Government
Accelerating Government Research and Development
Julia’s high-performance capabilities, native parallelism, and GPU support allow agencies like NASA, US Air Force, ARPA-E and DARPA to gain critical insight in government-funded R&D, accelerate mission-critical tasks and enable real-time decision-making
Government
Accelerating Government Research and Development
Julia’s high-performance capabilities, native parallelism, and GPU support allow agencies like NASA, US Air Force, ARPA-E and DARPA to gain critical insight in government-funded R&D, accelerate mission-critical tasks and enable real-time decision-making
Government
Accelerating Government Research and Development
Julia’s high-performance capabilities, native parallelism, and GPU support allow agencies like NASA, US Air Force, ARPA-E and DARPA to gain critical insight in government-funded R&D, accelerate mission-critical tasks and enable real-time decision-making
Services
Mission-Critical Development Services
JuliaHub offers a range of specialized software development services to support government research and development (R&D) efforts.
Services
Mission-Critical Development Services
JuliaHub offers a range of specialized software development services to support government research and development (R&D) efforts.
Services
Mission-Critical Development Services
JuliaHub offers a range of specialized software development services to support government research and development (R&D) efforts.
Custom Projects
Partner with Julia's creators to develop custom solutions for your most challenging government R&D projects
Digital Twin Development
Custom digital twin solutions that mirror real-world systems for predictive maintenance, mission planning, and operational optimization across defense assets and critical infrastructure.
Digital Twin Development
Custom digital twin solutions that mirror real-world systems for predictive maintenance, mission planning, and operational optimization across defense assets and critical infrastructure.
Digital Twin Development
Custom digital twin solutions that mirror real-world systems for predictive maintenance, mission planning, and operational optimization across defense assets and critical infrastructure.
High-Performance Simulation & Modeling
JuliaHub’s custom development services, powered by Dyad, enable faster and more accurate simulations across sectors like aerospace, defense, and energy. This capability reduces development cycles and helps in creating precise models for real-time decision-making.
High-Performance Simulation & Modeling
JuliaHub’s custom development services, powered by Dyad, enable faster and more accurate simulations across sectors like aerospace, defense, and energy. This capability reduces development cycles and helps in creating precise models for real-time decision-making.
High-Performance Simulation & Modeling
JuliaHub’s custom development services, powered by Dyad, enable faster and more accurate simulations across sectors like aerospace, defense, and energy. This capability reduces development cycles and helps in creating precise models for real-time decision-making.
Advanced Machine Learning Integration
Through SciML, JuliaHub integrates cutting-edge machine learning techniques with scientific computing, enabling government researchers to tackle complex predictive modeling and optimization challenges more effectively.
Advanced Machine Learning Integration
Through SciML, JuliaHub integrates cutting-edge machine learning techniques with scientific computing, enabling government researchers to tackle complex predictive modeling and optimization challenges more effectively.
Advanced Machine Learning Integration
Through SciML, JuliaHub integrates cutting-edge machine learning techniques with scientific computing, enabling government researchers to tackle complex predictive modeling and optimization challenges more effectively.
Secure Data Analysis and Visualization
JuliaHub supports government R&D by offering powerful tools for data analysis and visualization, enabling researchers to derive insights from vast datasets efficiently. This allows for better-informed decision-making in projects related to national security, healthcare, and environmental monitoring.
Secure Data Analysis and Visualization
JuliaHub supports government R&D by offering powerful tools for data analysis and visualization, enabling researchers to derive insights from vast datasets efficiently. This allows for better-informed decision-making in projects related to national security, healthcare, and environmental monitoring.
Secure Data Analysis and Visualization
JuliaHub supports government R&D by offering powerful tools for data analysis and visualization, enabling researchers to derive insights from vast datasets efficiently. This allows for better-informed decision-making in projects related to national security, healthcare, and environmental monitoring.
Proven Success
Over $25M in successful R&D contracts with NASA, DARPA, DOE, Air Force, and Office of Naval Research
NASA
Custom digital twin solutions that mirror real-world systems for predictive maintenance, mission planning, and operational optimization across defense assets and critical infrastructure.
NASA
Custom digital twin solutions that mirror real-world systems for predictive maintenance, mission planning, and operational optimization across defense assets and critical infrastructure.
