Search Results for "optimize" - Page 5
Sort By:
Showing 444 open source projects for "optimize"
View related business solutions-
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
PRTG Catches Network Issues Before They Cause DowntimeReactive troubleshooting usually means hearing about a problem from frustrated users, not your monitoring tool. PRTG sets threshold-based alerts across devices, servers and applications, notifying your team by email, SMS or push the moment a metric crosses a set limit. That means catching a failing disk or overloaded server before it becomes an outage and getting time back from firefighting. Start a free trial and set your first alerts today.
-
1
Rook
Storage Orchestration for Kubernetes
Rook turns distributed storage systems into self-managing, self-scaling, self-healing storage services. It automates the tasks of a storage administrator: deployment, bootstrapping, configuration, provisioning, scaling, upgrading, migration, disaster recovery, monitoring, and resource management. Rook orchestrates the Ceph storage solution, with a specialized Kubernetes Operator to automate management. Rook ensures that Ceph will run well on Kubernetes and simplify the deployment and... -
2
CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. ... -
3
fluentbit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX
...Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing. Filtering and enrichment to optimize security and minimize cost. The lightweight, asynchronous design optimizes resource usage: CPU, memory, disk I/O, network. No more OOM errors! Integration with all your technology, cloud-native services, containers, streaming processors, and data backends. Fully event-driven design leverages the operating system API for performance and reliability. ... -
4
lightGallery
A customizable, modular, responsive, lightbox gallery plugin
...Easily create your own modules, or detach modules that you don't want to use. lightGallery comes with many built-in modules, such as thumbnails, zoom, etc. light gallery is highly optimized for mobile and tablets to get the native look and feel and achieve the best performance. Supports separate settings for mobile devices to optimize further. lightGallery comes with numerous options, which allow you to customize the plugin without touching the core code. You can easily customize the look and feel of the gallery by updating SASS variables. -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
5
Turborepo
Build system optimized for JavaScript and TypeScript, written in Rust
...Turborepo won’t interfere with your runtime code or touch your sourcemaps. Execute builds using every core at maximum parallelism without wasting idle CPUs. Define the relationships between your tasks and then let Turborepo optimize what to build and when. -
6
Mac-list
The Mac software list and Mac usage tips
...It is designed as a continuously evolving resource, with contributions and updates expanding the list over time. The repository emphasizes completeness and usability, striving to become a go-to reference for Mac users looking to optimize their workflow. It serves both beginners and advanced users by offering a mix of essential tools and niche utilities. Overall, Mac-list functions as a curated ecosystem of macOS resources that enhance user productivity and system knowledge. -
7
CDviz
View software deployment's events & states
cdviz is a developer-focused visualization and analysis tool designed to help engineers understand, monitor, and optimize codebases by providing insights into structure, performance, and execution patterns. It likely focuses on transforming complex code relationships into visual representations that improve comprehension and debugging efficiency. The system may include static analysis capabilities, enabling it to detect inefficiencies, dependencies, or architectural issues within a project. ... -
8
Live helper chat
Live support for your website. Featuring web and mobile apps
...It supports a wide range of communication channels, including web chat widgets, email, and integrations with messaging platforms such as Facebook Messenger, Telegram, and WhatsApp. Advanced features such as chat automation, bots, proactive invitations, and analytics help businesses optimize customer engagement and response efficiency. -
9
Flexprice
Usage-based pricing and billing for developers
Flexprice is an open-source dynamic pricing engine designed to help online businesses and marketplaces automate and optimize their pricing strategies. It allows developers and data scientists to experiment with pricing algorithms using real-time market data, inventory levels, and historical sales to maximize revenue, conversion, or competitiveness. Built with flexibility in mind, Flexprice can be integrated into existing e-commerce infrastructure via APIs and supports simulation and A/B testing of pricing models. ... -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
10
Optax
Optax is a gradient processing and optimization library for JAX
Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize readability and structuring code to match standard equations, over code reuse. -
11
HomotopyContinuation.jl
A Julia package for solving systems of polynomials
HomotopyContinuation.jl is a Julia package for solving systems of polynomial equations by numerical homotopy continuation. Many models in the sciences and engineering are expressed as sets of real solutions to systems of polynomial equations. We can optimize any objective whose gradient is an algebraic function using homotopy methods by computing all critical points of the objective function. An important special case is when the objective function is the euclidean distance to a given point. An example of an non-algebraic objective function whose derivative is algebraic is the Kullback–Leibler divergence. ... -
12
VisualDL
Deep Learning Visualization Toolkit
VisualDL, a visualization analysis tool of PaddlePaddle, provides a variety of charts to show the trends of parameters and visualizes model structures, data samples, histograms of tensors, PR curves , ROC curves and high-dimensional data distributions. It enables users to understand the training process and the model structure more clearly and intuitively so as to optimize models efficiently. VisualDL provides various visualization functions, including tracking metrics in real-time, visualizing the model structure, displaying the data sample, visualizing the relationship between hyperparameters and model metrics, presenting the changes of distributions of tensors, showing the pr curves, projecting high-dimensional data to a lower dimensional space and more. ... -
