Related papers: GPU-based track-finding for the J-PARC muon g-2/ED…
The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly…
The conservative Post-Newtonian (PN) Hamiltonian formulation of spinning compact binaries has six integrals of motion including the total energy, the total angular momentum and the constant unit lengths of spins. The manifold correction…
In the next decade, the demands for computing in large scientific experiments are expected to grow tremendously. During the same time period, CPU performance increases will be limited. At the CERN Large Hadron Collider (LHC), these two…
Limits on power dissipation have pushed CPUs to grow in parallel processing capabilities rather than clock rate, leading to the rise of "manycore" or GPU-like processors. In order to achieve the best performance, applications must be able…
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core - MIC) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core…
Single muon triggers are crucial for the physics programmes at hadron collider experiments. To be sensitive to electroweak processes, single muon triggers with transverse momentum thresholds down to 20 GeV and dimuon triggers with even…
A track finding algorithm has been developed for reconstruction of e+e- pairs. It combines the information of the electromagnetic calorimeter with the information provided by the Tracker. Results on reconstruction efficiency of converted…
Approximate Nearest Neighbor Search (ANNS) has become fundamental to modern deep learning applications, having gained particular prominence through its integration into recent generative models that work with increasingly complex datasets…
Interest in many-core architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of many-core devices when applied to a typical HEP online task: the…
The IEEE 754-2008 standard recommends the correct rounding of some elementary functions. This requires to solve the Table Maker's Dilemma which implies a huge amount of CPU computation time. We consider in this paper accelerating such…
An implementation of A Common Tracking Software (ACTS) toolkit for signal electron reconstruction for the COMET muon to electron conversion experiment is discussed. The COMET experiment in J-PARC, Japan, will search for neutrinoless…
The contribution of Resistive Plate Chamber (RPC) to muon reconstruction in CMS has been studied on a sample of muons collected in proton-proton collisions at sqrt(s) = 7 TeV at the LHC in 2011. Muon reconstruction is performed using the…
In the search for physics beyond the Standard Model the Mu3e experiment tries to observe the lepton flavor violating decay $\mu^+ \rightarrow e^+ e^- e^+$. By observing the decay products of $1 \cdot 10^8\mu$/s it aims to either observe the…
The detection of ultralight dark matter through interactions with nucleons, electrons, and photons has been explored in depth. In this work we propose to use precision muon experiments, specifically muon g-2 and electric dipole moment…
Accurately predicting phonon scattering is crucial for understanding thermal transport properties. However, the computational cost of such calculations, especially for four-phonon scattering, can often be more prohibitive when large number…
A large number of high-energy and heavy-ion experiments successfully used Time Projection Chamber (TPC) as central tracker and particle identification detector. However, the performance requirements on TPC for new high-rate particle…
GPUReplay (GR) is a novel way for deploying GPU-accelerated computation on mobile and embedded devices. It addresses high complexity of a modern GPU stack for deployment ease and security. The idea is to record GPU executions on the full…
The training process of Deep Neural Network (DNN) is compute-intensive, often taking days to weeks to train a DNN model. Therefore, parallel execution of DNN training on GPUs is a widely adopted approach to speed up the process nowadays.…
Gas Electron Multipliers (GEM) are an interesting technology under consideration for the future upgrade of the forward region of the CMS muon system, specifically in the $1.6<| \eta |<2.4$ endcap region. With a sufficiently fine…
The Kernel Polynomial Method (KPM) is one of the fast diagonalization methods used for simulations of quantum systems in research fields of condensed matter physics and chemistry. The algorithm has a difficulty to be parallelized on a…