NASA
Custom digital twin solutions that mirror real-world systems for predictive maintenance, mission planning, and operational optimization across defense assets and critical infrastructure.
Defense Advanced Research & Projects Agency (DARPA)
JuliaHub’s custom development services, powered by Dyad, enable faster and more accurate simulations across sectors like aerospace, defense, and energy. This capability reduces development cycles and helps in creating precise models for real-time decision-making.
Defense Advanced Research & Projects Agency (DARPA)
JuliaHub’s custom development services, powered by Dyad, enable faster and more accurate simulations across sectors like aerospace, defense, and energy. This capability reduces development cycles and helps in creating precise models for real-time decision-making.
Defense Advanced Research & Projects Agency (DARPA)
JuliaHub’s custom development services, powered by Dyad, enable faster and more accurate simulations across sectors like aerospace, defense, and energy. This capability reduces development cycles and helps in creating precise models for real-time decision-making.
Department of Energy (DOE)
Through SciML, JuliaHub integrates cutting-edge machine learning techniques with scientific computing, enabling government researchers to tackle complex predictive modeling and optimization challenges more effectively.
Department of Energy (DOE)
Through SciML, JuliaHub integrates cutting-edge machine learning techniques with scientific computing, enabling government researchers to tackle complex predictive modeling and optimization challenges more effectively.
Department of Energy (DOE)
Through SciML, JuliaHub integrates cutting-edge machine learning techniques with scientific computing, enabling government researchers to tackle complex predictive modeling and optimization challenges more effectively.
US Air Force Research Labs
The U.S. AFRL's Intelligent Control and Evaluation of Teams flight test program flew an uncrewed aerial system in coordination with ground systems to provide aerial support in virtually contested environments. The UAS was able to plan and execute missions autonomously using onboard hardware programmed in Julia.
US Air Force Research Labs
The U.S. AFRL's Intelligent Control and Evaluation of Teams flight test program flew an uncrewed aerial system in coordination with ground systems to provide aerial support in virtually contested environments. The UAS was able to plan and execute missions autonomously using onboard hardware programmed in Julia.
US Air Force Research Labs
The U.S. AFRL's Intelligent Control and Evaluation of Teams flight test program flew an uncrewed aerial system in coordination with ground systems to provide aerial support in virtually contested environments. The UAS was able to plan and execute missions autonomously using onboard hardware programmed in Julia.
JuliaHub Air
JuliaHub Air for Secure Computing Environments
Deploy secure, high-performance computing in air-gapped environments with JuliaHub Air
JuliaHub Air
JuliaHub Air for Secure Computing Environments
Deploy secure, high-performance computing in air-gapped environments with JuliaHub Air
JuliaHub Air
JuliaHub Air for Secure Computing Environments
Deploy secure, high-performance computing in air-gapped environments with JuliaHub Air
Purpose-Built for Government Security
JuliaHub Air operates in air-gapped environments with stringent security requirements, facilitating rapid Authority to Operate (ATO) approval while ensuring confidentiality and integrity of sensitive data and computational processes.
Purpose-Built for Government Security
JuliaHub Air operates in air-gapped environments with stringent security requirements, facilitating rapid Authority to Operate (ATO) approval while ensuring confidentiality and integrity of sensitive data and computational processes.
Purpose-Built for Government Security
JuliaHub Air operates in air-gapped environments with stringent security requirements, facilitating rapid Authority to Operate (ATO) approval while ensuring confidentiality and integrity of sensitive data and computational processes.
Skip Expensive Cloud Certification
Avoid lengthy and expensive commercial cloud computing authorization processes like FedRAMP and DoD ILS that typically result in substantial deployment delays.
Skip Expensive Cloud Certification
Avoid lengthy and expensive commercial cloud computing authorization processes like FedRAMP and DoD ILS that typically result in substantial deployment delays.
Skip Expensive Cloud Certification
Avoid lengthy and expensive commercial cloud computing authorization processes like FedRAMP and DoD ILS that typically result in substantial deployment delays.
Flexible Deployment Options
Install seamlessly on AWS GovCloud or on-premises HPC assets (including GPU clusters) with comprehensive documentation and rigorous testing procedures designed to expedite the ATO process.
