Related papers: FPGA Online Tracking Algorithm for the PANDA Straw…

Computing centres, including those used to process High-Energy Physics data and simulations, are increasingly providing significant fractions of their computing resources through hardware architectures other than x86 CPUs, with GPUs being a…

This paper presents a deeply pipelined and massively parallel Binary Search Tree (BST) accelerator for Field Programmable Gate Arrays (FPGAs). Our design relies on the extremely parallel on-chip memory, or Block RAMs (BRAMs) architecture of…

The online event reconstruction for the ALICE experiment at CERN requires processing capabilities to process central Pb-Pb collisions at a rate of more than 200 Hz, corresponding to an input data rate of about 25 GB/s. The reconstruction of…

Recurrent Neural Networks (RNNs) have the ability to retain memory and learn data sequences. Due to the recurrent nature of RNNs, it is sometimes hard to parallelize all its computations on conventional hardware. CPUs do not currently offer…

Digital correlators play a significant role in dynamic light scattering (DLS) technology, which characterizes particle size distribution. We present a field programmable gate array (FPGA)-based digital correlator that can be applied to…

The increasing demand of dedicated accelerators to improve energy efficiency and performance has highlighted FPGAs as a promising option to deliver both. However, programming FPGAs in hardware description languages requires long time and…

Embedded system performances are bounded by power consumption. The trend is to offload greedy computations on hardware accelerators as GPU, Xeon Phi or FPGA. FPGA chips combine both flexibility of programmable chips and energy-efficiency of…

In the face of escalating complexity and size of contemporary FPGAs and circuits, routing emerges as a pivotal and time-intensive phase in FPGA compilation flows. In response to this challenge, we present an open-source parallel routing…

The upgrades of the Belle experiment and the KEKB accelerator aim to increase the data set of the experiment by the factor 50. This will be achieved by increasing the luminosity of the accelerator which requires a significant upgrade of the…

The ATLAS experiment measures the properties of particles that are products of proton-proton collisions at the LHC. The ATLAS detector will undergo a major upgrade before the high luminosity phase of the LHC. The ATLAS liquid argon…

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is designed to study a wide range of high energy physics phenomena. It employs a large all-silicon tracker within a 3.8 T magnetic solenoid, which allows precise…

Real-time track tracking in high energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern-recognition and track fitting in online trigger system, the artificial Retina…

It is well known that to accelerate stencil codes on CPUs or GPUs and to exploit hardware caches and their lines optimizers must find spatial and temporal locality of array accesses to harvest data-reuse opportunities. On FPGAs there is the…

Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core…

Particle tracking is a challenging pattern recognition task at the Large Hadron Collider (LHC) and the High Luminosity-LHC. Conventional algorithms, such as those based on the Kalman Filter, achieve excellent performance in reconstructing…

Hardware-based acceleration is an extensive attempt to facilitate many computationally-intensive mathematics operations. This paper proposes an FPGA-based architecture to accelerate the convolution operation - a complex and expensive…

Field-programmable gate array (FPGA) based accelerators are being widely used for acceleration of convolutional neural networks (CNNs) due to their potential in improving the performance and reconfigurability for specific application…

A novel combination of established data analysis techniques for reconstructing all charged-particle tracks in high energy collisions is proposed. It uses all information available in a collision event while keeping competing choices open as…

Recommendation systems, social network analysis, medical imaging, and data mining often involve processing sparse high-dimensional data. Such high-dimensional data are naturally represented as tensors, and they cannot be efficiently…

In the future high-luminosity LHC era, high-energy physics experiments face unprecedented computational challenges for event reconstruction. Employing the LHCb vertex locator as a case study we investigate a novel approach for charged…