Fraunhofer Institute for Industrial Mathematics ITWM

Conference

Conference, Houston, Texas, USA / February 24, 2026 - February 26, 2026

Energy High Performance Computing and AI Conference

The annual conference, taking place at Rice University in Houston, Texas, is the premier meeting place for professionals to network with experts from industry, academia, national labs and IT. Here, challenges, opportunities and new developments at the interface of the energy industry, IT and the research community are discussed in order to advance HPC and AI in the energy sector.

Our expert Dr. Franz-Josef Pfreundt, Chief Strategy Officer of the »High Performance Computing« department in the »Analytics and Computing« division, is on site.

Event details

Program

Here you can find the complete program.

Our Contribution

Our experts from the »High Performance Computing« department will present four projects at the event.

Deep Learning for Large Seismic Applications (DLseis) deals with basic research through to ready-to-use deep learning tools for seismic applications.
Carme combines machine learning with HPC back-end. The open-source multi-user software stack Carme stands for interactive machine learning.
Stencil and Tensor Accelerator (STX) relies on hardware-software co-design and open source to strengthen key technologies in Europe.
NASE is a framework for automatic search and multidimensional optimization of neural network architectures for DNNs and SNNs that generates efficient models while taking hardware, performance, and energy requirements into account.

Registration

You can register here on the external website of the event.

Location

Houston, Texas, USA
Rice University by the Ken Kennedy Institute

Date

February 24, 2026 - February 26, 2026

Download this event as iCal

Language

English

Key Topics

DLSeis

The project »Deep Learning for Large Seismic Applications« (DLseis) deals with basic research up to ready-to-use deep learning tools for seismic applications.

Carme

With the open source multi-user software stack Carme, several users can manage the available resources of a computing cluster.

Energy-Efficient Supercomputer Systems

The Stencil and Tensor Accelerator (STX) relies on hardware-software co-design and open source to strengthen key technologies such as system design in Europe.

Multi-Target Neural Architecture Optimization

AI-Services: NASE – Neural Architecture Search Engine

We support you in designing and integrating your optimal, individual neural network.