SimDSL: A Domain-Specific Language for Large-Scale GPU-Resident Simulation

We present SimDSL, a domain-specific language (DSL) for executing large-scale simulations on the GPU using an Entity Component System (ECS) architecture. Systems written in SimDSL are analyzed, lowered into an intermediate representation, and compiled by a CuPy-based backend into CUDA kernels operating over structure-of-arrays archetype tables. We evaluate SimDSL on five workloads: Particle Fountain, Traffic Ring, Reaction Diffusion, Ant Colony, and Tower Defense. The evaluation compares SimDSL with straightforward CuPy and CUDA baseline implementations under matched simulation configurations. Results show that SimDSL sustains GPU-resident execution and achieves favorable performance relative to these baselines. These findings demonstrate that high-level ECS simulation programs can be compiled into efficient GPU execution without requiring users to manually implement and coordinate low-level kernels.

Authors

Institutions

Publication Details

Journal
Software
Published
2026-08-20
DOI
https://doi.org/10.3390/software5030037
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SimDSL: A Domain-Specific Language for Large-Scale GPU-Resident Simulation

Tian Zhao, Anisha Tasnim
Software
Parallel Computing and Optimization Techniques
article

SimDSL: A Domain-Specific Language for Large-Scale GPU-Resident Simulation

Tian Zhao, Anisha Tasnim
article en

Abstract

We present SimDSL, a domain-specific language (DSL) for executing large-scale simulations on the GPU using an Entity Component System (ECS) architecture. Systems written in SimDSL are analyzed, lowered into an intermediate representation, and compiled by a CuPy-based backend into CUDA kernels operating over structure-of-arrays archetype tables. We evaluate SimDSL on five workloads: Particle Fountain, Traffic Ring, Reaction Diffusion, Ant Colony, and Tower Defense. The evaluation compares SimDSL with straightforward CuPy and CUDA baseline implementations under matched simulation configurations. Results show that SimDSL sustains GPU-resident execution and achieves favorable performance relative to these baselines. These findings demonstrate that high-level ECS simulation programs can be compiled into efficient GPU execution without requiring users to manually implement and coordinate low-level kernels.

SoftwareVol. 5(3)
University of Wisconsin–Milwaukee (US)
Openalex Percentile: Top 5%
Parallel Computing and Optimization Techniques
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.