Alternatives to RunMat
Compare RunMat alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to RunMat in 2026. Compare features, ratings, user reviews, pricing, and more from RunMat competitors and alternatives in order to make an informed decision for your business.
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1
UberCloud
Simr (formerly UberCloud)
Simr (formerly UberCloud) is a cutting-edge platform for Simulation Operations Automation (SimOps). It streamlines and automates complex simulation workflows, enhancing productivity and collaboration. Leveraging cloud-based infrastructure, Simr offers scalable, cost-effective solutions for industries like automotive, aerospace, and electronics. Trusted by leading global companies, Simr empowers engineers to innovate efficiently and effectively. Simr supports a variety of CFD, FEA and other CAE software including Ansys, COMSOL, Abaqus, CST, STAR-CCM+, MATLAB, Lumerical and more. Simr automates every major cloud including Microsoft Azure, Amazon AWS, and Google GCP. -
2
Rio Terminal
Rio Terminal
Rio is a terminal application that’s built with Rust, WebGPU, Tokio runtime. It targets to have the best frame per second experience as long you want, but is also configurable to use as minimal from GPU. The terminal renderer is based on redux state machine, lines that has not updated will not suffer a redraw. Looking for the minimal rendering process in most of the time. Rio is also designed to support WebAssembly runtime so in the future you will be able to define how a tab system will work with a WASM plugin written in your favorite language. Rio uses WGPU, which is an implementation of WebGPU for use outside of a browser and as backend for Firefox’s WebGPU implementation. WebGPU allows for more efficient usage of modern GPU’s than WebGL. -
3
MATLAB
The MathWorks
MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design. -
4
Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.
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5
TypeGPU
Software Mansion
TypeGPU is a TypeScript library that enhances the WebGPU API, allowing resource management in a type-safe, declarative way. It is designed to change the way developers work with GPU rendering and computing by bringing stronger structure, validation, and developer experience to WebGPU workflows. TypeGPU helps developers easily encode and decode GPU data, using typed binary so they do not have to think about raw bytes when writing GPU programs. Complex data types such as structs and arrays can be described directly, while TypeScript automatically validates outgoing and incoming data. It works on React Native through react-native-wgpu, expanding WebGPU development beyond the browser. TypeGPU’s roadmap is focused on end-to-end type safety on the GPU through interoperating primitives such as data structures, buffers, bind groups, a linker, functions, pipelines, and imperative code. -
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YAKINDU Model Viewer
itemis AG
YAKINDU Model Viewer (YMV) is a tool designed for the viewing of models created with MATLAB Simulink and shows the corresponding block diagrams with a similar look and feel as in Simulink. YAKINDU Model Viewer gives you the flexibility to quickly navigate, explore, and search very large and complex models. It provides browser-like navigation on diagrams, allowing a fast drill-down of the system hierarchy. It also features rich visualization, signal tracing, requirements tracing, gesture-based interactions, and much more. YAKINDU Model Viewer provides various views to visualize a model’s outline and the properties of elements. -
7
PyTorch
PyTorch
Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies. -
8
LiveLink for MATLAB
Comsol Group
Seamlessly integrate COMSOL Multiphysics® with MATLAB® to extend your modeling with scripting programming in the MATLAB environment. LiveLink™ for MATLAB® allows you to utilize the full power of MATLAB and its toolboxes in preprocessing, model manipulation, and postprocessing. Enhance your in-house MATLAB code with powerful multiphysics simulations. Base your geometry modeling on probabilistic or image data. Use multiphysics models together with Monte Carlo simulations and genetic algorithms. Export COMSOL models on state-space matrix format for incorporating into control systems. Interface in the COMSOL Desktop® environment enables the use of MATLAB® functions while modeling. Manipulate your models from the command line or script to parameterize the geometry, physics, or the solution scheme. -
9
Micrium OS
Silicon Labs
