相关论文: JClarens: A Java Framework for Developing and Depl…

The growing adoption of Deep Learning (DL) applications in the Internet of Things has increased the demand for energy-efficient accelerators. Field Programmable Gate Arrays (FPGAs) offer a promising platform for such acceleration due to…

Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phenomena. Realizing these ideals will require the development…

Scientific computing can in some sense be distilled to the execution of an application - or rather sets of applications which are combined into complex workflows. Due to the complexity and number both of scientific packages as well as…

Designing accelerators for resource- and power-constrained applications is a daunting task. High-level Synthesis (HLS) addresses these constraints through resource sharing, an optimization at the HLS binding stage that maps multiple…

Heterogeneous computing integrates diverse processing elements, such as CPUs, GPUs, and FPGAs, within a single system, aiming to leverage the strengths of each architecture to optimize performance and energy consumption. In this context,…

The design of efficient hardware accelerators for high-throughput data-processing applications, e.g., deep neural networks, is a challenging task in computer architecture design. In this regard, High-Level Synthesis (HLS) emerges as a…

Data processing frameworks are an essential part of HEP experiments' software stacks. Frameworks provide a means by which code developers can undertake the essential tasks of physics data processing, accessing relevant inputs and storing…

Writing desktop applications in JavaScript offers developers the opportunity to write cross-platform applications with cutting edge capabilities. However in doing so, they are potentially submitting their code to a number of unsanctioned…

The beginning of the 21st century has seen many projects on distributed hash tables, both research and commercial. One of their aims has been to replace the first generation of file sharing software with scalable peer-to-peer architectures.…

Cloud computing, thanks to the pervasiveness of information technologies, provides a foundational environment for developing IT applications, offering organizations virtually unlimited and flexible computing resources on a pay-per-use…

Serverless computing has emerged as a compelling paradigm for the development and deployment of a wide range of event based cloud applications. At the same time, cloud providers and enterprise companies are heavily adopting machine learning…

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…

Function-as-a-Service (FaaS) is a type of serverless computing that allows developers to write and deploy code as individual functions, which can be triggered by specific events or requests. FaaS platforms automatically manage the…

Flexible and performant Persistency Service is a necessary component of any HEP Software Framework. The building of a modular, non-intrusive and performant persistency component have been shown to be very difficult task. In the past, it was…

Robust generalization under climate change remains a major challenge for machine learning applications in climate science. Most existing approaches struggle to extrapolate beyond the climate they were trained on, leading to a strong…

The globally distributed computing infrastructure required to cope with the multi-petabytes datasets produced by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at CERN comprises several subsystems, such as…

The Infrastructure-as-a-Service (IaaS) model of cloud computing is a promising approach towards building elastically scaling systems. Unfortunately, building such applications today is a complex, repetitive and error-prone endeavor, as IaaS…

Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and developers have to implement complete solutions which are…

This document presents a number of quick-step instructions to get started on writing mini-service-oriented web services-based applications using OpenESB 2.31, Tomcat 6, GlassFish 2.x/3.0.1 with BPEL support, and Java 1.6+ primarily in…

This work describes the setup of an advanced technical infrastructure for collaborative software development (CDE) in large, distributed projects based on GitLab. We present its customization and extension, additional features and processes…