Flexible Deployment Options
Install seamlessly on AWS GovCloud or on-premises HPC assets (including GPU clusters) with comprehensive documentation and rigorous testing procedures designed to expedite the ATO process.
Flexible Deployment Options
Install seamlessly on AWS GovCloud or on-premises HPC assets (including GPU clusters) with comprehensive documentation and rigorous testing procedures designed to expedite the ATO process.
Enterprise-Ready Architecture
Self-contained Kubernetes package server that deploys Julia applications based on specific mission needs and priorities, offering the full power of JuliaHub in completely isolated environments.
Enterprise-Ready Architecture
Self-contained Kubernetes package server that deploys Julia applications based on specific mission needs and priorities, offering the full power of JuliaHub in completely isolated environments.
Enterprise-Ready Architecture
Self-contained Kubernetes package server that deploys Julia applications based on specific mission needs and priorities, offering the full power of JuliaHub in completely isolated environments.
Proven Government Applications
Ideal for simulation and modeling with digital twins, scientific machine learning, geospatial processing, flight test data analysis, and natural language processing.
Proven Government Applications
Ideal for simulation and modeling with digital twins, scientific machine learning, geospatial processing, flight test data analysis, and natural language processing.
Proven Government Applications
Ideal for simulation and modeling with digital twins, scientific machine learning, geospatial processing, flight test data analysis, and natural language processing.
Powered by Julia: the Standard for technical and scientific computing
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Powered by Julia: the Standard for technical and scientific computing
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Powered by Julia: the Standard for technical and scientific computing
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Case Studies
Trusted by Government Thought Leaders
Over the past 7 years, Julia has secured over $25M in grants and R&D contracts from prestigious government entities such as the NSF, NASA, DARPA, DOE, ARPA-E, IARPA, DoD, the Air Force, and the Office of Naval Research.
Case Studies
Trusted by Government Thought Leaders
Over the past 7 years, Julia has secured over $25M in grants and R&D contracts from prestigious government entities such as the NSF, NASA, DARPA, DOE, ARPA-E, IARPA, DoD, the Air Force, and the Office of Naval Research.
Case Studies
Trusted by Government Thought Leaders
Over the past 7 years, Julia has secured over $25M in grants and R&D contracts from prestigious government entities such as the NSF, NASA, DARPA, DOE, ARPA-E, IARPA, DoD, the Air Force, and the Office of Naval Research.
Dyad
Enabling Software-Defined Machines and Digital Twins
Dyad redefines hardware design with an acausal modeling language and integrated Scientific AI. Create living digital twins for rapid iteration, seamless deployment, and enhanced control of physical systems.
Dyad
Enabling Software-Defined Machines and Digital Twins
Dyad redefines hardware design with an acausal modeling language and integrated Scientific AI. Create living digital twins for rapid iteration, seamless deployment, and enhanced control of physical systems.
Dyad
Enabling Software-Defined Machines and Digital Twins
Dyad redefines hardware design with an acausal modeling language and integrated Scientific AI. Create living digital twins for rapid iteration, seamless deployment, and enhanced control of physical systems.
Unified Acausal Modeling Language
Utilize the Dyad Modeling Language for acausal, object-oriented modeling, enabling seamless workflows between graphical user interfaces and Julia code. It integrates physics-based modeling with SciML for comprehensive digital twin development.
Rapid Iteration & Deployment
Accelerate design cycles and facilitate rapid deployments for over-the-air updates, enabling agile workflows in industrial engineering. Dyad supports the entire product lifecycle from fast prototyping to production deployment.
Living Digital Twins
Develop digital twins that continuously evolve via streaming data and Scientific AI. This transforms modeling workflows by enabling autonomously improving models in the cloud, with SciML-native primitives for discovery and data integration.
Bridging Engineering & Development
Break down silos by uniting engineers and developers on a single source of truth, fostering seamless collaboration across the product lifecycle. Dyad promotes robust software engineering principles for scalable projects.
Open and Extensible Ecosystem
Dyad offers a flexible, open environment. Its toolchain is largely source-available and integrates with Julia for imperative calculations. Dyad Studio and Dyad Builder provide flexible model development and analysis.
