Best AI tools for< Optimize Runtime >

ONNX Runtime is a production-grade AI engine designed to accelerate machine learning training and inferencing in various technology stacks. It supports multiple languages and platforms, optimizing performance for CPU, GPU, and NPU hardware. ONNX Runtime powers AI in Microsoft products and is widely used in cloud, edge, web, and mobile applications. It also enables large model training and on-device training, offering state-of-the-art models for tasks like image synthesis and text generation.

TimeComplexity.ai is an AI tool that helps users analyze the runtime complexity of their code. It can be used across different programming languages without the need for headers, imports, or a main statement. Users can input their code and get insights into its efficiency. However, it is important to note that the results may not always be accurate, so caution is advised when using the tool.

ONNX is an open standard for machine learning interoperability, providing a common format to represent machine learning models. It defines a set of operators and a file format for AI developers to use models across various frameworks, tools, runtimes, and compilers. ONNX promotes interoperability, hardware access, and community engagement.

SWE Kit is an open-source headless IDE designed for building custom coding agents with state-of-the-art performance. It offers AI-native tools to streamline the coding review process, enhance code quality, and optimize development efficiency. The application supports various agentic frameworks and LLM inference providers, providing a flexible runtime environment for seamless codebase interaction. With features like code analysis, code indexing, and third-party service integrations, SWE Kit empowers developers to create and run coding agents effortlessly.

Webflow Optimize is an AI-powered website optimization and personalization tool that allows users to create high-performing sites, analyze site performance, maximize conversions through testing and personalization, and connect their site to various apps. It offers features such as A/B testing, personalization, audience insights, advanced targeting, and integration with ABM tools. With Webflow Optimize, users can deliver custom experiences, track performance, and harness AI for faster results and smarter insights.

Jobscan is a comprehensive job search tool that helps job seekers optimize their resumes, cover letters, and LinkedIn profiles to increase their chances of getting interviews. It uses artificial intelligence and machine learning technology to analyze job descriptions and identify the skills and keywords that recruiters are looking for. Jobscan then provides personalized suggestions on how to tailor your application materials to each specific job you apply for. In addition to its resume and cover letter optimization tools, Jobscan also offers a job tracker, a LinkedIn optimization tool, and a career change tool. With its powerful suite of features, Jobscan is an essential tool for any job seeker who wants to land their dream job.

TestMarket is an AI-powered sales optimization platform for online marketplace sellers. It offers a range of services to help sellers increase their visibility, boost sales, and improve their overall performance on marketplaces such as Amazon, Etsy, and Walmart. TestMarket's services include product promotion, keyword analysis, Google Ads and SEO optimization, and advertising optimization.

VWO is a comprehensive experimentation platform that enables businesses to optimize their digital experiences and maximize conversions. With a suite of products designed for the entire optimization program, VWO empowers users to understand user behavior, validate optimization hypotheses, personalize experiences, and deliver tailored content and experiences to specific audience segments. VWO's platform is designed to be enterprise-ready and scalable, with top-notch features, strong security, easy accessibility, and excellent performance. Trusted by thousands of leading brands, VWO has helped businesses achieve impressive growth through experimentation loops that shape customer experience in a positive direction.

Botify AI is an AI-powered tool designed to assist users in optimizing their website's performance and search engine rankings. By leveraging advanced algorithms and machine learning capabilities, Botify AI provides valuable insights and recommendations to improve website visibility and drive organic traffic. Users can analyze various aspects of their website, such as content quality, site structure, and keyword optimization, to enhance overall SEO strategies. With Botify AI, users can make data-driven decisions to enhance their online presence and achieve better search engine results.

Siteimprove is an AI-powered platform that offers a comprehensive suite of digital governance, analytics, and SEO tools to help businesses optimize their online presence. It provides solutions for digital accessibility, quality assurance, content analytics, search engine marketing, and cross-channel advertising. With features like AI-powered insights, automated analysis, and machine learning capabilities, Siteimprove empowers users to enhance their website's reach, reputation, revenue, and returns. The platform transcends traditional boundaries by addressing a wide range of digital requirements and impact-drivers, making it a valuable tool for businesses looking to improve their online performance.

