相关论文: MarlinTPC: A Marlin based common TPC software fram…
This paper presents an open-source, lightweight, yet comprehensive software framework, named RPC, which integrates physics-based simulators, planning and control libraries, debugging tools, and a user-friendly operator interface. RPC…
The openPC is a set of open source tools that realizes a parallel machine and distributed computing environment divisible into several independent blocks of nodes, and each of them is remotely but fully in any means accessible for users…
After an overview of the modular analysis and reconstruction framework Marlin an introduction on the functionality of the Marlin-based reconstruction package MarlinReco is given. This package includes a full set of modules for event…
With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows,…
The goal of our Macro Lambda Calculus project (MLC) is to encode lambda terms into interaction nets. Its software implementation will accept input in the notation similar to lambda calculus allowing macro definitions. Output is similar to…
Here, we present the concept of an open virtual prototyping framework for maritime systems and operations that enables its users to develop re-usable component or subsystem models, and combine them in full-system simulations for…
Task based parallel programming has shown competitive outcomes in many aspects of parallel programming such as efficiency, performance, productivity and scalability. Different approaches are used by different software development frameworks…
The CALICE collaboration is developing calorimeters for a future linear collider, and has collected a large amount of physics data during test beam efforts. For the analysis of these data, standard software available for linear collider…
Large-scale social digital twinning projects are complex with multiple objectives. For example, a social digital twinning platform for innovative last-mile delivery solutions may aim to assess consumer delivery method choices within their…
To achieve high performance on modern computers, it is vital to map algorithmic parallelism to that inherent in the hardware. From an application developer's perspective, it is also important that code can be maintained in a portable manner…
xMLC is the second book of this `Machine Learning Tools in Fluid Mechanics' Series and focuses on Machine Learning Control (MLC). The objectives of this book are two-fold: First, provide an introduction to MLC for students, researchers, and…
Trilinos is a community-developed, open-source software framework that facilitates building large-scale, complex, multiscale, multiphysics simulation code bases for scientific and engineering problems. Since the Trilinos framework has…
Let's HPC (www.letshpc.org) is an open-access online platform to supplement conventional classroom oriented High Performance Computing (HPC) and Parallel & Distributed Computing (PDC) education. The web based platform provides online…
A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of…
OpenCL is a standard for parallel programming of heterogeneous systems. The benefits of a common programming standard are clear; multiple vendors can provide support for application descriptions written according to the standard, thus…
While there exist many ways to deploy machine learning models on microcontrollers, it is non-trivial to choose the optimal combination of frameworks and targets for a given application. Thus, automating the end-to-end benchmarking flow is…
The amount of remote sensing data available to applications is constantly growing due to the rise of very-high-resolution sensors and short repeat cycle satellites. Consequently, tackling computational complexity in Earth Observation…
Large Language Models (LLMs) have become increasingly prevalent in cloud-based platforms, propelled by the introduction of AI-based consumer and enterprise services. LLM inference requests in particular account for up to 90% of total LLM…
Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are…
The architecture of a robotics software framework tremendously influences the effort and time it takes for end users to test new concepts in a simulation environment and to control real hardware. Many years of activity in the field allowed…