Related papers: Multi-threaded Geant4 on the Xeon-Phi with Complex…
We evolve PyDTNN, a framework for distributed parallel training of Deep Neural Networks (DNNs), into an efficient inference tool for convolutional neural networks. Our optimization process on multicore ARM processors involves several…
This article introduces a highly parallel algorithm for molecular dynamics simulations with short-range forces on single node multi- and many-core systems. The algorithm is designed to achieve high parallel speedups for strongly…
Advanced detector R&D for both new and ongoing experiments in HEP requires performing computationally intensive and detailed simulations as part of the detector-design optimisation process. We propose a versatile approach to this task that…
The conjugate gradient (CG) algorithm is among the most essential and time consuming parts of lattice calculations with staggered quarks. We test the performance of CG and dslash, the key step in the CG algorithm, on the Intel Xeon Phi,…
We give an overview of QPACE 2, which is a custom-designed supercomputer based on Intel Xeon Phi processors, developed in a collaboration of Regensburg University and Eurotech. We give some general recommendations for how to write…
Many complex problems, such as natural language processing or visual object detection, are solved using deep learning. However, efficient training of complex deep convolutional neural networks for large data sets is computationally…
A model for the simulation of orientational effects in straight and bent periodic atomic structures is presented. The continuum potential approximation has been adopted.The model allows the manipulation of particle trajectories by means of…
Coupled multiphysics simulations for high-dimensional, large-scale problems can be prohibitively expensive due to their computational demands. This article presents a novel framework integrating a deep operator network (DeepONet) with the…
Significant new challenges are continuously confronting the High Energy Physics (HEP) experiments, in particular the two detectors at the Large Hadron Collider (LHC) at CERN, where nominal conditions deliver proton-proton collisions to the…
In our work we analyze computational aspects of the problem of numerical integration in finite element calculations and consider an OpenCL implementation of related algorithms for processors with wide vector registers. As a platform for…
The efficient execution of image processing algorithms is an active area of Bioinformatics. In image processing, one of the classes of algorithms or computing pattern that works with irregular data structures is the Irregular Wavefront…
This article presents an automatic approach to quickly derive a good solution for hardware resource partition and task granularity for task-based parallel applications on heterogeneous many-core architectures. Our approach employs a…
High Energy and Nuclear Physics (HENP) libraries are now required to be more and more multi-thread-safe, if not multi-thread-friendly and multi-threaded. This is usually done using the new constructs and library components offered by the…
In this paper, we present the High Energy Physics data format, processing toolset and analysis library a4, providing fast I/O of structured data using the Google protocol buffer library. The overall goal of a4 is to provide physicists with…
We evaluate the performance of an Omnivision OV5647 CMOS image sensor (5 Mp) for detecting radiation from Sr90 and Cs137 sources. Our experimental setup uses a Raspberry Pi 3 mini-computer for data acquisition, with image processing using…
The Crossroads supercomputer was designed to simulate some of the most complex physical devices in the world. These simulations routinely require 1/2 petabyte or more of system memory running on thousands of compute nodes for months at a…
Computation intensive kernels, such as convolutions, matrix multiplication and Fourier transform, are fundamental to edge-computing AI, signal processing and cryptographic applications. Interleaved-Multi-Threading (IMT) processor cores are…
NVIDIA's new architecture, Kepler improves GPU's performance significantly with the new streaming multiprocessor SMX. Along with the performance, NVIDIA has also introduced many new technologies such as direct parallelism, hyper-Q and GPU…
An accurate description of interactions between thermal neutrons (below 4 eV) and materials is key to simulate the transport of neutrons in a wide range of applications such as criticality-safety, reactor physics, compact accelerator-driven…
The risk of reinsurance portfolios covering globally occurring natural catastrophes, such as earthquakes and hurricanes, is quantified by employing simulations. These simulations are computationally intensive and require large amounts of…