13
Jessibuca
Jessibuca is an open source pure H5 live streaming player
...The player supports modern streaming protocols and codecs, allowing it to handle real-time video feeds with low latency and stable rendering. Its architecture is modular, separating decoding, demuxing, and rendering to optimize performance and scalability. Jessibuca includes intelligent buffering and frame handling to prevent delay accumulation during long playback sessions. It also supports multiple playback instances simultaneously, making it suitable for monitoring dashboards or multi-stream environments. With a lightweight footprint and strong compatibility, it is widely used for web-based surveillance, live streaming, and embedded video applications. -
14
Rhino
On-device Speech-to-Intent engine powered by deep learning
...Develop voice features with a few lines of code using intuitive and cross-platform SDKs. Deliver voice AI everywhere: on-device, mobile, web browsers, on-premise, or cloud. Measure adoption, learn, and iterate. Continuously re-design and re-train to optimize engagement. Building accurate, responsive, and private voice technology is difficult. We learned the hard way, so you don’t have to. Picovoice heavily invests in R&D to offer superior voice AI that surpasses even Big Tech in accuracy and efficiency. Picovoice researchers do not follow recent frameworks and techniques but build them. -
15
min-sized-rust
How to minimize Rust binary size
...This project systematically explores how to invert those priorities, focusing instead on minimizing output size for use cases such as embedded systems, WebAssembly, and constrained deployment environments. It provides concrete examples and configurations showing how to strip symbols, reduce panic overhead, optimize linking, and eliminate unused code paths. The repository also highlights trade-offs between size, performance, and safety, helping developers understand the implications of each optimization step. -
16
ArgoSBX
Xiaobai built his own agent artifact
...The tool supports a wide range of protocols and configurations, including TLS-based and Reality-based connections, enabling users to tailor their setup to different network conditions. One of its defining features is the ability to integrate CDN-based routing and WARP combinations, offering numerous configuration permutations to optimize performance and bypass restrictions. The script is built for minimal interaction, allowing users to deploy complex setups with a single command while still retaining deep customization options. -
17
CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory layouts, parallelism, and execution patterns while still maintaining a developer-friendly syntax. ... -
18
TensorRT LLM
TensorRT LLM provides users with an easy-to-use Python API
TensorRT-LLM is an open-source high-performance inference library specifically designed to optimize and accelerate large language model deployment on NVIDIA GPUs. It provides a Python-based API built on top of PyTorch that allows developers to define, customize, and deploy LLMs efficiently across a variety of hardware configurations, from single GPUs to large multi-node clusters. The library focuses on maximizing throughput and minimizing latency through advanced techniques such as quantization, custom attention kernels, and optimized memory management strategies. ... -
19
LMOps
General technology for enabling AI capabilities w/ LLMs and MLLMs
...The project explores the technologies and methodologies required to move foundation models from research environments into production-grade AI products. It includes experimental tools and frameworks that help developers optimize prompts, design workflows for generative models, and manage the lifecycle of LLM-based systems. The initiative also investigates techniques for improving the reliability, scalability, and maintainability of applications powered by large models. By addressing challenges such as prompt engineering, evaluation strategies, and deployment infrastructure, LMOps aims to establish best practices for operating large language model systems in real-world environments. -
20
Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
Anthropic's Original Performance repository contains the publicly released version of a performance challenge originally used by Anthropic as part of their technical interview process, offering developers the opportunity to optimize and benchmark low-level code against simulated models. The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under constraints. This take-home includes starter code, tests, and tools to debug performance, aiming to measure how effectively one can apply algorithmic improvements and optimizations. ... -
21
OpenOps
The batteries-included, No-Code FinOps automation platform
OpenOps is an open-source, no-code FinOps automation platform designed to help organizations manage and optimize cloud financial operations with minimal manual effort. At its core, OpenOps provides a visual workflow builder that lets teams construct automated processes for cloud cost optimization, budgeting, tagging, allocation, forecasting, and anomaly management without writing code, making complex financial workflows approachable for both technical and financial users. -
22
Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. ... -
23
Vibe Design System
Official monday.com UI resources for application development in React
...It includes comprehensive documentation, a component catalog, and an interactive playground so developers and designers can explore components, review guidelines, and experiment with layouts before using them in production. Vibe is distributed as a package, and loading its CSS tokens provides a unified theming baseline across apps and extensions. Components are designed to optimize usability and accessibility while supporting monday-style workflows such as boards, dashboards, and complex data visualizations. -
24
OpenAdapt
Open Source Generative Process Automation
OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook, and... -
25
Core ML Tools
Core ML tools contain supporting tools for Core ML model conversion
Use Core ML Tools (coremltools) to convert machine learning models from third-party libraries to the Core ML format. This Python package contains the supporting tools for converting models from training libraries. Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to fine-tune models, all on the user’s device. Core ML optimizes on-device...
