Search Results for "linux performance booster" - Page 27
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Showing 933 open source projects for "linux performance booster"
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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ClassyVision
An end-to-end PyTorch framework for image and video classification
Classy Vision is a PyTorch-based framework designed for large-scale training and deployment of state-of-the-art image and video classification models. Developed by Facebook Research, it serves as an end-to-end system that simplifies the process of training at scale, reducing redundancy and friction in moving from research to production. Unlike traditional computer vision libraries that focus solely on modular components, Classy Vision provides a complete and unified framework, featuring... -
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ToMe (Token Merging)
A method to increase the speed and lower the memory footprint
ToMe (Token Merging) is a PyTorch-based optimization framework designed to significantly accelerate Vision Transformer (ViT) architectures without retraining. Developed by researchers at Facebook (Meta AI), ToMe introduces an efficient technique that merges similar tokens within transformer layers, reducing redundant computation while preserving model accuracy. This approach differs from token pruning, which removes background tokens entirely; instead, ToMe merges tokens based on feature... -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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FuzzBench
FuzzBench - Fuzzer benchmarking as a service
FuzzBench is a large-scale, open research platform developed by Google to evaluate and benchmark fuzzers — automated software testing tools that detect vulnerabilities through randomized input generation. It provides a standardized, reproducible environment for comparing the performance and effectiveness of different fuzzing algorithms on real-world software targets. FuzzBench integrates with the OSS-Fuzz infrastructure, allowing it to run experiments on authentic open source projects and... -
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Merlion
A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. It supports various time series learning tasks, including forecasting, anomaly detection, and change point detection for both univariate and multivariate time series. This library aims to provide engineers and researchers a one-stop solution to... -
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Render 4 Monitoring
Render Web Services for Viewing/Monitoring and Test Web Applications
Renders and aggregates other web services into static HTML monitoring output. Also implements simple and dynamic testing of web based applications using mechanize. Includes Basic authentication, and ADFS authentication for web service testing. Custom authentications can be implemented very easily with python programming. Implements PhantomJS rendering for Javascript/HTML5 dynamic web pages. Requires python3 -
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ElegantRL
Massively Parallel Deep Reinforcement Learning
ElegantRL is an efficient and flexible deep reinforcement learning framework designed for researchers and practitioners. It focuses on simplicity, high performance, and supporting advanced RL algorithms. -
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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sqlitedict
Persistent dict, backed by sqlite3 and pickle, multithread-safe
sqlitedict is a lightweight Python wrapper that provides a persistent dictionary backed by SQLite. Applications interact with stored data using familiar dictionary operations such as indexing, keys, values, items, and length. Values can contain any picklable Python object instead of being restricted to basic SQL types. Multiple independent dictionary tables can live inside the same SQLite database file. The library supports access to one connection from multiple threads while internally... -
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quantitative
Quantized transactions python3
The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew... -
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dein.vim
Dark powered Vim/Neovim plugin manager
dein.vim is a high-performance, feature-rich plugin manager for Vim and Neovim that enables fast startup and efficient plugin loading. It supports managing plugins from GitHub and local directories, with a design that balances speed (like vim-plug) and flexibility (like NeoBundle). Active development has ceased, with only bug fixes expected going forward. Function API and familiar patterns, without commands or dependency hell. Clean asynchronous installation supported. Supports plugins from... -
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
albert_zh is a Chinese ALBERT pretraining and model release repository. It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair... -
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Shennina
Automating Host Exploitation with AI
Shennina is an automated host exploitation framework. The mission of the project is to fully automate the scanning, vulnerability scanning/analysis, and exploitation using Artificial Intelligence. Shennina is integrated with Metasploit and Nmap for performing the attacks, as well as being integrated with an in-house Command-and-Control Server for exfiltrating data from compromised machines automatically. Shennina scans a set of input targets for available network services, uses its AI engine... -
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LSTMs for Human Activity Recognition
Human Activity Recognition example using TensorFlow on smartphone
LSTM-Human-Activity-Recognition is a machine learning project that demonstrates how recurrent neural networks can be used to recognize human activities from sensor data. The repository implements a deep learning model based on Long Short-Term Memory (LSTM) networks to classify physical activities using time-series data collected from wearable sensors. The project uses the well-known Human Activity Recognition dataset derived from smartphone accelerometer and gyroscope signals. Through the... -
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aiopg
aiopg is a library for accessing a PostgreSQL database
aiopg is an asynchronous PostgreSQL database driver for Python built on top of asyncio and psycopg2. It provides support for asynchronous query execution and connection pooling, enabling efficient, non-blocking database access in Python applications. aiopg is well-suited for web services and microservices that require concurrency without threads. -
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ProjectQ
An open source software framework for quantum computing
ProjectQ is an open-source effort for quantum computing. It features a compilation framework capable of targeting various types of hardware, a high-performance quantum computer simulator with emulation capabilities, and various compiler plug-ins. -
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Emb-GAM
An interpretable and efficient predictor using pre-trained models
Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings for... -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
AlphaTensor, developed by Google DeepMind, is the research codebase accompanying the 2022 Nature publication “Discovering faster matrix multiplication algorithms with reinforcement learning.” The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking,... -
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Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. The... -
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FormaVid
Small Business Appliance
The FormaVid Small Business Appliance https://formavid.org is designed to integrate a content management system (CMS), an issues tracker and an invoicing application into a single, well constructed, offering. It is an excellent starting point for any developer(s) wishing to support the CMS or any of the other components, including the appliance itself. All components are stable, open source and well supported. The appliance is built using scripts so no hidden "monkey business" and you can... -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV... -
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Text Classification
All kinds of text classification models and more with deep learning
Text Classification is a deep learning repository focused on text classification models for NLP. It provides a broad set of baseline architectures that can be used to study, train, compare, and adapt classification approaches. The project supports both single-label and multi-label classification, making it useful for sentence-level and document-level tasks. It includes classic and advanced models such as fastText, TextCNN, BERT, TextRNN, RCNN, hierarchical attention networks, seq2seq... -
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Fedhf
A Flexible Federated Learning Simulator
FedHF is a Python-based simulator for flexible, heterogeneous, and asynchronous federated learning research. It provides configurable resource models, supports asynchronous protocols, and accelerates experimentation. -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please...