At the heart of any embedded OS is a kernel, which provides vital task scheduling and multi-tasking services to ensure that the timing requirements of your application code can be met, even as you regularly update and expand that code with new features. Micrium OS is more than a kernel, though, providing a number of additional modules to help you meet your project’s needs. Micrium OS is provided entirely free of charge for deployment on Silicon Labs EFM32 and EFR32 devices! You can begin adding Micrium’s professional-quality components to your projects today without payment of any licensing fees. -
10
Autodesk Fusion
Autodesk
Autodesk Fusion is a cloud-based product design and manufacturing platform that combines CAD, CAM, CAE, PCB, and data management in one solution. It helps teams connect design, engineering, manufacturing, electronics, and collaboration workflows in a unified workspace. The software supports product development from concept to production with tools for modeling, simulation, machining, PCB design, and drawing automation. Autodesk Fusion also includes built-in PDM and PLM capabilities to reduce version conflicts, improve collaboration, and keep project data secure and up to date. Teams can choose from Fusion, Fusion for Manufacturing, and Fusion for Design depending on their needs for advanced manufacturing, simulation, generative design, and data management. With cloud collaboration, integrated workflows, and AI-powered assistance, Autodesk Fusion helps companies bring products to market faster.Starting Price: $495 per year -
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Apple Hypervisor
Apple
Build virtualization solutions on top of a lightweight hypervisor, without third-party kernel extensions. Hypervisor provides C APIs so you can interact with virtualization technologies in user space, without writing kernel extensions (KEXTs). As a result, the apps you create using this framework are suitable for distribution on the Mac App Store. Use this framework to create and control hardware-facilitated virtual machines and virtual processors (VMs and vCPUs) from your entitled, sandboxed, user-space process. Hypervisor abstracts virtual machines as processes, and virtual processors as threads. The Hypervisor framework requires hardware support to virtualize hardware resources. On Apple silicon, that includes the Virtualization Extensions. On Intel-based Mac computers, the framework supports machines with an Intel VT-x feature set that includes Extended Page Tables (EPT) and Unrestricted Mode. -
12
LXC
Canonical
LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers. LXC containers are often considered as something in the middle between a chroot and a full fledged virtual machine. The goal of LXC is to create an environment as close as possible to a standard Linux installation but without the need for a separate kernel. LXC is free software, most of the code is released under the terms of the GNU LGPLv2.1+ license, some Android compatibility bits are released under a standard 2-clause BSD license and some binaries and templates are released under the GNU GPLv2 license. LXC's stable release support relies on the Linux distributions and their own commitment to pushing stable fixes and security updates. -
13
Minoca OS
Minoca
Minoca OS is an open-source, general purpose operating system designed specifically for feature-rich embedded devices. It's got all the high-level functionality that you've come to expect from an operating system, but offers it in a fraction of the memory footprint. The driver API separates device drivers from the kernel, enabling driver binaries to remain compatible even when the kernel is updated. Driver separation allows for automatic loading and unloading of device drivers on demand. Hardware layer API allows for a single unified kernel, even on ARM. No need to maintain a separate kernel fork. A unified power management architecture allows for smarter power management decisions, leading to better device battery life. Fewer background tasks and wake-ups from idle means machines can reach deeper idle states and save even more power. Proprietary and non-GPL source licenses are available, keeping options open for your customers and end users. -
14
Homebrew Cask
Homebrew
A CLI workflow for the administration of macOS applications distributed as binaries. Homebrew Cask extends Homebrew and brings its elegance, simplicity, and speed to the installation and management of GUI macOS applications such as Atom and Google Chrome. We do this by providing a friendly CLI workflow for the administration of macOS applications distributed as binaries. To start using Homebrew Cask, you just need Homebrew installed. Homebrew Cask installs macOS apps, fonts and plugins, and other non-open source software. Homebrew Cask is implemented as part of Homebrew. All Homebrew Cask commands begin with brew, which works for both Casks and Formulae. The command brew install accepts one or multiple Cask tokens. Homebrew Cask comes with bash and zsh completion for the brew command. Since the Homebrew Cask repository is a Homebrew Tap, you’ll pull down the latest Casks every time you issue the regular Homebrew command brew update.Starting Price: Free -
