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The Core Imaging Library (CIL) is an open-source versatile Python framework for solving inverse problems with special emphasis on imaging applications such as computed tomography (CT), using a plug-in architecture for data and operators,…

Large Language Models (LLMs) are rapidly becoming ubiquitous both as stand-alone tools and as components of current and future software systems. To enable usage of LLMs in the high-stake or safety-critical systems of 2030, they need to…

In this presentation the experiences of the LHC experiments using grid computing were presented with a focus on experience with distributed analysis. After many years of development, preparation, exercises, and validation the LHC (Large…

LCG-1 is the second release of the software framework for the LHC Computing Grid project. In our work we describe the installation process, arising problems and their solutions, and configuration tuning details of the complete LCG-1 site,…

What is Sequence Algebra? This is a question that any teacher or student of mathematics or computer science can engage with. Sequences are in Calculus, Combinatorics, Statistics and Computation. They are foundational, a step up from number…

Optimising use of the Web (WWW) for LHC data analysis is a complex problem and illustrates the challenges arising from the integration of and computation across massive amounts of information distributed worldwide. Finding the right piece…

The Large Hadron Collider (LHC) is one of the most complex machines ever build. It is composed of many components which constitute a large system. The tunnel and the accelerator is just one of a very critical fraction of the whole LHC…

This paper presents Haskell#, a coordination language targeted at the efficient implementation of parallel scientific applications on loosely coupled parallel architectures, using the functional language Haskell. Examples of applications,…

The need for computational resources grows as computational algorithms gain popularity in different sectors of the scientific community. This search has stimulated the development of several cloud platforms that abstract the complexity of…

Software weaknesses that create attack surfaces for adversarial exploits, such as lateral SQL injection (LSQLi) attacks, are usually introduced during the design phase of software development. Security design patterns are sometimes applied…

HEP-Frame is a new C++ package designed to efficiently perform analyses of data sets from a very large number of events, like those available at the Large Hadron Collider (LHC) at CERN, Geneva. It mainly targets high performance servers and…

Trusted Execution Environments (TEEs) are a feature of modern central processing units (CPUs) that aim to provide a high assurance, isolated environment in which to run workloads that demand both confidentiality and integrity. Hardware and…

To extract physics results from the recorded data, the LHC experiments are using Grid computing infrastructure. The event data processing on the Grid requires scalable access to non-event data (detector conditions, calibrations, etc.)…

When algorithmic skeletons were first introduced by Cole in late 1980 the idea had an almost immediate success. The skeletal approach has been proved to be effective when application algorithms can be expressed in terms of skeletons…

The growing complexity of modern computing platforms and the need for strong isolation protections among their software components has led to the increased adoption of Trusted Execution Environments (TEEs). While several commercial and…

Separation kernels are fundamental software of safety and security-critical systems, which provide to their hosted applications spatial and temporal separation as well as controlled information flows among partitions. The application of…

We describe the plans and objectives of the CEDAR project (Combined e-Science Data Analysis Resource for High Energy Physics) newly funded by the PPARC e-Science programme in the UK. CEDAR will combine the strengths of the well established…

Having built up Linux clusters to more than 1000 nodes over the past five years, we already have practical experience confronting some of the LHC scale computing challenges: scalability, automation, hardware diversity, security, and rolling…

This paper was prepared by the HEP Software Foundation (HSF) PyHEP Working Group as input to the second phase of the LHCC review of High-Luminosity LHC (HL-LHC) computing, which took place in November, 2021. It describes the adoption of…

Text clustering, as one of the most fundamental challenges in unsupervised learning, aims at grouping semantically similar text segments without relying on human annotations. With the rapid development of deep learning, deep clustering has…