Report Open Access

Employing HPC for Heterogeneous HEP Data Processing

Barbone, Marco

The DEEP-EST Project aims to build a Modular Supercomputer Architecture (MSA) with the main focus on the usage of heterogenous computing resources. The majority of current HEP workflows are capable of utilizing exclusively Central Processing Units (CPU), which create inefficiency when trying to run on heterogenous systems equipped with additional hardware accelerators (GPUs, FPGAs).
Within the context of this project, we want to extend current CPU specific implementations of various algorithms (calorimeter reconstruction, track fitting, etc. ) by utilizing OpenCL and CUDA language extensions in order to harness the computational power provided by various hardware accelerators.

Files (806.8 kB)
Name Size
Report_Marco Barbone.pdf
md5:7193d04dee8001185c49861c6db94cb2
806.8 kB Download
173
124
views
downloads
All versions This version
Views 173173
Downloads 124124
Data volume 100.0 MB100.0 MB
Unique views 159159
Unique downloads 115115

Share

Cite as