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QEMU
QEMU
QEMU is a generic and open-source machine emulator and virtualizer. Run operating systems for any machine, on any supported architecture. Run programs for another Linux/BSD target, on any supported architecture. Run KVM and Xen virtual machines with near-native performance. Guest memory dumps are now fully supported, along with pre-copy/post-copy migration and background guest snapshots. Support for nw DEVICE_UNPLUG_GUEST_ERROR to detect guest-reported hotplug failures. macOS hosts with Apple Silicon CPUs now support ‘hvf’ accelerator for AArch64 guests. M-profile MVE extension is now supported for Cortex-M55. AMD SEV guests now support measurement of kernel binary when doing direct kernel boot (not using a bootloader). Support for vhost-user and numa mem options across all boards. -
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Collimator
Collimator
Collimator is a modeling and simulation platform for hybrid dynamical systems. We allow engineers to design and test complex, mission critical systems in a way that is reliable, secure, fast and intuitive. Our customers are electrical, mechanical and control systems engineers who are using Collimator to increase productivity, improve performance and collaborate more effectively. They do this using our out of the box features including an intuitive block diagram graphical editor, Python blocks to develop custom algorithms, Jupyter notebooks to parametrize and optimize their systems, high performance computing in the cloud and role based access controls. -
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CUDA
NVIDIA
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.Starting Price: Free -
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TorchMetrics
TorchMetrics
TorchMetrics is a collection of 90+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. A standardized interface to increase reproducibility. It reduces boilerplate. distributed-training compatible. It has been rigorously tested. Automatic accumulation over batches. Automatic synchronization between multiple devices. You can use TorchMetrics in any PyTorch model, or within PyTorch Lightning to enjoy additional benefits. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. Similar to torch.nn, most metrics have both a class-based and a functional version. The functional versions implement the basic operations required for computing each metric. They are simple python functions that as input take torch.tensors and return the corresponding metric as a torch.tensor. Nearly all functional metrics have a corresponding class-based metric.Starting Price: Free -
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Code Metal
Code Metal
CodeMetal is an AI-enabled code translation and deployment platform designed to help engineering teams automatically convert high-level reference code into optimized, hardware-specific implementations for edge and embedded environments. It allows developers to write algorithms in familiar languages such as Python, MATLAB, or Julia and then automatically generates low-level code tailored to the target runtime, including embedded C/C++, Rust, CUDA, or FPGA languages. Its agentic workflow analyzes module dependencies, maps equivalents across architectures, and produces a transpilation and deployment plan that developers can review or execute directly. CodeMetal emphasizes verifiable AI by combining generative techniques with formal methods to ensure translated code is tested, compliant, and production-ready, addressing the reliability concerns common in safety-critical industries. -
20
KVM
Red Hat
KVM (for Kernel-based Virtual Machine) is a full virtualization solution for Linux on x86 hardware containing virtualization extensions (Intel VT or AMD-V). It consists of a loadable kernel module, kvm.ko, that provides the core virtualization infrastructure and a processor specific module, kvm-intel.ko or kvm-amd.ko. Using KVM, one can run multiple virtual machines running unmodified Linux or Windows images. Each virtual machine has private virtualized hardware: a network card, disk, graphics adapter, etc. KVM is open source software. The kernel component of KVM is included in mainline Linux, as of 2.6.20. The userspace component of KVM is included in mainline QEMU, as of 1.3. -
21
MatConvNet
VLFeat
The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. MatConvNet is a MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient, and can run and learn state-of-the-art CNNs. Many pre-trained CNNs for image classification, segmentation, face recognition, and text detection are available. -
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Intel Tiber AI Cloud
Intel
