2026-10-13T06:21:33Z https://www.scidb.cn/oai

10.57760/sciencedb.012uz 2026-09-16T14:02:53Z

2026-09-16 Reliability-Aware Robust Scheduling for Heterogeneous Onboard High-Performance Computing doi:10.57760/sciencedb.012uz en This package provides the reproducible source code and generated outputs for Reliability-Aware Robust Scheduling for Heterogeneous Onboard High-Performance Computing. It includes a Python decision-level discrete-event simulator, test scripts, input parameters for an eight-task and four-resource heterogeneous computing scenario, a fixed random seed, CSV outputs for baseline comparison, disturbance-intensity sweeps, protection-budget sweeps, and independent resource-fault injection, together with figures generated from the source code.The simulation represents CPU, GPGPU, NPU, and FPGA resources. It computes task-DAG scheduling decisions using resource compatibility, communication costs, first-order RC thermal dynamics, health-adjusted risk, and budgeted uncertainty protection. Static, HEFT, E-HEFT, NMC, and RaRS are evaluated with shared stochastic traces within each replay. The default configuration uses seed 20260915 and 2,000 replays per disturbance point.This package is a calibrated synthetic decision-level model. It contains no in-orbit telemetry, hardware measurements, or flight-qualification data. It supports inspection and reproduction of the scheduling logic, model parameters, generated outputs, and stated experimental scope. supercomputing; Heterogeneous; Reliability-Aware Robust Scheduling 赵文杰 PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank