RenderKernel: High-level programming for real-time rendering systems

Real-time rendering applications leverage heterogeneous computing to optimize performance. However, software development across multiple devices presents challenges, including data layout inconsistencies, synchronization issues, resource management complexities, and architectural disparities. Additionally, the creation of such systems requires verbose and unsafe programming models. Recent developments in domain-specific and unified shading languages aim to mitigate these issues. Yet, current programming models primarily address data layout consistency, neglecting other persistent challenges.In this paper, we introduce RenderKernel, a programming model designed to simplify the development of real-time rendering systems. Recognizing the need for a high-level approach, RenderKernel addresses the specific challenges of real-time rendering, enabling development on heterogeneous systems as if they were homogeneous. This model allows for early detection and prevention of errors due to system heterogeneity at compile-time. Furthermore, RenderKernel enables the use of common programming patterns from homogeneous environments, freeing developers from the complexities of underlying heterogeneous systems. Developers can focus on coding unique application features, thereby enhancing productivity and reducing the cognitive load associated with real-time rendering system development.

Authors

Institutions

Publication Details

Journal
Visual Informatics
Published
2024-09-01
DOI
https://doi.org/10.1016/j.visinf.2024.09.004
Citations
1
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
0.63

Funders

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

RenderKernel: High-level programming for real-time rendering systems

Soumyabrata Dev, Jinyuan Yang, Abraham G. Campbell
1 citations
Visual Informatics
Computer Graphics and Visualization Techniques
0.63
article

RenderKernel: High-level programming for real-time rendering systems

Soumyabrata Dev, Jinyuan Yang, Abraham G. Campbell
article en
1 citations

Abstract

Real-time rendering applications leverage heterogeneous computing to optimize performance. However, software development across multiple devices presents challenges, including data layout inconsistencies, synchronization issues, resource management complexities, and architectural disparities. Additionally, the creation of such systems requires verbose and unsafe programming models. Recent developments in domain-specific and unified shading languages aim to mitigate these issues. Yet, current programming models primarily address data layout consistency, neglecting other persistent challenges.In this paper, we introduce RenderKernel, a programming model designed to simplify the development of real-time rendering systems. Recognizing the need for a high-level approach, RenderKernel addresses the specific challenges of real-time rendering, enabling development on heterogeneous systems as if they were homogeneous. This model allows for early detection and prevention of errors due to system heterogeneity at compile-time. Furthermore, RenderKernel enables the use of common programming patterns from homogeneous environments, freeing developers from the complexities of underlying heterogeneous systems. Developers can focus on coding unique application features, thereby enhancing productivity and reducing the cognitive load associated with real-time rendering system development.

Visual InformaticsVol. 8(3)
University College Dublin (IE)
China Sponsorship Council
Openalex Percentile: Top 21%
Computer Graphics and Visualization Techniques
0.63
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.