Project Details
Description
The European Council for Nuclear Research (CERN) has made many fundamental discoveries
since its creation in 1952. The applications of those discoveries range from the technology behind
touch screens that are ubiquitous today, to the protocol used to share webpages on the Internet.
CERN's subatomic research requires the collision of nuclei at high speeds in specialized devices.
One of these devices is the Large Hadron Collider (LHC), which contains multiple detectors for
particles and their associated dynamics. In 2022, CONARE was approved for incorporation as a
full member of the LHCb collaboration, which opens a great opportunity to interact with CERN
scientists in the quest to understand the nature of the universe. This situation is strategic because
the LHCb experiment has just updated its detectors, allowing the collection of an enormous
amount of data that must be processed. This processing has historically been done on traditional
processors (CPU), but there is enormous interest in using graphics processing cards (GPU) that
offer a better balance between computing power and energy. This project proposes the
reimplementation of several algorithms used in LHCb data processing for GPUs and their
optimization on the new platform.
since its creation in 1952. The applications of those discoveries range from the technology behind
touch screens that are ubiquitous today, to the protocol used to share webpages on the Internet.
CERN's subatomic research requires the collision of nuclei at high speeds in specialized devices.
One of these devices is the Large Hadron Collider (LHC), which contains multiple detectors for
particles and their associated dynamics. In 2022, CONARE was approved for incorporation as a
full member of the LHCb collaboration, which opens a great opportunity to interact with CERN
scientists in the quest to understand the nature of the universe. This situation is strategic because
the LHCb experiment has just updated its detectors, allowing the collection of an enormous
amount of data that must be processed. This processing has historically been done on traditional
processors (CPU), but there is enormous interest in using graphics processing cards (GPU) that
offer a better balance between computing power and energy. This project proposes the
reimplementation of several algorithms used in LHCb data processing for GPUs and their
optimization on the new platform.
General Objective
Diseñar y desarrollar un programa computacional en
unidades de procesamiento gráfico para la reconstrucción del resultado de los
detectores de partículas RICH
unidades de procesamiento gráfico para la reconstrucción del resultado de los
detectores de partículas RICH
Research Lines
Teoría y Metodologías en Computación
Aplicación de la computación en distintos dominios científicos, tecnológicos,
organizacionales y sociales
Aplicación de la computación en distintos dominios científicos, tecnológicos,
organizacionales y sociales
| Status | Finished |
|---|---|
| Effective start/end date | 1/01/24 → 31/12/25 |
Keywords
- computational physics
- GPU
- accelerator
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