Intel® Tiber™ AI Cloud is a powerful platform designed to scale AI workloads with advanced computing resources. It offers specialized AI processors, such as the Intel Gaudi AI Processor and Max Series GPUs, to accelerate model training, inference, and deployment. Optimized for enterprise-level AI use cases, this cloud solution enables developers to build and fine-tune models with support for popular libraries like PyTorch. With flexible deployment options, secure private cloud solutions, and expert support, Intel Tiber™ ensures seamless integration, fast deployment, and enhanced model performance.Starting Price: Free -
23
Homebrew
Homebrew
The missing package manager for macOS (or Linux). The script explains what it will do and then pauses before it does it. Homebrew installs the stuff you need that Apple (or your Linux system) didn’t. Homebrew installs packages to their own directory and then symlinks their files into /usr/local (on macOS Intel). Homebrew won’t install files outside its prefix and you can place a Homebrew installation wherever you like. Trivially create your own Homebrew packages. It’s all Git and Ruby underneath, so hack away with the knowledge that you can easily revert your modifications and merge upstream updates. Homebrew formulae are simple Ruby scripts. Homebrew complements macOS (or your Linux system). Install your RubyGems with gem and their dependencies with brew. Homebrew Cask installs macOS apps, fonts and plugins and other non-open source software. Making a cask is as simple as creating a formula.Starting Price: Free -
24
NVIDIA TensorRT
NVIDIA
NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.Starting Price: Free -
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Lguest
Lguest
Lguest allows you to run multiple copies of the same 32-bit kernel, simply modprobe lg, then run Documentation/lguest/lguest to create a new guest. I suggest you try this yourself, lguest is incredibly easy to get up and running. It's also quite useful: I can test-boot kernels with it in less than a second, or about 10x faster than basic qemu, and 100x faster than a real boot. And as it uses a pty as console, you can do things like pipe it through grep. lguest is all one big kernel patch, including the launcher. It's in 2.6.23-git13 and above. Lguest aims to isolate the guest so it cannot reach outside to the host (except for virtual devices supplied by the host of course), even if the guest is malicious. However, a malicious guest kernel can currently pin host memory (up to the amount of memory allowed to the guest). Most images are set up to create a console virtual consoles (/dev/tty0 etc), but the lguest console is /dev/hvc0. -
26
Unsloth
Unsloth
Unsloth is an open source platform designed to accelerate and optimize the fine-tuning and training of Large Language Models (LLMs). It enables users to train custom models, such as ChatGPT, in just 24 hours instead of the typical 30 days, achieving speeds up to 30 times faster than Flash Attention 2 (FA2) while using 90% less memory. Unsloth supports both LoRA and QLoRA fine-tuning techniques, allowing for efficient customization of models like Mistral, Gemma, and Llama versions 1, 2, and 3. Unsloth's efficiency stems from manually deriving computationally intensive mathematical steps and handwriting GPU kernels, resulting in significant performance gains without requiring hardware modifications. Unsloth delivers a 10x speed increase on a single GPU and up to 32x on multi-GPU systems compared to FA2, with compatibility across NVIDIA GPUs from Tesla T4 to H100, and portability to AMD and Intel GPUs.Starting Price: Free -
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CoppeliaSim
Coppelia Robotics
CoppeliaSim, developed by Coppelia Robotics, is a versatile and powerful robot simulation platform utilized for rapid algorithm development, factory automation simulations, fast prototyping and verification, robotics education, remote monitoring, safety double-checking, and digital twin creation. It features a distributed control architecture, allowing each object or model to be individually controlled via embedded scripts (Python or Lua), plugins (C/C++), remote API clients (Python, Lua, Java, MATLAB, Octave, C, C++, Rust), or custom solutions. The simulator supports five physics engines, MuJoCo, Bullet Physics, ODE, Newton, and Vortex Dynamics, for fast and customizable dynamics calculations, enabling realistic simulation of real-world physics and object interactions, including collision response, grasping, soft bodies, strings, ropes, and cloths. CoppeliaSim provides forward and inverse kinematics calculations for any type of mechanism.Starting Price: $2,380 per year -
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Smelter
Software Mansion
