PaCRAM: Understanding RowHammer Under Reduced Refresh Latency: Experimental Analysis of Real DRAM Chips and Implications on Future Solutions

PaCRAM is a technique that reduces the performance overhead of RowHammer mitigation mechanisms by carefully reducing the preventive refresh latency that are issued by RowHammer mitigations without compromising system security.

Repository File Structure

.
+-- DB_scripts/                           # Scripts to parse and plot DRAM Bender Results
+-- Ram_scripts/                          # Scripts to parse and plot Ramulator2 results
│   +-- ramulator_pacram/src              # Ramulator2 source code
│   │   +-- dram/impl
│   │   │   +-- DDR5-RVRR.cpp             # DDR5 implementation that supports partial charge restoration
│   │   +-- dram_controller
│   │   │   +-- impl/plugin
│   │   │   │   │   +-- pacram.h          # Ramulator2 plugin that implements PaCRAM
│   │   ...
...
+-- README.md                             # This file                        

Installation Guide:

Prerequisites:

• Git
• g++ with c++20 capabilities (g++-10 or above recommended)
• Python3 (3.10 or above recommended)

Installation steps:

1. Clone the repository git clone https://github.com/yct000/PaCRAM
2. Install python dependencies, build Ramulator2, and download DRAM Bender results and traces with ./setup_all.sh

Example Use

1. Parse and plot DRAM Bender results ./plot_db_figures.sh or plot_db_figures_slurm.sh.
2. Prepare Ramulator2 warmup checkpoints ./prepare_warmups.sh or ./prepare_warmups_slurm.sh.
3. Wait for the warmup runs to finish. You can use python3 check_warmup_status.py to track warmup status. If it reports any failed or not found runs, you can rerun step 2.
4. Run Ramulator2 simulations ./run_ramulator_all.sh or ./run_ramulator_all_slurm.sh.
5. Wait for the runs to finish. You can use python3 check_run_status.py to track run status. If it reports any failed or not found runs, you can rerun step 4.
6. Parse simulation results and process them with ./parse_ram_results.sh
7. Generate figures with ./plot_ram_figures.sh

Simulation Configuration Parameters

Execution of Ramulator2 simulations can be configured with the following configuration parameters. These parameters reside in Ram_scripts/utils_runs.py.

MITIGATION_LIST: The list of tested RowHammer mitigations

NRH_VALUES: The list of tested RowHammer threshold values

MFR_DICT: The dictionary of charge restoration amounts for different manufacturers

While using Slurm with a cluster, Slurm parameters can be configured with the following parameters. These parameters reside in Ram_scripts/utils_slurm.py.

MAX_SLURM_JOBS: The maximum number of runs that the cluster can run simultaneously

SLURM_RETRY_DELAY: The delay between retrying Slurm job submission when job limit is reached

Contacts:

Yahya Can Tuğrul (yahyacantugrul [at] gmail [dot] com)