InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

ABSTRACT Introduction Unity is a powerful and versatile tool for creating real‐time experiments. It includes a built‐in compute shader language, a C‐like programming language designed for massively parallel General‐Purpose GPU (GPGPU) computing. However, as Unity is primarily developed for multi‐platform game creation, its compute shader language has several limitations, including the lack of multi‐GPU computation support and incomplete mathematical libraries. Contribution To address these limitations, GPU manufacturers have developed specialized programming models, such as CUDA and HIP, which enable developers to leverage the full computational power of modern GPUs. This article introduces an open‐source tool designed to bridge the gap between Unity and CUDA, allowing developers to integrate CUDA's capabilities within Unity‐based projects. Methods The proposed solution establishes an interoperability framework that facilitates communication between Unity and CUDA. The tool is designed to efficiently transfer data, execute CUDA kernels, and retrieve results, ensuring seamless integration into Unity's rendering and computation pipeline. Results Our tool extends Unity's capabilities by enabling CUDA‐based computations, overcoming the inherent limitations of Unity's compute shader language. This integration allows developers to exploit multi‐GPU architectures, leverage advanced mathematical functions, and enhance computational performance for real‐time applications.

Authors

Institutions

Publication Details

Journal
Software Practice and Experience
Published
2025-02-12
DOI
https://doi.org/10.1002/spe.3414
Citations
2
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
4.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Lilian Aveneau, Bérenger Bramas, Emmanuelle Darles, David Algis
2 citations
Software Practice and Experience
Parallel Computing and Optimization Techniques
4.54
article

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Lilian Aveneau, Bérenger Bramas, Emmanuelle Darles, David Algis
article en
2 citations

Abstract

ABSTRACT Introduction Unity is a powerful and versatile tool for creating real‐time experiments. It includes a built‐in compute shader language, a C‐like programming language designed for massively parallel General‐Purpose GPU (GPGPU) computing. However, as Unity is primarily developed for multi‐platform game creation, its compute shader language has several limitations, including the lack of multi‐GPU computation support and incomplete mathematical libraries. Contribution To address these limitations, GPU manufacturers have developed specialized programming models, such as CUDA and HIP, which enable developers to leverage the full computational power of modern GPUs. This article introduces an open‐source tool designed to bridge the gap between Unity and CUDA, allowing developers to integrate CUDA's capabilities within Unity‐based projects. Methods The proposed solution establishes an interoperability framework that facilitates communication between Unity and CUDA. The tool is designed to efficiently transfer data, execute CUDA kernels, and retrieve results, ensuring seamless integration into Unity's rendering and computation pipeline. Results Our tool extends Unity's capabilities by enabling CUDA‐based computations, overcoming the inherent limitations of Unity's compute shader language. This integration allows developers to exploit multi‐GPU architectures, leverage advanced mathematical functions, and enhance computational performance for real‐time applications.

Software Practice and ExperienceVol. 55(6)
Université de Poitiers (FR), Centre Inria de l'Université de Lorraine (FR)
Association Nationale de la Recherche et de la Technologie
Openalex Percentile: Top 8%
Parallel Computing and Optimization Techniques
4.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA — Lilian Aveneau, Bérenger Bramas, et al. · Software Practice and Experience (2025) | TGRS Research Map | TGRS