RECRUIT

Reducing Energy Consumption in Radio-astronomical and Ultrasound Imaging Tools

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When it comes to algorithms, technologies, and energy constraints, imaging efforts in radio astronomy and medical ultrasound share fundamentally similar challenges; both near the edge and further downstream in processing pipelines. Although time and space scales are orders of magnitude apart, the associated data processing and enabling hardware to image galaxy or brain both share the common requirements. That is, they must be processed in a local, real-time, and energy-efficient way. In this project, ASTRON (the Netherlands Institute for Radio Astronomy) and CUBE (the Center for Ultrasound and Brain imaging at Erasmus MC) join forces to tackle HPC and energy-efficiency challenges by utilizing new technologies and algorithmic improvements. The Adaptive Compute Acceleration Platform by Xilinx and Tensor Cores in NVIDIA GPUs are top examples of such enabling technologies. This project will unlock the potential of these highly-efficient technologies for use in radio astronomy and ultrasound brain imaging, delivering open-source libraries, innovation in limited-precision algorithms, and will develop a new tool to analyze energy efficiency. Ultimately, this will allow more (energy) efficient instruments to be built.

Participating organisations

ASTRON
Erasmus University Medical Center
Netherlands eScience Center

Impact

Output

Team

Contact person

Ben van Werkhoven

Ben van Werkhoven

Netherlands eScience Center
Mail Ben
Ben van Werkhoven
Ben van Werkhoven
Lead RSE
Netherlands eScience Center
Bouwe Andela
Bouwe Andela
eScience Research Engineer
Netherlands eScience Center
CS
Christos Strydis
JR
John Romein
Principal investigator
ASTRON
Leon Oostrum
Leon Oostrum
eScience Research Engineer
Netherlands eScience Center
LV
Luuk Verhoef
PhD Student
Erasmus MC
PK
Pieter Kruizinga
Co-applicant
Erasmus MC
Rena Bakhshi
Rena Bakhshi
Programme Manager
Netherlands eScience Center

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