From aba02c6f04c0a1ca367dcb07b2e3be9c9a0779c7 Mon Sep 17 00:00:00 2001 From: Dennis Klein Date: Thu, 9 Dec 2021 18:19:28 +0100 Subject: [PATCH] Update --- readme.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/readme.md b/readme.md index c797dd43..95b3c1c6 100644 --- a/readme.md +++ b/readme.md @@ -1,6 +1,6 @@ ## FairMQ in a nutshell -Next-generation Particle Physics Experiments at [GSI](https://www.gsi.de)/[FAIR](https://www.gsi.de/forschungbeschleuniger/fair) and [CERN](https://home.web.cern.ch/) are facing [unprecedented data processing challenges](https://doi.org/10.1051/epjconf/201921405010). Expected data rates require a non-trivial amount of high performance compute (HPC) resources in the order of thousands of CPU/GPU cores per experiment. Online (synchronous) data processing (compression) is crucial to stay within storage capacity limits. The complexity of tasks that need to be performed during the online data processing is significantly higher than ever before. Complex tasks like calibration and track finding classically ran in an offline (asynchronous) environment and have to now run online in a high performance and high throughput environment. +Next-generation Particle Physics Experiments at [GSI](https://www.gsi.de)/[FAIR](https://www.gsi.de/forschungbeschleuniger/fair) and [CERN](https://home.web.cern.ch/) are facing [unprecedented data processing challenges](https://doi.org/10.1051/epjconf/201921405010). Expected data rates require a non-trivial amount of high performance compute (HPC) resources in the order of thousands of CPU/GPU cores per experiment. Online (synchronous) data processing (compression) is crucial to stay within storage capacity limits. The complexity of tasks that need to be performed during the online data processing is significantly higher than ever before. Classically complex tasks like calibration and track finding run in an offline (asynchronous) environment. Now they have to run online in a high performance and high throughput environment. The [FairMQ C++ library](https://github.com/FairRootGroup/FairMQ/) is designed to aid the implementation of such large-scale online data processing workflows by