Smelter is a real-time video compositing toolkit for low-latency multimedia composition in live streams and pre-recorded videos. It lets developers combine live feeds, screen recordings, pre-recorded videos, audio, embedded websites, text, graphics, animations, transitions, overlays, and custom shaders into a single video composition or live stream. Smelter is designed for use cases that demand immediate responsiveness, such as live streaming, broadcasting, video conferencing, interactive webinars, meetings, and production studios. It supports multiple sources at the same time without frame drops, allows layouts to change on the fly, and can mix or enrich video content, both live and offline, before saving the result as a file. The toolkit offers a browser-based experience that runs high-performance video processing with WASM and can leverage GPU rendering through WebGL or WebGPU. -
29
Bayesforge
Quantum Programming Studio
Bayesforge™ is a Linux machine image that curates the very best open source software for the data scientist who needs advanced analytical tools, as well as for quantum computing and computational mathematics practitioners who seek to work with one of the major QC frameworks. The image combines common machine learning frameworks, such as PyTorch and TensorFlow, with open source software from D-Wave, Rigetti as well as the IBM Quantum Experience and Google's new quantum computing language Cirq, as well as other advanced QC frameworks. For instance our quantum fog modeling framework, and our quantum compiler Qubiter which can cross-compile to all major architectures. All software is made accessible through the Jupyter WebUI which, due to its modular architecture, allows the user to code in Python, R, and Octave. -
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Dive
Dive
Dive CAE is a cloud-native computational fluid dynamics software platform that enables engineers to simulate complex fluid behaviors, such as free-surface flow, multiphase interactions, heat transfer, and moving machinery, using a mesh-free Smoothed Particle Hydrodynamics method. It runs entirely in the browser and on high-performance computing infrastructure, so users don’t need local hardware or installation. The mesh-free approach allows for modeling of complex geometry, surface tension, non-Newtonian fluids, and transient flows without the time-consuming meshing and tuning required by conventional CFD. Onboarding is fast (typically under one day), and the software supports parallel design-of-experiment workflows that deliver multiple iterations in hours rather than days. Dive CAE emphasizes collaboration, license simplicity (one licence for all users), transparent cost control, data usage governance, and scalability via cloud infrastructure. -
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Ansys Sherlock
Ansys
Ansys Sherlock is the only reliability physics-based electronics design tool that provides fast and accurate life predictions for electronic hardware at the component, board and system levels in early stage design. Ansys Sherlock automated design analysis provides fast and accurate life predictions for electronic hardware at the component, board and system levels in early design stages. Sherlock bypasses the ‘test-fail-fix-repeat’ cycle by empowering designers to accurately model silicon–metal layers, semiconductor packaging, printed circuit boards (PCBs) and assemblies to predict failure risks due to thermal, mechanical and manufacturing stressors--all before prototype. With embedded libraries containing over 500,000 parts, Sherlock rapidly converts electronic computer-aided design (ECAD) files into computational fluid dynamics (CFD) and finite element analysis (FEA) models. Each model contains accurate geometries, material properties and translates stress information. -
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Simcenter X
Siemens
Simcenter X is a cloud-powered multi-domain simulation suite from Siemens designed to help engineering teams accelerate innovation with flexible SaaS access. It brings together trusted Simcenter simulation applications with cloud deployment, high-performance computing, and scalable licensing. The platform supports CFD, mechanical, systems simulation, and MDAO tools so teams can work across multiple disciplines in one environment. Simcenter X helps reduce engineering silos by improving collaboration, data management, and cross-domain simulation workflows. Its centralized cloud-managed entitlements, universal tokens, and one-click HPC access make it easier to manage users, resources, and peak simulation workloads. With Simcenter X Advanced, organizations can simplify licensing, expand simulation capacity, and empower engineers to run complex studies more efficiently. -
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NVIDIA PhysicsNeMo
NVIDIA
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.Starting Price: Free -
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Inventor Nastran
