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This work presents a comprehensive evaluation of neural network graph compilers across heterogeneous hardware platforms, addressing the critical gap between theoretical optimization techniques and practical deployment scenarios. We…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-30 Alireza Furutanpey , Carmen Walser , Philipp Raith , Pantelis A. Frangoudis , Schahram Dustdar

Persistent homology is perhaps the most popular and useful tool offered by topological data analysis, with point-cloud data being the most common setup. Its older cousin, the Euler characteristic curve (ECC) is less expressive, but far…

Computational Geometry · Computer Science 2023-03-07 Fan Wang , Hubert Wagner , Chao Chen

Given a finitely presented Graded Commutative Differential Algebra (GCDA), we present a method to compute its minimal model, together with a map that is a quasi-isomorphism up to a given degree. The method works by adding generators one by…

Algebraic Topology · Mathematics 2021-01-27 Victor Manero , Miguel Ángel Marco Buzunariz

Hulls of linear codes have been of interest and extensively studied due to their rich algebraic structures and wide applications. In this paper, alternative characterizations of hulls of linear codes are given as well as their applications.…

Information Theory · Computer Science 2019-09-11 Satanan Thipworawimon , Somphong Jitman

Generalized Concatenated (GC), also known as Integrated Interleaved (II) Codes, are studied from an erasure correction point of view making them useful for Redundant Arrays of Independent Disks (RAID) types of architectures combining global…

Information Theory · Computer Science 2014-07-11 Mario Blaum , Steven Hetzler

We present a convex hull algorithm that is accelerated on commodity graphics hardware. We analyze and identify the hurdles of writing a recursive divide and conquer algorithm on the GPU and divise a framework for representing this class of…

Computational Geometry · Computer Science 2015-03-20 Stanley Tzeng , John D. Owens

This paper introduces cuHALLaR, a GPU-accelerated implementation of the HALLaR method proposed in Monteiro et al. 2024 for solving large-scale semidefinite programming (SDP) problems. We demonstrate how our Julia-based implementation…

iPIC3D is a widely used massively parallel Particle-in-Cell code for the simulation of space plasmas. However, its current implementation does not support execution on multiple GPUs. In this paper, we describe the porting of iPIC3D particle…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-27 Chaitanya Prasad Sishtla , Steven W. D. Chien , Vyacheslav Olshevsky , Erwin Laure , Stefano Markidis

Counterexample-driven genetic programming (CDGP) uses specifications provided as formal constraints to generate the training cases used to evaluate evolving programs. It has also been extended to combine formal constraints and user-provided…

Neural and Evolutionary Computing · Computer Science 2024-08-26 Thomas Helmuth , Edward Pantridge , James Gunder Frazier , Lee Spector

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

We present new algorithms for the parallelization of Eulerian-Lagrangian interaction operations in the immersed boundary method. Our algorithms rely on two well-studied parallel primitives: key-value sort and segmented reduce. The use of…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-02 Andrew Kassen , Varun Shankar , Aaron L Fogelson

Machine learning (ML) workloads launch hundreds to thousands of short-running GPU kernels per iteration. With GPU compute throughput growing rapidly, CPU-side launch latency of kernels is emerging as a bottleneck. CUDA Graphs promise to…

Machine Learning · Computer Science 2025-12-24 Abhishek Ghosh , Ajay Nayak , Ashish Panwar , Arkaprava Basu

Modern computing workloads commonly involve matrix-matrix multiplication (mmul) as a core computing pattern. Coarse-Grained Reconfigurable Arrays (CGRAs) can flexibly and efficiently support it, since they combine operation-level…

Hardware Architecture · Computer Science 2026-04-29 Yuxuan Wang , María José Belda , Fernando Castro , Katzalin Olcoz , David Atienza , Giovanni Ansaloni

We present a reversible intermediate language with concurrency for translating a high-level concurrent programming language to another lower-level concurrent programming language, keeping reversibility. Intermediate languages are commonly…

Programming Languages · Computer Science 2023-09-15 Shunya Oguchi , Shoji Yuen

Subgraph Isomorphism uses a small graph as a pattern to identify within a larger graph a set of vertices that have matching edges. This paper addresses a logic program written in Prolog for a specific relatively complex graph pattern for…

Logic in Computer Science · Computer Science 2026-01-14 Claire Y. Yin , Peter M. Kogge

We introduce a GUI fronted program that can compute combinatorial properties and topological invariants of recognisable and primitive symbolic substitutions on finite alphabets and their associated tiling spaces. We introduce theory from…

Dynamical Systems · Mathematics 2015-12-02 Scott Balchin , Dan Rust

What is the best representation for doing euclidean geometry on computers? These notes from a SIGGRAPH 2019 short course entitled "Geometric algebra for computer graphics" introduce projective geometric algebra (PGA) as a modern framework…

Graphics · Computer Science 2020-08-19 Charles G. Gunn

A reference implementation of a new method in isogeometric analysis (IGA) is presented. It delivers low-cost variable-scale approximations (surrogates) of the matrices which IGA conventionally requires to be computed by element-scale…

Mathematical Software · Computer Science 2020-04-14 Daniel Drzisga , Brendan Keith , Barbara Wohlmuth

Sparse graphs are ubiquitous in real and virtual worlds. With the phenomenal growth in semi-structured and unstructured data, sizes of the underlying graphs have witnessed a rapid growth over the years. Analyzing such large structures…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-08 Ashwina Kumar , M. Venkata Krishna , Prasanna Bartakke , Rahul Kumar , Rajesh Pandian M , Nibedita Behera , Rupesh Nasre

Future computing systems, from handhelds to supercomputers, will undoubtedly be more parallel and heterogeneous than todays systems to provide more performance and energy efficiency. Thus, GPUs are increasingly being used to accelerate…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-18 Saeed Taheri , Apan Qasem , Martin Burtscher
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