Advanced Simulation Acceleration
Accelerate simulation with surrogate modeling for faster, data-driven approximations. Enhance design via optimization, including Uncertainty-Quantified Calibration and Universal Differential Equations for physics discovery.
Unified Acausal Modeling Language
Utilize the Dyad Modeling Language for acausal, object-oriented modeling, enabling seamless workflows between graphical user interfaces and Julia code. It integrates physics-based modeling with SciML for comprehensive digital twin development.
Rapid Iteration & Deployment
Accelerate design cycles and facilitate rapid deployments for over-the-air updates, enabling agile workflows in industrial engineering. Dyad supports the entire product lifecycle from fast prototyping to production deployment.
Living Digital Twins
Develop digital twins that continuously evolve via streaming data and Scientific AI. This transforms modeling workflows by enabling autonomously improving models in the cloud, with SciML-native primitives for discovery and data integration.
Bridging Engineering & Development
Break down silos by uniting engineers and developers on a single source of truth, fostering seamless collaboration across the product lifecycle. Dyad promotes robust software engineering principles for scalable projects.
Open and Extensible Ecosystem
Dyad offers a flexible, open environment. Its toolchain is largely source-available and integrates with Julia for imperative calculations. Dyad Studio and Dyad Builder provide flexible model development and analysis.
Advanced Simulation Acceleration
Accelerate simulation with surrogate modeling for faster, data-driven approximations. Enhance design via optimization, including Uncertainty-Quantified Calibration and Universal Differential Equations for physics discovery.
Unified Acausal Modeling Language
Utilize the Dyad Modeling Language for acausal, object-oriented modeling, enabling seamless workflows between graphical user interfaces and Julia code. It integrates physics-based modeling with SciML for comprehensive digital twin development.
Rapid Iteration & Deployment
Accelerate design cycles and facilitate rapid deployments for over-the-air updates, enabling agile workflows in industrial engineering. Dyad supports the entire product lifecycle from fast prototyping to production deployment.
Living Digital Twins
Develop digital twins that continuously evolve via streaming data and Scientific AI. This transforms modeling workflows by enabling autonomously improving models in the cloud, with SciML-native primitives for discovery and data integration.
Bridging Engineering & Development
Break down silos by uniting engineers and developers on a single source of truth, fostering seamless collaboration across the product lifecycle. Dyad promotes robust software engineering principles for scalable projects.
Open and Extensible Ecosystem
Dyad offers a flexible, open environment. Its toolchain is largely source-available and integrates with Julia for imperative calculations. Dyad Studio and Dyad Builder provide flexible model development and analysis.
Advanced Simulation Acceleration
Accelerate simulation with surrogate modeling for faster, data-driven approximations. Enhance design via optimization, including Uncertainty-Quantified Calibration and Universal Differential Equations for physics discovery.
JuliaHub
The Platform for High-Performance Scientific Computing
JuliaHub provides a secure, cloud-native environment for advanced scientific computing and AI. Empowering engineers to develop, scale, and deploy complex simulations and models with speed and collaboration.
JuliaHub
The Platform for High-Performance Scientific Computing
JuliaHub provides a secure, cloud-native environment for advanced scientific computing and AI. Empowering engineers to develop, scale, and deploy complex simulations and models with speed and collaboration.
JuliaHub
The Platform for High-Performance Scientific Computing
JuliaHub provides a secure, cloud-native environment for advanced scientific computing and AI. Empowering engineers to develop, scale, and deploy complex simulations and models with speed and collaboration.
Cloud-Native Architecture
Access a fully integrated, cloud-hosted environment with JuliaIDE and Pluto Notebooks for interactive development, debugging, and experimentation. Develop locally with the JuliaHub VS Code extension and execute in the cloud.
Scalable & Parallel Computing
Leverage the power of Julia for high-performance computing, with built-in support for composable multi-threading, distributed computing, and GPU acceleration. Effortlessly scale your computations from a single CPU/GPU instance to a cluster of machines.
Reproducibility & Traceability
Ensure the integrity of your work with automatic saving of batch jobs, persistent file systems, and Git-based version control for all code and data. Time Capsules allow you to re-run old jobs with the exact same environment and settings, crucial for regulatory compliance.