Autodesk
CAD-embedded finite element analysis software. Use a wider variety of study types and materials in your analysis. Inventor® Nastran® delivers finite element analysis (FEA) tools for engineers and analysts. Simulation covers multiple analysis types, such as linear and nonlinear stress, dynamics, and heat transfer. Inventor Nastran is available only in the Product Design & Manufacturing Collection. The Product Design & Manufacturing Collection delivers tools that work right inside Inventor—including advanced simulation, 5-axis CAM, and nesting, plus AutoCAD and Fusion 360. -
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Shaders
Shaders
Shaders is a component-based library designed to bring GPU-accelerated visual effects directly into modern web applications, enabling developers and designers to create interactive, high-performance visuals using WebGPU in the browser. It provides a declarative system where users can compose effects such as animated backgrounds, image distortions, lighting effects, and dynamic UI elements as reusable components compatible with frameworks like React, Vue, Svelte, Solid, and vanilla JavaScript. It includes a visual design editor that allows users to experiment with effects in real time and then export clean, production-ready code that can be seamlessly integrated into frontend projects, reducing the need for low-level shader programming. It offers a growing library of presets and collections, allowing users to quickly implement complex visual styles such as gradients, holographic effects, liquid animations, and ASCII transformations without building them from scratch.Starting Price: $15 per month -
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RightNow AI
RightNow AI
RightNow AI is an AI-powered platform designed to automatically profile, detect bottlenecks, and optimize CUDA kernels for peak performance. It supports all major NVIDIA architectures, including Ampere, Hopper, Ada Lovelace, and Blackwell GPUs. It enables users to generate optimized CUDA kernels instantly using natural language prompts, eliminating the need for deep GPU expertise. With serverless GPU profiling, users can identify performance issues without relying on local hardware. RightNow AI replaces complex legacy optimization tools with a streamlined solution, offering features such as inference-time scaling and performance benchmarking. Trusted by leading AI and HPC teams worldwide, including Nvidia, Adobe, and Samsung, RightNow AI has demonstrated performance improvements ranging from 2x to 20x over standard implementations.Starting Price: $20 per month -
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NVIDIA FLARE
NVIDIA
NVIDIA FLARE (Federated Learning Application Runtime Environment) is an open source, extensible SDK designed to facilitate federated learning across diverse industries, including healthcare, finance, and automotive. It enables secure, privacy-preserving AI model training by allowing multiple parties to collaboratively train models without sharing raw data. FLARE supports various machine learning frameworks such as PyTorch, TensorFlow, RAPIDS, and XGBoost, making it adaptable to existing workflows. FLARE's componentized architecture allows for customization and scalability, supporting both horizontal and vertical federated learning. It is suitable for applications requiring data privacy and regulatory compliance, such as medical imaging and financial analytics. It is available for download via the NVIDIA NVFlare GitHub repository and PyPi.Starting Price: Free -
38
Refraction
Refraction
Refraction is a code-generation tool for developers. It uses AI to generate code for you. You can use it to generate unit tests, documentation, refactor code, and more. Generate code using AI in 34 languages — Assembly, C#, C++, CoffeeScript, CSS, Dart, Elixir, Erlang, Go, GraphQL, Groovy, Haskell, HTML, Java, JavaScript, Kotlin, LaTeX, Less, Lua, MatLab, Objective-C, OCaml, Perl, PHP, Python, R Lang, Ruby, Rust, Sass / SCSS, Scala, Shell, SQL, Swift, and TypeScript. Join thousands of developers around the world using Refraction to generate documentation, create unit tests, refactor code, and more using AI. Use the power of AI to automate the tedious parts of software development like testing, documentation, and refactoring, so you can focus on what matters. Refactor, optimize, fix and style-check your code. Generate unit tests for your code with various test frameworks. Explain the purpose of your code to make it easier to understand.Starting Price: $8 per month -
39
AWS Neuron
Amazon Web Services