SiteSpect is an AI-driven platform that offers A/B testing, personalization, and optimization solutions for businesses. It provides capabilities such as analytics, visual editor, mobile support, and AI-driven product recommendations. SiteSpect helps businesses validate ideas, deliver personalized experiences, manage feature rollouts, and make data-driven decisions. With a focus on conversion and revenue success, SiteSpect caters to marketers, product managers, developers, network operations, retailers, and media & entertainment companies. The platform ensures faster site performance, better data accuracy, scalability, and expert support for secure and certified optimization.

EverSQL is an AI-powered SQL query optimizer and database observability tool that specializes in optimizing PostgreSQL and MySQL databases. It offers automatic SQL query optimization, ongoing performance insights, and cost reduction recommendations. With over 100,000 professionals trusting EverSQL, it aims to save time and improve database performance by making SQL queries faster and more efficient.

Competera is an AI-powered pricing platform designed for online and omnichannel retailers. It offers a unified workplace with an easy-to-use interface, real-time market data, and AI-powered product matching. Competera focuses on demand-based pricing, customer-centric pricing, and balancing price elasticity with competitive pricing. It provides granular pricing at the SKU level and offers a seamless adoption and onboarding process. The platform helps retailers optimize pricing strategies, increase margins, and save time on repricing.

Inventoro is a smart inventory forecasting and replenishment tool that helps businesses optimize their inventory management processes. By analyzing past sales data, the tool predicts future sales, recommends order quantities, reduces inventory size, identifies profitable inventory items, and ensures customer satisfaction by avoiding stockouts. Inventoro offers features such as sales forecasting, product segmentation, replenishment, system integration, and forecast automations. The tool is designed to help businesses decrease inventory, increase revenue, save time, and improve product availability. It is suitable for businesses of all sizes and industries looking to streamline their inventory management operations.

Vic.ai is an AI-powered accounting software designed to streamline invoice processing, purchase order matching, approval flows, payments, analytics, and insights. The platform offers autonomous finance solutions that optimize accounts payable processes, achieve lasting ROI, and enable informed decision-making. Vic.ai leverages AI technology to enhance productivity, accuracy, and efficiency in accounting workflows, reducing manual tasks and improving overall financial operations.

TimeToTok is an AI Copilot and Agent designed for TikTok creators to optimize their posting schedule and content strategy. By analyzing millions of viral TikTok videos worldwide, TimeToTok provides personalized insights and recommendations to help creators increase engagement, gain more followers, and boost their views. The application leverages LLM AI technology, like GPT, to deliver data-driven growth strategies and improve content performance. With features such as identifying the best time to post, generating viral content ideas, optimizing videos, tracking competitors, and providing continuous support, TimeToTok aims to simplify TikTok growth and make it more effective for creators.

Paro is a professional business finance and accounting solutions platform that matches businesses and accounting firms with skilled finance experts. It offers a wide range of services including accounting, bookkeeping, financial planning, budgeting, business analysis, data visualization, strategic advisory, growth strategy consulting, startup and fundraising consulting, transaction advisory, tax and compliance services, AI consulting services, and more. Paro aims to help businesses optimize faster by providing expert solutions to bridge gaps in finance and accounting operations. The platform also offers staff augmentation services, talent acquisition, and custom solutions to enhance operational efficiency and maximize ROI.

Seventh Sense is an AI software designed to optimize email delivery times using artificial intelligence for HubSpot and Marketo users. It helps email marketers improve engagement and conversions by personalizing email delivery times based on individual recipient behavior. The tool aims to address the challenges of email marketing in today's competitive digital landscape by leveraging AI to increase deliverability, engagement, and conversions. Seventh Sense has been successful in helping hundreds of companies enhance their email marketing performance and stand out in crowded inboxes.

Rewatch is an AI-powered meeting assistant and video hub that helps users capture meetings, create summaries, transcriptions, and action items. It centralizes all meeting videos, notes, and discussions in one place, replacing repetitive in-person meetings with asynchronous collaborative series. Rewatch also offers features like screen recording, integrations with other tools, and conversation intelligence to empower organizations with actionable insights. Trusted by productive businesses, Rewatch aims to optimize necessary meetings, eliminate useless ones, and enhance cross-functional collaboration in a unified hub.

