遇见数据集

Resource-Aware Rendering Pipelines for High-Fidelity Interactive Narrative Environments

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Zenodo2026-06-17 更新2026-06-18 收录
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This repository contains the raw hardware telemetry data collected during the empirical ablation study for the manuscript "Resource-Aware Rendering Pipelines for High-Fidelity Interactive Narrative Environments." Measurements were captured using HWMonitor on an MSI GP66 Leopard (Intel Core i7-11800H, NVIDIA RTX 3070 8GB) to validate the efficacy of data-parallel optimization strategies (material instancing, texture packing, and visibility culling) under heavy pipeline loads. Files Included: 01_System_Idle_Baseline.jpg: Baseline system metrics prior to engine load (0.0% GPU, ~11W). 02_Optimized_Scene_Initialization.jpg: Telemetry during resource-aware scene load demonstrating low VRAM overhead. 03_Unoptimized_Dense_Village.jpg: Telemetry capturing a heavy memory-fetch bottleneck in unoptimized dense geometry. 04_Optimized_Heavy_Combat.jpg: Telemetry capturing peak shader compute under optimized constraints (99.0% GPU, ~119W). 05_Indoor_Portal_Culling_Room1.jpg: Efficiency metrics demonstrating portal culling in enclosed spaces (99.0% GPU, ~108W). 06_Indoor_Portal_Culling_Room2.jpg: Sustained portal culling efficiency in secondary enclosed space (100.0% GPU, ~107W).

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Zenodo
创建时间:
2026-06-17
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