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With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY. [ABSTRACT FROM AUTHOR]

FastCaloSim is a parameterized simulation of the particle energy response and of the energy distribution in the ATLAS calorimeter. It is a relatively small and self-contained package with massive inherent parallelism and captures the essence of GPU offloading via important operations like data transfer, memory initialization, floating point operations, and reduction. It was identified by the High Energy Physics Center for Computational Excellence project as a good testbed for evaluating the performance and ease of portability of programming models. In this paper, we will discuss the results of our evaluation of the porting process to Kokkos, SYCL, Alpaka, OpenMP and std::par (nvc++), and compare performance on NVIDIA, AMD and Intel GPUs, as well as multicore CPUs. [ABSTRACT FROM AUTHOR]

We present tools for high-performance analysis written in pure Julia, a just-in-time (JIT) compiled dynamic programming language with a high-level syntax and performance. The packages we present center around UnROOT.jl, a pure Julia ROOT file I/O package that is optimized for speed, lazy reading, flexibility and thread safety. We discuss what affects performance in Julia, the challenges, and their solutions during the development of UnROOT.jl. We highlight type stability as a challenge and discuss its implication whenever any "compilation" happens (incl. Numba, Jax, C++) as well as Julia's specific ones. We demonstrate the performance and "easy to use" claim by comparing UnROOT.jl against popular alternatives (RDataFrame, Uproot, etc.) in medium-size realistic benchmarks, comparing both performance and code complexity. Finally, we also showcase real ATLAS analysis workflows both locally and on an HPC system, highlighting the composability of UnROOT.jl with multithread/process and out-of-core distributed computing libraries. [ABSTRACT FROM AUTHOR]

UKRI/STFC's Scientific Computing Department (SCD) has a long and rich history of delivering face to face public engagement and outreach, both on site and in public places, as part of the wider STFC programme. Due to the global COVID-19 pandemic, SCD was forced to abandon an extensive planned programme of public engagement, alongside altering the day-to-day working methods of the majority of its staff. SCD had to respond rapidly to create a new, remote only, programme for the summer and for the foreseeable future. This was initially an exercise in improvisation, identifying existing activities that could be delivered remotely with minimal changes. As the pandemic went on, SCD also created new resources specifically for a remote audience and adapted existing activities where appropriate, using our evaluation framework to ensure these activities continued to meet the aims of the in-person programme. This paper presents the process through which this was achieved, some of the benefits and challenges of remote engagement and the plans for 2021 and beyond. [ABSTRACT FROM AUTHOR]

VyPR (http://pyvypr.github.io/home/) is a framework being developed with the aim of automating as much as possible the performance analysis of Python programs. To achieve this, it uses an analysis-by-specification approach; developers specify the performance requirements of their programs (without any modifications of the source code) and such requirements are checked at runtime. VyPR then provides tools which allow developers to perform detailed analyses of the performance of their code. Such analyses can include determining the common paths taken to reach badly performing parts of code, deciding whether a single path through code led to variations in time taken by future observations, and more. This paper describes the developments that have taken place in the past year on VyPR's analysis tools to yield a Python shell-based analysis library, and a web-based application. It concludes by demonstrating the use of the analysis tools on the CMS Experiment's Conditions Upload service. [ABSTRACT FROM AUTHOR]

The storage group of CERN IT operates more than 20 individual EOS[1] storage services with a raw data storage volume of more than 340 PB. Storage space is a major cost factor in HEP computing and the planned future LHC Run 3 and 4 increase storage space demands by at least an order of magnitude. A cost effective storage model providing durability is Erasure Coding (EC) [2]. The decommissioning of CERN's remote computer center (Wigner/Budapest) allows a reconsideration of the currently configured dual-replica strategy where EOS provides one replica in each computer center. EOS allows one to configure EC on a per file bases and exposes four different redundancy levels with single, dual, triple and fourfold parity to select different quality of service and variable costs. This paper will highlight tests which have been performed to migrate files on a production instance from dual-replica to various EC profiles. It will discuss performance and operational impact, and highlight various policy scenarios to select the best file layout with respect to IO patterns, file age and file size. We will conclude with the current status and future optimizations, an evaluation of cost savings and discuss an erasure encoded EOS setup as a possible tape storage replacement. [ABSTRACT FROM AUTHOR]

In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evaluate the derivative of a function specified by a computer program. AD exploits the fact that every computer program, no matter how complicated, executes a sequence of elementary arithmetic operations (addition, subtraction, multiplication, division, etc.), elementary functions (exp, log, sin, cos, etc.) and control flow statements. AD takes source code of a function as input and produces source code of the derived function. By applying the chain rule repeatedly to these operations, derivatives of arbitrary order can be computed automatically, accurately to working precision, and using at most a small constant factor more arithmetic operations than the original program. This paper presents AD techniques available in ROOT, supported by Cling, to produce derivatives of arbitrary C/C++ functions through implementing source code transformation and employing the chain rule of differential calculus in both forward mode and reverse mode. We explain its current integration for gradient computation in TFormula. We demonstrate the correctness and performance improvements in ROOT's fitting algorithms. [ABSTRACT FROM AUTHOR]