CEREBRUMX is an AI-powered platform that offers preventive car maintenance telematics solutions for various industries such as fleet management, vehicle service contracts, electric vehicles, smart cities, and media. The platform provides data insights and features like driver safety, EV charging, predictive maintenance, roadside assistance, and traffic flow management. CEREBRUMX aims to optimize fleet operations, enhance efficiency, and deliver high-value impact to customers through real-time connected vehicle data insights.

LiteRT is Google's open-source high-performance runtime for on-device AI, previously known as TensorFlow Lite. The repository is currently not intended for open-source development, but aims to evolve to allow direct building and contributions. LiteRT supports Python versions 3.9, 3.10, 3.11 on Linux and MacOS. It ensures compatibility with existing .tflite file extension and format, offering conversion tools and continued active development under the name LiteRT.

Data Prep Kit is a community project aimed at democratizing and speeding up unstructured data preparation for LLM app developers. It provides high-level APIs and modules for transforming data (code, language, speech, visual) to optimize LLM performance across different use cases. The toolkit supports Python, Ray, Spark, and Kubeflow Pipelines runtimes, offering scalability from laptop to datacenter-scale processing. Developers can contribute new custom modules and leverage the data processing library for building data pipelines. Automation features include workflow automation with Kubeflow Pipelines for transform execution.

Starwhale is an MLOps/LLMOps platform that brings efficiency and standardization to machine learning operations. It streamlines the model development lifecycle, enabling teams to optimize workflows around key areas like model building, evaluation, release, and fine-tuning. Starwhale abstracts Model, Runtime, and Dataset as first-class citizens, providing tailored capabilities for common workflow scenarios including Models Evaluation, Live Demo, and LLM Fine-tuning. It is an open-source platform designed for clarity and ease of use, empowering developers to build customized MLOps features tailored to their needs.

Bodo is a high-performance Python compute engine designed for large-scale data processing and AI workloads. It utilizes an auto-parallelizing just-in-time compiler to optimize Python programs, making them 20x to 240x faster compared to alternatives. Bodo seamlessly integrates with native Python APIs like Pandas and NumPy, eliminates runtime overheads using MPI for distributed execution, and provides exceptional performance and scalability for data workloads. It is easy to use, interoperable with the Python ecosystem, and integrates with modern data platforms like Apache Iceberg and Snowflake. Bodo focuses on data-intensive and computationally heavy workloads in data engineering, data science, and AI/ML, offering automatic optimization and parallelization, linear scalability, advanced I/O support, and a high-performance SQL engine.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

Koordinator is a QoS based scheduling system for hybrid orchestration workloads on Kubernetes. It aims to improve runtime efficiency and reliability of latency sensitive workloads and batch jobs, simplify resource-related configuration tuning, and increase pod deployment density. It enhances Kubernetes user experience by optimizing resource utilization, improving performance, providing flexible scheduling policies, and easy integration into existing clusters.

GLake is an acceleration library and utilities designed to optimize GPU memory management and IO transmission for AI large model training and inference. It addresses challenges such as GPU memory bottleneck and IO transmission bottleneck by providing efficient memory pooling, sharing, and tiering, as well as multi-path acceleration for CPU-GPU transmission. GLake is easy to use, open for extension, and focuses on improving training throughput, saving inference memory, and accelerating IO transmission. It offers features like memory fragmentation reduction, memory deduplication, and built-in security mechanisms for troubleshooting GPU memory issues.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

The ByteIR Project is a ByteDance model compilation solution. ByteIR includes compiler, runtime, and frontends, and provides an end-to-end model compilation solution. Although all ByteIR components (compiler/runtime/frontends) are together to provide an end-to-end solution, and all under the same umbrella of this repository, each component technically can perform independently. The name, ByteIR, comes from a legacy purpose internally. The ByteIR project is NOT an IR spec definition project. Instead, in most scenarios, ByteIR directly uses several upstream MLIR dialects and Google Mhlo. Most of ByteIR compiler passes are compatible with the selected upstream MLIR dialects and Google Mhlo.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

uTensor is an extremely light-weight machine learning inference framework built on Tensorflow and optimized for Arm targets. It consists of a runtime library and an offline tool that handles most of the model translation work. The core runtime is only ~2KB. The workflow involves constructing and training a model in Tensorflow, then using uTensor to produce C++ code for inferencing. The runtime ensures system safety, guarantees RAM usage, and focuses on clear, concise, and debuggable code. The high-level API simplifies tensor handling and operator execution for embedded systems.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

TensorRT-LLM is an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM contains components to create Python and C++ runtimes that execute those TensorRT engines. It also includes a backend for integration with the NVIDIA Triton Inference Server; a production-quality system to serve LLMs. Models built with TensorRT-LLM can be executed on a wide range of configurations going from a single GPU to multiple nodes with multiple GPUs (using Tensor Parallelism and/or Pipeline Parallelism).

