster but also why certain functions or techniques should be preferred in different scenarios. The... -
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netstress is a client/server utility designed to stress & benchmark network activity of a given ethernet device or path using simulated (random) real world data and packet sizes instead of fixed data and packet sizes.
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progrep
Utility to show live progress, status & stats for running simulations
progrep is a command-line tool (Linux) to show live progress report, status & stats of a running simulation or compute job that executes a given number of iterations. It shows % completed, time remaining, time elapsed, number of threads, MPI_Rank(if any), CPU usage & speed (FPS). The FPS measures may be used in benchmarking, e.g. while optimizing HPC algorithms for performance. progrep supports both single-threaded and parallel (multicore/multinode - e.g. OpenMP/MPI) jobs. progrep can... -
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qpxtool
Utility for testing CD/DVD quality and burning rate
Utility for testing CD/DVD quality and transfer rate written on C++ and Qt -
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TensorFlow 2.0 Tutorials
TensorFlow 2.x version's Tutorials and Examples
...Each section of the repository includes runnable code and structured experiments designed to illustrate how different architectures and algorithms function in real applications. The tutorials use well-known benchmark datasets such as MNIST, CIFAR, and Fashion-MNIST to demonstrate practical model training and evaluation workflows. -
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The GeneRFinder-Benchmark is a comprehensive benchmark data for gene prediction which is based on data of CAMI (Critical Assessment of Metagenome Interpretation) and contains labeled data from gene regions. The benchmark is made up of 9 datasets. For each one of them is provided: - List of names, taxonomy ID and taxonomic level of the genomes of the organisms that make up the dataset (genomes.csv) - Set of sequences extracted from the respective selected genomes (sequences.fasta) - Ground truth for each of the extracted ORFs (groundtruth.csv) For information about download, see the documentation.
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
...It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights both fixed and learnable sparsity patterns that trade off computational cost and model expressiveness. By enabling tractable training on longer contexts, the project opened the door to applications in large-scale text and image generation. Though archived, it remains a key reference for efficient transformer research, influencing many later architectures that aim to extend sequence length while reducing compute. -
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ENAS in PyTorch
PyTorch implementation of "Efficient Neural Architecture Search
...The repository demonstrates how a controller network can explore a large search space and discover high-performing architectures while dramatically reducing the computational cost traditionally associated with neural architecture search. It is primarily intended as a research and educational codebase, helping practitioners understand how ENAS works in practice and how to reproduce results on benchmark datasets. The project includes training scripts, model definitions, and search procedures that show the full workflow from architecture sampling to evaluation. Because ENAS relies on shared weights among candidate models, the implementation emphasizes efficiency and experiment reproducibility. -
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sysbench
Scriptable database and system performance benchmark
...Can be used as a general-purpose Lua interpreter as well, simply replace #!/usr/bin/lua with #!/usr/bin/sysbench in your script. Execute events for this many seconds with statistics disabled before the actual benchmark run with statistics enabled. This is useful when you want to exclude the initial period of a benchmark run from statistics. -
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BenchMark para Revit
Test de hardware para Revit
Esta addin permite correr una serie de tests de hardware en Revit, y luego se publican los resultados en una base de datos web. El usuario obtiene una Mark, y el percentile respecto del resto de usuarios. -
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UNMAINTAINED: Try https://github.com/pjoe/loadem instead This project aims to provide a tool for load testing web applications. The goal is a tool that is easy to use and provides near real-time performance measurements of the application under test which is very usefull during optimization.
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Tiny
Tiny Face Detector, CVPR 2017
...The code depends on MatConvNet, which must be compiled (with GPU / CUDA / cuDNN support) for full performance. Pretrained model provided (ResNet101-based, plus alternatives). Demo and evaluation scripts for benchmark datasets. Use of “foveal descriptors” to incorporate context for low-resolution faces. Pretrained model provided (ResNet101-based, plus alternatives).
