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CyberCompute - An Extensible Platform for Computational Experiments

Functionality

  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.

System Design

  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error

Terminology

Model

Engine

Parameters

Inputs of scientific interest to an experiment

  • initial values for ODE
  • weights of inference-mode NNs

Observables

Outputs of scientific interest from an experiment

  • variables (e.g. time)
  • constants (e.g., total energy)

Examples

Astrophysics

Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?

Neuroscience

Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?

Computational Physics

Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?

Roadmap

  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)

About

Define and Run Computational Experiments on Cybershuttle

cybershuttle.org

Topics

airavatacomputational-sciencesexperimentationframework

Resources

Readme
Activity

Stars

1 star

Watchers

1 watching

Forks

0 forks
Report repository

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Repository files navigation
CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
About
Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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Used by
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Repository files navigation
CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
About
Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
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Repository files navigation
CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
About
Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
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Repository files navigation
CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
About
Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
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Repository files navigation
CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
About
Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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Used by
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GitHub - yasithdev/cybercomp: Define and Run Computational Experiments on Cybershuttle · GitHub
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environment.yml
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pyproject.toml
Repository files navigation
CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
About
Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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CyberCompute - An Extensible Platform for Computational Experiments
Functionality
  • Searching computational models and execution engines registered in cybercompute.
  • Defining experiments by coupling computational models with execution engines, and defining their choice of parameter values.
  • Defining larger experiments through composition of smaller experiments.
  • Defining experiment collections by grouping a set of experiments with common observables.
  • Comparing and contrasting observables within/across experiment collections.
System Design
  • System should find which systems out of N systems are compatible, and suggest them to users
  • System should type-match parameters/observables when coupling models and engines, and when composing larger experiments.
  • system should validate first (before execution) and throw error
Terminology
Model
Engine
Parameters
Inputs of scientific interest to an experiment
  • initial values for ODE
  • weights of inference-mode NNs
Observables
Outputs of scientific interest from an experiment
  • variables (e.g. time)
  • constants (e.g., total energy)
Examples
Astrophysics
Q: Given a "solar system" with "parameters" and "initial conditions", what is the gravitational force X between planet X and planet Y at time T?
Neuroscience
Q: Given a "neuronal network" with "parameters" "initial conditions", when does neuron X exhibit a membrane voltage < Y?
Computational Physics
Q: Given a "double pendulum" with "parameters" and "initial conditions", what is the trajectory (X, Y) followed by the second bob?
Roadmap
  1. Neuroscience (Giri)
  2. Deep Learning (Giri, Chris)
  3. Quantum Chemistry (Sudhakar)
  4. Geoscience (Dimuthu)
  5. Molecular Dynamics (Sudhakar)
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Define and Run Computational Experiments on Cybershuttle
cybershuttle.org
Topics
airavatacomputational-sciencesexperimentationframework
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