The GenAI repository contains pipelines that implement image and text generation tasks. The implementation uses OpenVINO capabilities to optimize the pipelines. Each sample covers a family of models and suggests certain modifications to adapt the code to specific needs. It includes the following pipelines: 1. Benchmarking script for large language models 2. Text generation C++ samples that support most popular models like LLaMA 2 3. Stable Diffuison (with LoRA) C++ image generation pipeline 4. Latent Consistency Model (with LoRA) C++ image generation pipeline

PowerInfer is a high-speed Large Language Model (LLM) inference engine designed for local deployment on consumer-grade hardware, leveraging activation locality to optimize efficiency. It features a locality-centric design, hybrid CPU/GPU utilization, easy integration with popular ReLU-sparse models, and support for various platforms. PowerInfer achieves high speed with lower resource demands and is flexible for easy deployment and compatibility with existing models like Falcon-40B, Llama2 family, ProSparse Llama2 family, and Bamboo-7B.

Zeta is a tool designed to build state-of-the-art AI models faster by providing modular, high-performance, and scalable building blocks. It addresses the common issues faced while working with neural nets, such as chaotic codebases, lack of modularity, and low performance modules. Zeta emphasizes usability, modularity, and performance, and is currently used in hundreds of models across various GitHub repositories. It enables users to prototype, train, optimize, and deploy the latest SOTA neural nets into production. The tool offers various modules like FlashAttention, SwiGLUStacked, RelativePositionBias, FeedForward, BitLinear, PalmE, Unet, VisionEmbeddings, niva, FusedDenseGELUDense, FusedDropoutLayerNorm, MambaBlock, Film, hyper_optimize, DPO, and ZetaCloud for different tasks in AI model development.

The `ai-models` command is a tool used to run AI-based weather forecasting models. It provides functionalities to install, run, and manage different AI models for weather forecasting. Users can easily install and run various models, customize model settings, download assets, and manage input data from different sources such as ECMWF, CDS, and GRIB files. The tool is designed to optimize performance by running on GPUs and provides options for better organization of assets and output files. It offers a range of command line options for users to interact with the models and customize their forecasting tasks.

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. It provides a common API to deliver inference solutions on various platforms, including CPU, GPU, NPU, and heterogeneous devices. OpenVINO™ supports pre-trained models from Open Model Zoo and popular frameworks like TensorFlow, PyTorch, and ONNX. Key components of OpenVINO™ include the OpenVINO™ Runtime, plugins for different hardware devices, frontends for reading models from native framework formats, and the OpenVINO Model Converter (OVC) for adjusting models for optimal execution on target devices.

RKLLM software stack is a toolkit designed to help users quickly deploy AI models to Rockchip chips. It consists of RKLLM-Toolkit for model conversion and quantization, RKLLM Runtime for deploying models on Rockchip NPU platform, and RKNPU kernel driver for hardware interaction. The toolkit supports RK3588 and RK3576 series chips and various models like TinyLLAMA, Qwen, Phi, ChatGLM3, Gemma, InternLM2, and MiniCPM. Users can download packages, docker images, examples, and docs from RKLLM_SDK. Additionally, RKNN-Toolkit2 SDK is available for deploying additional AI models.

TurnkeyML is a tools framework that integrates models, toolchains, and hardware backends to simplify the evaluation and actuation of deep learning models. It supports use cases like exporting ONNX files, performance validation, functional coverage measurement, stress testing, and model insights analysis. The framework consists of analysis, build, runtime, reporting tools, and a models corpus, seamlessly integrated to provide comprehensive functionality with simple commands. Extensible through plugins, it offers support for various export and optimization tools and AI runtimes. The project is actively seeking collaborators and is licensed under Apache 2.0.

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