It supports high-performance training on AWS Trainium-based Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances. For model deployment, it supports high-performance and low-latency inference on AWS Inferentia-based Amazon EC2 Inf1 instances and AWS Inferentia2-based Amazon EC2 Inf2 instances. With Neuron, you can use popular frameworks, such as TensorFlow and PyTorch, and optimally train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal code changes and without tie-in to vendor-specific solutions. AWS Neuron SDK, which supports Inferentia and Trainium accelerators, is natively integrated with PyTorch and TensorFlow. This integration ensures that you can continue using your existing workflows in these popular frameworks and get started with only a few lines of code changes. For distributed model training, the Neuron SDK supports libraries, such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP). -
40
WebLLM
WebLLM
WebLLM is a high-performance, in-browser language model inference engine that leverages WebGPU for hardware acceleration, enabling powerful LLM operations directly within web browsers without server-side processing. It offers full OpenAI API compatibility, allowing seamless integration with functionalities such as JSON mode, function-calling, and streaming. WebLLM natively supports a range of models, including Llama, Phi, Gemma, RedPajama, Mistral, and Qwen, making it versatile for various AI tasks. Users can easily integrate and deploy custom models in MLC format, adapting WebLLM to specific needs and scenarios. The platform facilitates plug-and-play integration through package managers like NPM and Yarn, or directly via CDN, complemented by comprehensive examples and a modular design for connecting with UI components. It supports streaming chat completions for real-time output generation, enhancing interactive applications like chatbots and virtual assistants.Starting Price: Free -
41
DeepSpeed
Microsoft
DeepSpeed is an open source deep learning optimization library for PyTorch. It's designed to reduce computing power and memory use, and to train large distributed models with better parallelism on existing computer hardware. DeepSpeed is optimized for low latency, high throughput training. DeepSpeed can train DL models with over a hundred billion parameters on the current generation of GPU clusters. It can also train up to 13 billion parameters in a single GPU. DeepSpeed is developed by Microsoft and aims to offer distributed training for large-scale models. It's built on top of PyTorch, which specializes in data parallelism.Starting Price: Free -
42
Embedded Linux
Canonical
Developers are much more productive on Ubuntu than handcrafted embedded Linux. Sharing a platform shares the cost. Licensing is cheaper, updates more tested and maintenance shared. Familiar and widely used Ubuntu means easy CI/CD, better tools, faster updates and better kernels. Linux is not a differentiator. Use pre-enabled boards and focus on software unique to your story. Managing a familiar environment and platform is easier and cheaper than a specialist OS. Naturally. More Linux developers choose Ubuntu, so the talent pool is deeper and broader. Tap the biggest talent pool. Ubuntu is ahead of the pack by every measure. Productivity starts with reuse. Accelerate developers with the world’s largest package selection. -
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FreeRTOS
FreeRTOS
Developed in partnership with the world’s leading chip companies over a 15-year period, and now downloaded every 170 seconds, FreeRTOS is a market-leading real-time operating system (RTOS) for microcontrollers and small microprocessors. Distributed freely under the MIT open source license, FreeRTOS includes a kernel and a growing set of IoT libraries suitable for use across all industry sectors. FreeRTOS is built with an emphasis on reliability and ease of use. With proven robustness, tiny footprint, and wide device support, the FreeRTOS kernel is trusted by world-leading companies as the de facto standard for microcontrollers and small microprocessors. With detailed pre-configured demos and Internet of Things (IoT) reference integrations, there is no need to determine how to setup a project. Quickly download, compile, and get to market faster. Our partner ecosystem provides a breadth of options including community contributions and professional support. -
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PlantFCE Model Builder
Storm Consulting
Customize models, refine designs, and export with precision. PlantFCE Model Builder offers intuitive 3D modeling for process plants. Model Builder is useful when estimating costs for an engineering project. View real-time updates in the rendering window as you edit the scene. Low lock-in with PlantFCE Model Builder* Model Builder allows you to import and export 3D models from and to industry-standard 3D model formats like GLB, OBJ, and STL. With an automatic clash check, reduce errors and save time.** PlantFCE Model Builder's automatic clash check** reduces time spent on clash check sessions and gives you more time to work on your project. Download for Windows and Mac on the PlantFCE website. *Exporting through Model Builder does not include Model Builder specific functionality like properties set on objects or features specific to Model Builder. **Clash check will be released in version 2.Starting Price: $49/month/user -
