This repository bundle provides configuration files, scripts, and example datasets to reproduce the experiments in Volatility-Aware Hybrid Memory Architecture for Real-Time and Persistent Big Data Systems.
Contents
simulators/— DRAMSim3 and NVMain config templates and driver stubs.workloads/— small synthetic workload generators (YCSB-like and Spark trace generator stub).ml/— feature extractor and Random Forest training script (scikit-learn).analysis/— result aggregation and plotting scripts.supplementary/— Supplementary tables of parameters and baseline configs.run_all.sh— top-level script to run a minimal end-to-end example (requires external simulators).
Important This bundle provides ready-to-run scripts assuming the environment has:
- DRAMSim3 installed and available on PATH (or you can provide the path in
simulators/README_simulators.md). - NVMain installed and available on PATH.
- Python 3.8+ with dependencies listed in
requirements.txt(scikit-learn, numpy, pandas, matplotlib). - Apache Spark installed and configured if you want to run the Spark-based workloads.