240 citations · 420 across the 11 of their papers we have counts for
13 papers
Efficient precision simulation of processes with many-jet final states at the LHC
Enrico Bothmann, Taylor Childers, Christian Guetschow +5
We present a scalable technique for the simulation of collider events with multi-jet final states, based on an improved parton-level event file format. The method is implemented fo…
Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics
Mohammad Atif, Meghna Battacharya, Paolo Calafiura +17
High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapid…
Speeding up Madgraph5 aMC@NLO through CPU vectorization and GPU offloading: towards a first alpha release
Andrea Valassi, Taylor Childers, Laurence Field +9
The matrix element (ME) calculation in any Monte Carlo physics event generator is an ideal fit for implementing data parallelism with lockstep processing on GPUs and vector CPUs. F…
Efficient phase-space generation for hadron collider event simulation
Enrico Bothmann, Taylor Childers, Walter Giele +5
We present a simple yet efficient algorithm for phase-space integration at hadron colliders. Individual mappings consist of a single t-channel combined with any number of s-channel…
Developments in Performance and Portability for MadGraph5_aMC@NLO
Andrea Valassi, Taylor Childers, Laurence Field +6
Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. Th…
Portability: A Necessary Approach for Future Scientific Software
Meghna Bhattacharya, Paolo Calafiura, Taylor Childers +16
Today's world of scientific software for High Energy Physics (HEP) is powered by x86 code, while the future will be much more reliant on accelerators like GPUs and FPGAs. The porta…
HL-LHC Computing Review Stage-2, Common Software Projects: Event Generators
The HSF Physics Event Generator WG, :, Efe Yazgan +36
This paper has been prepared by the HEP Software Foundation (HSF) Physics Event Generator Working Group (WG), as an input to the second phase of the LHCC review of High-Luminosity…
Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
Taylor Childers, Matti J. Kortelainen, Martin Kwok +2
Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, an…
Deep Reinforcement Agent for Scheduling in HPC
Yuping Fan, Zhiling Lan, Taylor Childers +3
Cluster scheduler is crucial in high-performance computing (HPC). It determines when and which user jobs should be allocated to available system resources. Existing cluster schedul…
HL-LHC Computing Review: Common Tools and Community Software
HEP Software Foundation, :, Thea Aarrestad +107
Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHC's success so far and continued development and optimisation will b…
Challenges in Monte Carlo event generator software for High-Luminosity LHC
The HSF Physics Event Generator WG, :, Andrea Valassi +38
We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics p…
Machine Learning in High Energy Physics Community White Paper
Kim Albertsson, Piero Altoe, Dustin Anderson +125
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by a…
A Roadmap for HEP Software and Computing R&D for the 2020s
Johannes Albrecht, Antonio Augusto Alves, Guilherme Amadio +307
Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facil…