Autonomous Data Acquisition, Uncertainty Quantification and HPC Optimization

gpCAM is powered by


The Center for Advanced Mathematics for Energy Research Applications

Mission of the project

gpCAM is an API and software designed to make autonomous data acquisition and analysis for experiments and simulations faster, simpler and more widely available. The tool is based on a flexible and powerful Gaussian process regression at the core. The flexibility stems from the modular design of gpCAM which allows the user to implement and import their own Python functions to customize and control almost every aspect of the software. That makes it possible to easily tune the algorithm to account for various kinds of physics and other domain knowledge, and to identify and find interesting features. A specialized function optimizer in gpCAM can take advantage of HPC architectures for fast analysis time and reactive autonomous data acquisition.

Simple API

The API is designed in a way that makes it easy to be used

Powerful Computing

gpCAM is implemented using torch and DASK for fast training and predictions

Advanced Mathematics for Increased Flexibility

gpCAM allows the advanced user to import their own Python functions to control the training and prediction

Software for the Novice and the Expert

For users not familiar with Python, gpCAM can be run without doing any Python coding at all


Contact to get more information on the project. We also encourage you to join the SLACK channel.

Want to transform your science with autonomous data acquisition?

gpCAM is a software tool created by CAMERA

The Center for Advanced Mathematics for Energy Research Application


Supported by the US Department of Energy Office of Science

Advanced Scientific Computing Research (

Basic Energy Sciences (