The development of the GeantV Electromagnetic (EM) physics package has evolved following two necessary paths towards code modernization. A first phase required the revision of the main electromagnetic physics models and their implementation. The main objectives were to improve their accuracy, extend them to the new high-energy frontier posed by the Future Circular Collider (FCC) programme and allow a better adaptation to a multi-particle flow. Most of the EM physics models in GeantV have been reviewed from theoretical perspective and rewritten with vector-friendly implementations, being now available in scalar mode in the alpha release. The second phase consists of a thorough investigation on the possibility to vectorise the most CPU-intensive physics code parts, such as final state sampling. We have shown the feasibility of implementing electromagnetic physics models that take advantage of SIMD/SIMT architectures, thus obtaining gains in performance. After this phase, the time has come for the GeantV project to take a step forward towards the final proof of concept. This takes shape through the testing of the full simulation chain (transport + physics + geometry) running in vectorized mode. In this paper we will present the first benchmark results obtained after vectorizing a full set of electromagnetic physics models. [ABSTRACT FROM AUTHOR]

In this paper, we describe a neural field model which explains how a population of cortical neurons may encode in its firing pattern simultaneously the nature and time of sequential stimulus events. Moreover, we investigate how noise-induced perturbations may affect the coding process. This is obtained by means of a two-dimensional neural field equation, where one dimension represents the nature of the event (for example, the color of a light signal) and the other represents the moment when the signal has occurred. The additive noise is represented by a Q-Wiener process. Some numerical experiments reported are carried out using a computational algorithm for two-dimensional stochastic neural field equations. [ABSTRACT FROM AUTHOR]

The tightened-up norms concerning the emission of harmful substances into the natural environment are putting before designers of knots sealing very rigorous requirements. One should notice that mechanical seals are ones of most often applied sub-assemblies of the sealing nodes. The main task for mechanical seals is to maintain maximum tightness. They are applied practically in all branches of industry and must fulfil their function while working under various operating conditions. The determination of the pressure distribution in the fluid film layer is necessary to calculate the gasdynamic force and moments. A two-dimensional equation of Reynolds was solved based on Finite Volume Method (FVM). At the presented work findings of the simulation results concerning the comparison get based on the author's computer program in C++ language with results obtained from the commercial ANSYS CFX program was presented. [ABSTRACT FROM AUTHOR]

A brute force attack is a common method used by cybercriminals to gain unauthorized access to user accounts. It is essential for individuals and organizations to take proactive measures to protect themselves from such attacks. One way to do this is by improving their knowledge of cybersecurity and implementing measures to safeguard their online presence. Using programming languages like Python and web-frameworks like Django, websites can be developed to help individuals generate secure and memorable passwords that align with the latest password security standards. This can help anyone who wants to improve their password security, irrespective of whether they have been a victim of a cyber-attack or not. [ABSTRACT FROM AUTHOR]

VecGeom is a geometry modeller library with hit-detection features as needed by particle detector simulation at the LHC and beyond. It was incubated by a Geant-R&D initiative and the motivation to combine the code of Geant4 and ROOT/TGeo into a single, better maintainable piece of software within the EU-AIDA program. So far, VecGeom is mainly used by LHC experiments as a geometry primitive library called from Geant4, where it was shown to provide 7–12% reduction in CPU time due to its faster algorithms for complex primitives [1]. In this contribution, we discuss how VecGeom can be used as the navigating library in Geant4 in order to benefit from both its fast geometry primitives as well as its vectorised navigation module. We investigate whether this integration provides the speed improvements expected, in addition to the gain obtained from geometry primitives. We discuss and benchmark the application of a VecGeomnavigator plugin to Geant4 for a simplified geometry and show paths towards production usage. [ABSTRACT FROM AUTHOR]

The CMS experiment has recorded a high-purity sample of 10 billion unbiased b hadron decays. The CMS trigger and data acquisition systems were configured to deliver a custom data stream at an average throughput of 2 GB s−1, which was "parked" prior to reconstruction. The data stream was defined by level-1 and high level trigger algorithms that operated at peak trigger rates in excess of 50 and 5 kHz, respectively. New algorithms have been developed to reconstruct and identify electrons with high efficiency at transverse momenta as low as 0.5 GeV. The trigger strategy and electron reconstruction performance were validated with pilot processing campaigns. The accumulation and reconstruction of this data set, now complete, were delivered without significant impact on the core physics programme of CMS. This unprecedented sample provides a unique opportunity for physics analyses in the flavour sector and beyond. [ABSTRACT FROM AUTHOR]

We describe our experience porting the Regensburg implementation of the DD-αAMG solver from QPACE 2 to QPACE 3. We first review how the code was ported from the first generation Intel Xeon Phi processor (Knights Corner) to its successor (Knights Landing). We then describe the modifications in the communication library necessitated by the switch from InfiniBand to Omni-Path. Finally, we present the performance of the code on a single processor as well as the scaling on many nodes, where in both cases the speedup factor is close to the theoretical expectations. [ABSTRACT FROM AUTHOR]