Porting HEP Parameterized Calorimeter Simulation Code to GPUs.

Front Big Data

Brookhaven National Laboratory, Upton, NY, United States.

Published: June 2021

The High Energy Physics (HEP) experiments, such as those at the Large Hadron Collider (LHC), traditionally consume large amounts of CPU cycles for detector simulations and data analysis, but rarely use compute accelerators such as GPUs. As the LHC is upgraded to allow for higher luminosity, resulting in much higher data rates, purely relying on CPUs may not provide enough computing power to support the simulation and data analysis needs. As a proof of concept, we investigate the feasibility of porting a HEP parameterized calorimeter simulation code to GPUs. We have chosen to use FastCaloSim, the ATLAS fast parametrized calorimeter simulation. While FastCaloSim is sufficiently fast such that it does not impose a bottleneck in detector simulations overall, significant speed-ups in the processing of large samples can be achieved from GPU parallelization at both the particle (intra-event) and event levels; this is especially beneficial in conditions expected at the high-luminosity LHC, where extremely high per-event particle multiplicities will result from the many simultaneous proton-proton collisions. We report our experience with porting FastCaloSim to NVIDIA GPUs using CUDA. A preliminary Kokkos implementation of FastCaloSim for portability to other parallel architectures is also described.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8267914PMC
http://dx.doi.org/10.3389/fdata.2021.665783DOI Listing

Publication Analysis

Top Keywords

calorimeter simulation
12
porting hep
8
hep parameterized
8
parameterized calorimeter
8
simulation code
8
code gpus
8
detector simulations
8
data analysis
8
simulation
4
gpus
4

Similar Publications

The Large Hadron Collider's high luminosity era presents major computational challenges in the analysis of collision events. Large amounts of Monte Carlo (MC) simulation will be required to constrain the statistical uncertainties of the simulated datasets below these of the experimental data. Modelling of high-energy particles propagating through the calorimeter section of the detector is the most computationally intensive MC simulation task.

View Article and Find Full Text PDF

The identification of biological evidence is particularly important for criminal detection, and the deoxyribonucleic acid (DNA) analysis plays a significant role in reconstructing events. However, bloodstains after thermal exposure in fires are quite unique compared to those in other scenes. Previous results regarding DNA recovery in bloodstains after heating are inconsistent with each other, which limits guidance for forensic science.

View Article and Find Full Text PDF

Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.

Comput Softw Big Sci

May 2024

Institut für Hochenergiephysik, Österreichischen Akademie der Wissenschaften, Nikolsdorfer Gasse 18, 1050 Wien, Austria.

Cryogenic phonon detectors with transition-edge sensors achieve the best sensitivity to sub-GeV/c dark matter interactions with nuclei in current direct detection experiments. In such devices, the temperature of the thermometer and the bias current in its readout circuit need careful optimization to achieve optimal detector performance. This task is not trivial and is typically done manually by an expert.

View Article and Find Full Text PDF

Laser Metal Deposition of Rene 80-Microstructure and Solidification Behavior Modelling.

Micromachines (Basel)

September 2024

Bundesanstalt für Materialforschung und -prüfung (BAM), Unter den Eichen 87, 12205 Berlin, Germany.

New developments in nickel-based superalloys and production methods, such as the use of additive manufacturing (AM), can result in innovative designs for turbines. It is crucial to understand how the material behaves during the AM process to advance the industrial use of these techniques. An analytical model based on reaction-diffusion formalism is developed to better explain the solidification behavior of the material during laser metal deposition (LMD).

View Article and Find Full Text PDF
Article Synopsis
  • An aptamer-ligand biorecognition system was developed to detect cyanide intoxication through its metabolite, 2-amino-2-thiazoline-4-carboxylic acid (ATCA).
  • Aptamers were identified from a DNA library using a technique called GO-SELEX, and their effectiveness was tested through molecular docking and thermodynamic analysis.
  • The resulting aptasensor, utilizing the best-performing aptamer (Apt46), demonstrated a low detection limit and high recovery rates across different biological samples, showing promise for use in acute cyanide exposure cases.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!