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Dedicated tensor accelerators demonstrate the importance of linear algebra in modern applications. Such accelerators have the potential for impressive performance gains, but require programmers to rewrite code using vendor APIs - a barrier…

Efficiently exploiting GPUs is increasingly essential in scientific computing, as many current and upcoming supercomputers are built using them. To facilitate this, there are a number of programming approaches, such as CUDA, OpenACC and…

Performance · Computer Science 2017-11-07 G. D. Balogh , I. Z. Reguly , G. R. Mudalige

Tremendous advances in parallel computing and graphics hardware opened up several novel real-time GPU applications in the fields of computer vision, computer graphics as well as augmented reality (AR) and virtual reality (VR). Although…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-19 Patrick Stotko

The article deals with a kind of recursive function templates in C++, where the recursion is realized corresponding template parameters to achieve better computational performance. Some specialization of these template functions ends the…

Mathematical Software · Computer Science 2007-05-23 Volodymyr Myrnyy

This paper presents the acados software package, a collection of solvers for fast embedded optimization intended for fast embedded applications. Its interfaces to higher-level languages make it useful for quickly designing an…

This report provides an introduction to the ensmallen numerical optimization library, as well as a deep dive into the technical details of how it works. The library provides a fast and flexible C++ framework for mathematical optimization of…

Mathematical Software · Computer Science 2023-11-16 Ryan R. Curtin , Marcus Edel , Rahul Ganesh Prabhu , Suryoday Basak , Zhihao Lou , Conrad Sanderson

With the announcement that the Aurora Supercomputer will be composed of general purpose Intel CPUs complemented by discrete high performance Intel GPUs, and the deployment of the oneAPI ecosystem, Intel has committed to enter the arena of…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-19 Yuhsiang M. Tsai , Terry Cojean , Hartwig Anzt

A C library for random number generation, Randompack, is presented. The library implements several modern random number generators (engines), including xoshiro256, PCG64, Philox, ranlux++, and sfc64; 14 continuous distributions including…

Applications · Statistics 2026-05-11 Kristján Jónasson

In this paper, we present Ginkgo, a modern C++ math library for scientific high performance computing. While classical linear algebra libraries act on matrix and vector objects, Ginkgo's design principle abstracts all functionality as…

The recent advancements in Transformer-based Language Models have demonstrated significant potential in enhancing the multilingual capabilities of these models. The remarkable progress made in this domain not only applies to natural…

Software Engineering · Computer Science 2023-08-28 Jonathan Katzy , Maliheh Izadi , Arie van Deursen

Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it well. High-performance libraries are available, but adoption costs are significant. Moreover, libraries tie programs into vendor-specific…

Performance · Computer Science 2020-01-29 Philip Ginsbach , Bruce Collie , Michael F. P. O'Boyle

This paper provides the description of a novel, multi-purpose spline library. In accordance with the increasingly diverse modes of usage of splines, it is multi-purpose in the sense that it supports geometry representation, finite element…

Mathematical Software · Computer Science 2020-02-28 Markus Frings , Norbert Hosters , Corinna Müller , Max Spahn , Christoph Susen , Konstantin Key , Stefanie Elgeti

The rapid advancements in artificial intelligence (AI), particularly the Large Language Models (LLMs), have profoundly affected our daily work and communication forms. However, it is still a challenge to deploy LLMs on resource-constrained…

Hardware Architecture · Computer Science 2025-03-03 Mingqiang Huang , Ao Shen , Kai Li , Haoxiang Peng , Boyu Li , Yupeng Su , Hao Yu

I describe an approach to compiling common idioms in R code directly to native machine code and illustrate it with several examples. Not only can this yield significant performance gains, but it allows us to use new approaches to computing…

Computation · Statistics 2014-09-12 Duncan Temple Lang

This report is devoted to some C++ codes implementing the implicit LU class algorithms for solving linear determined, and undetermined systems with $n$ variables and $m$ equations. A main program used in part of the numerical test is given…

Numerical Analysis · Mathematics 2025-10-20 Xing Li , Ying Liu , Antonino Del Popolo

For over 15 years, the mlpack machine learning library has served as a "swiss army knife" for C++-based machine learning. Its efficient implementations of common and cutting-edge machine learning algorithms have been used in a wide variety…

We introduce cilantro, an open-source C++ library for geometric and general-purpose point cloud data processing. The library provides functionality that covers low-level point cloud operations, spatial reasoning, various methods for point…

Computer Vision and Pattern Recognition · Computer Science 2018-11-19 Konstantinos Zampogiannis , Cornelia Fermuller , Yiannis Aloimonos

Graphic Processing Units (GPUs) have become ubiquitous in scientific computing. However, writing efficient GPU kernels can be challenging due to the need for careful code tuning. To automatically explore the kernel optimization space,…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-23 Stijn Heldens , Ben van Werkhoven

This paper presents a programming language which includes paradigms that are usually associated with declarative languages, such as sets, rules and search, into an imperative (functional) language. Although these paradigms are separately…

Programming Languages · Computer Science 2007-05-23 Yves Caseau , Francois-Xavier Josset , Francois Laburthe

Even though in recent years the scale of statistical analysis problems has increased tremendously, many statistical software tools are still limited to single-node computations. However, statistical analyses are largely based on dense…

Computation · Statistics 2016-11-01 Rodrigo Canales , Elmar Peise , Paolo Bientinesi