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LTE MAC Lab
IS Wireless
LTE MAC Lab is a system-level simulation tool running under Matlab. LTE MAC Lab allows customers to model a wireless LTE network deployment, analyse its performance and understand dynamic mechanisms of the radio interface. It reflects the dynamic behaviour of a modelled HetNet RAN (Figure 1) focusing on Radio Resource Management features such as scheduling, carrier aggregation, handovers and link adaptation. It includes implementation of propagation (path loss, shadowing and multipath) and mobility models. -
46
Three.js
Three.js
Three.js is a JavaScript 3D library. The aim of the project is to create an easy-to-use, lightweight, cross-browser, general-purpose 3D library. The current builds only include a WebGL renderer but WebGPU (experimental), SVG and CSS3D renderers are also available in the examples. To actually be able to display anything with three.js, we need three things, scene, camera, and renderer, so that we can render the scene with the camera. In addition to the WebGLRenderer, Three.js comes with a few others, often used as fallbacks for users with older browsers or for those who don't have WebGL support for some reason. Create a loop that causes the renderer to draw the scene every time the screen is refreshed (on a typical screen this means 60 times per second). Anything you want to move or change while the app is running has to go through the animate loop. You can of course call other functions from there.Starting Price: Free -
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IREN Cloud
IREN
IREN’s AI Cloud is a GPU-cloud platform built on NVIDIA reference architecture and non-blocking 3.2 TB/s InfiniBand networking, offering bare-metal GPU clusters designed for high-performance AI training and inference workloads. The service supports a range of NVIDIA GPU models with specifications such as large amounts of RAM, vCPUs, and NVMe storage. The cloud is fully integrated and vertically controlled by IREN, giving clients operational flexibility, reliability, and 24/7 in-house support. Users can monitor performance metrics, optimize GPU spend, and maintain secure, isolated environments with private networking and tenant separation. It allows deployment of users’ own data, models, frameworks (TensorFlow, PyTorch, JAX), and container technologies (Docker, Apptainer) with root access and no restrictions. It is optimized to scale for demanding applications, including fine-tuning large language models. -
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nTop Platform
nTopology
Engineering software built for digital manufacturing The way we build parts has changed. Your engineering software needs to change too. A unifying technique for design, simulation, and manufacturing data. The nTop Platform approach removes geometry bottlenecks in design by achieving more efficient workflows, dramatically improving team collaboration with faster iteration, enabling smarter, more complex designs to meet performance demands. By utilizing nTop Platform’s breakthrough computational modeling techniques, design teams can process and evaluate more design concepts than ever before. Find the most optimal solution in a shorter amount of time. At nTopology we know that your engineering know-how is the most valuable asset in your organization. nTop Platform makes that know-how accessible, shareable and, most importantly, secure across your entire organization. -
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Edera
Edera
Introducing secure-by-design AI and Kubernetes no matter where you run your infrastructure. Eliminate container escapes and put a security boundary around Kubernetes workloads. Simplify running AI/ML workloads through enhanced GPU device virtualization, driver isolation, and vGPUs. Edera Krata begins a new paradigm of isolation technology, ushering in a new era of security. Edera brings a new era of AI & GPU security and performance, while also integrating seamlessly with Kubernetes. Each container receives its own Linux kernel, eliminating a shared kernel state between containers. Which means goodbye container escapes, costly security tool layering, and long days doom scrolling logs. Run Edera Protect with just a couple lines of YAML and you’re off to the races. It’s written in Rust for enhanced memory safety and has no performance impact. A secure-by-design Kubernetes solution that stops attackers in their tracks. -
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Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