Seamless Collaboration
Facilitate team-based development with Projects, offering shared workspaces, granular access controls, and integrated version control (Git) for code, data, and notebooks. Streamline workflows and accelerate joint research and development efforts.
Package and Registry Management
Utilize a dedicated package server for both public and private packages, ensuring control over dependencies and promoting the use of secure, patched versions across your organization.
Application Deployment & Hosting
Easily build and deploy interactive Julia applications and dashboards, with support for bare Kubernetes deployments to various cloud or on-premise infrastructures.
Cloud-Native Architecture
Access a fully integrated, cloud-hosted environment with JuliaIDE and Pluto Notebooks for interactive development, debugging, and experimentation. Develop locally with the JuliaHub VS Code extension and execute in the cloud.
Scalable & Parallel Computing
Leverage the power of Julia for high-performance computing, with built-in support for composable multi-threading, distributed computing, and GPU acceleration. Effortlessly scale your computations from a single CPU/GPU instance to a cluster of machines.
Reproducibility & Traceability
Ensure the integrity of your work with automatic saving of batch jobs, persistent file systems, and Git-based version control for all code and data. Time Capsules allow you to re-run old jobs with the exact same environment and settings, crucial for regulatory compliance.
Seamless Collaboration
Facilitate team-based development with Projects, offering shared workspaces, granular access controls, and integrated version control (Git) for code, data, and notebooks. Streamline workflows and accelerate joint research and development efforts.
Package and Registry Management
Utilize a dedicated package server for both public and private packages, ensuring control over dependencies and promoting the use of secure, patched versions across your organization.
Application Deployment & Hosting
Easily build and deploy interactive Julia applications and dashboards, with support for bare Kubernetes deployments to various cloud or on-premise infrastructures.
Cloud-Native Architecture
Access a fully integrated, cloud-hosted environment with JuliaIDE and Pluto Notebooks for interactive development, debugging, and experimentation. Develop locally with the JuliaHub VS Code extension and execute in the cloud.
Scalable & Parallel Computing
Leverage the power of Julia for high-performance computing, with built-in support for composable multi-threading, distributed computing, and GPU acceleration. Effortlessly scale your computations from a single CPU/GPU instance to a cluster of machines.
Reproducibility & Traceability
Ensure the integrity of your work with automatic saving of batch jobs, persistent file systems, and Git-based version control for all code and data. Time Capsules allow you to re-run old jobs with the exact same environment and settings, crucial for regulatory compliance.
Seamless Collaboration
Facilitate team-based development with Projects, offering shared workspaces, granular access controls, and integrated version control (Git) for code, data, and notebooks. Streamline workflows and accelerate joint research and development efforts.
Package and Registry Management
Utilize a dedicated package server for both public and private packages, ensuring control over dependencies and promoting the use of secure, patched versions across your organization.
Application Deployment & Hosting
Easily build and deploy interactive Julia applications and dashboards, with support for bare Kubernetes deployments to various cloud or on-premise infrastructures.
Contact Sales
Learn about our products, pricing, implementation, and how JuliaHub can help your business
We’ll use your information to respond to your inquiry and, if applicable, classify your interest for relevant follow-up regarding our products. If you'd like to receive our newsletter and product updates, please check the box above. You can unsubscribe at any time. Learn more in our Privacy Policy.
Get a Demo
Discover how Dyad, JuliaHub, and Pumas can improve your modeling and simulation workflows.
Enterprise Support
Leverage our developers, engineers and data scientists to help you build new solutions.
Custom Solutions
Have a complex setup that needs a custom solution? We are here to help.
Contact Sales
Learn about our products, pricing, implementation, and how JuliaHub can help your business
We’ll use your information to respond to your inquiry and, if applicable, classify your interest for relevant follow-up regarding our products. If you'd like to receive our newsletter and product updates, please check the box above. You can unsubscribe at any time. Learn more in our Privacy Policy.
Get a Demo
Discover how Dyad, JuliaHub, and Pumas can improve your modeling and simulation workflows.
Enterprise Support
Leverage our developers, engineers and data scientists to help you build new solutions.
Custom Solutions
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