Search Results for "optimizer"
Sort By:
Showing 158 open source projects for "optimizer"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
1
Prompt Optimizer
A prompt word optimizer to help write high-quality prompt words
Prompt-Optimizer is a high-impact AI prompt engineering tool designed to help users craft better, more effective prompts for large language models, boosting the quality and relevance of AI responses. It focuses on automating and streamlining the iterative refinement of prompts by analyzing examples, comparing original and optimized text, and guiding users through multi-round improvements that surface clarity, structure, and specificity. -
2
image-optimizer
Easily optimize images using PHP
Spatie Image Optimizer is a PHP package that automatically optimizes images by compressing them without losing quality. It works with various image formats, including JPEG, PNG, GIF, and SVG, by using underlying optimization tools. The package is lightweight and can be easily integrated into web applications to reduce image file sizes, enhancing loading speed and performance. -
3
Laravel Image Optimizer
Optimize images in your Laravel app
This package is the Laravel 6.0 and up-specific integration of spatie/image-optimizer. It can optimize PNGs, JPGs, SVGs, and GIFs by running them through a chain of various image optimization tools. The package will automatically detect which optimization binaries are installed on your system and use them. -
4
NVIDIA Model Optimizer
A unified library of SOTA model optimization techniques
Model Optimizer is a unified library that provides state-of-the-art techniques for compressing and optimizing deep learning models to improve inference efficiency and deployment performance. It brings together multiple optimization strategies such as quantization, pruning, distillation, and speculative decoding into a single cohesive framework. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
CoreCycler
Script to test single core stability
...Modern CPUs can adjust their CPU frequency depending on their load, and have mechanisms that allow them to clock higher. With this script, you can test the stability for each core, which helps you to validate if your Ryzen "PBO" resp. "Curve Optimizer" settings are actually stable. It also works to test Intel's "Active-Core" Turbo-Boost settings. -
6
Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
The Grey Wolf Optimizer for Path Planning is a MATLAB-based implementation of the Grey Wolf Optimizer (GWO) algorithm designed for UAV path and trajectory planning. It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. -
7
auto-cpufreq
Automatic CPU speed & power optimizer for Linux
Automatic CPU speed & power optimizer for Linux. Actively monitors laptop battery state, CPU usage, CPU temperature, and system load, ultimately allowing you to improve battery life without making any compromises. -
8
ProGuard
ProGuard, Java optimizer and obfuscator
ProGuard is a free shrinker, optimizer, obfuscator, and preverifier for Java bytecode. It detects and removes unused classes, fields, methods, and attributes. It optimizes bytecode and removes unused instructions. It renames the remaining classes, fields, and methods using short meaningless names. ProGuard can be run as a task in Gradle. Before you can use the proguard task, you have to make sure Gradle can find it in its class path at build time. -
9
This tool helps to optimize images (in batch) to their best quality given a constraint file size in KBs. It utilizes opensource tools such as imagemagick, with a modified binary search tree algorithm. Inspired by handbrake, it has been compiled for Windows 11 with Python 3.13.0 version. Most compatible for jpeg image files. See the intro video clip for how it works.
-
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
-
11
ReDex
A bytecode optimizer for Android apps
ReDex is an Android bytecode (dex) optimizer originally developed at Facebook. It provides a framework for reading, writing, and analyzing .dex files, and a set of optimization passes that use this framework to improve the bytecode. An APK optimized by ReDex should be smaller and faster than its source. Redex provides a framework for reading, writing, and analyzing .dex files, and a set of optimization passes that use this framework to improve the bytecode. -
12
CCC
Claude Opus 4.6 wrote a dependency-free C compiler in Rust
Claude’s C Compiler is a remarkable experiment in automated software generation: a full C compiler written from scratch in Rust entirely by an AI model (Claude Opus 4.6) with minimal human intervention, capable of targeting multiple architectures like x86-64, i686, ARM, and RISC-V. The project implements every part of a traditional compiler — the lexer, parser, intermediate representation, optimizer, code generator, assembler, linker, and debug info emitter — without relying on any external toolchain, producing standalone executables in the ELF format. While still early and not fully validated for correctness, it demonstrates the frontier of what sophisticated AI can build in complex, systems-level software domains, including the potential to compile real operating systems and large software projects. -
13
fastai
Deep learning library
fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying... -
14
Polars
Dataframes powered by a multithreaded, vectorized query engine
Polars is a high-performance, multi-language DataFrame library built in Rust using Apache Arrow. It delivers blazing-fast, vectorized, and parallel data manipulation with both eager and lazy execution, making it an excellent tool for data processing in Python, Rust, Node.js, R, and SQL contexts. -
15
FSRS4Anki
A modern Anki custom scheduling based on Free Spaced Repetition
A modern spaced-repetition scheduler for Anki based on the Free Spaced Repetition Scheduler algorithm. -
16
Kimi K2
Kimi K2 is the large language model series developed by Moonshot AI
...It was trained on an enormous corpus of over 15.5 trillion tokens to push frontier capabilities in coding, reasoning, and general agentic tasks while addressing training stability through novel optimizer and architecture design strategies. The model family includes variants like a foundational base model that researchers can fine-tune for specific use cases and an instruct-optimized variant primed for general-purpose chat and agent-style interactions, offering flexibility for both experimentation and deployment. With its high-dimensional attention mechanisms and expert routing, Kimi-K2 excels across benchmarks in live coding, math reasoning, and problem solving. -
17
SVGO
Node.js tool for optimizing SVG files
SVG Optimizer is a Node.js-based tool for optimizing SVG vector graphics files. SVG files, in particular those exported from multiple editors, normally contain tons of redundant and useless information. This can include editor metadata, comments, hidden elements, default or non-optimal values and other stuff that can be safely removed or converted without affecting the SVG rendering result. -
18
Optimizer_sovkov
Constructing and optimizing general mathematical and physical models
We present the package Optimizer, aimed at constructing and optimizing general mathematical models of phenomena of versatile nature. It is written in the Matlab algorithmic language and is executed in the Matlab environment with partial functionality in Octave. The convenient visual interface and the detailed manuals are provided. The main benefit of the package is its capability to construct models of any level of complexity in a block-by-block manner. -
19
MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
...AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. AMD OpenVX is a highly optimized open-source implementation of the Khronos OpenVX™ 1.3 computer vision specification. ... -
20
Functors.jl
Parameterise all the things
...For large machine learning models, it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help manage complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimizer update step. -
21
LLM From Scratch
Build and train a GPT-style language model
...Inspired by Andrej Karpathy’s nanoGPT, the project emphasizes learning through direct implementation and experimentation rather than black-box usage. The workshop documentation explains concepts such as self-attention, embeddings, gradient clipping, optimizer scheduling, and decoding strategies in a practical and approachable way. -
22
TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers, embedded, or automotive product platforms. ... -
23
Codeflash
Optimize your code automatically with AI
Codeflash is a general-purpose optimizer for Python that uses advanced large language models (LLMs) to automatically generate, test, and benchmark multiple optimization ideas, then creates merge-ready pull requests with the best improvements for your code. Optimize an entire existing codebase by running codeflash --all. Automate optimizing all future code you will write by installing Codeflash as a GitHub action. -
24
OpenVINO
OpenVINO™ Toolkit repository
...Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi. -
25
Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate into the JIT runtime seamlessly. ...