Clone the RapidChiplet repository:
git clone https://github.com/spcl/rapidchiplet.gitInstall all requirements using pip:
cd rc
pip install -r requirements.txtBuild the BookSim2 [1,2] simulator:
cd booksim2/src
make
cd ../../Build Netrace [3,4]
cd netrace
gcc export_trace.c netrace.c -o export_trace
cd ../python3 reproduce_paper_results.py- Note that this script runs for almost one day.
- The results might slightly differ from the paper due to different system specifications.
- The plots that appear in the paper in Figure 4 (right), Figure 5, and Figure 6 will be stored in the
./plots/directory. - The chip visualization that appears in the paper in Figure 4 (left) will be stored in the
./images/directory.
Configure your chip design using the different input files. Check out the example files in ./inputs/ to get started.
We provide the following input generation scripts for more complex input-files that cannot easily be written by hand:
generate_routing.py: Generates a routing table for a given chip design
python3 generate_routing.py -df inputs/designs/<design_file> -rtf <routing_table_file> -ra <routing_algorithm>- The
<design file>points to all inputs that the routing table generator needs (chiplets, placement, topology). - The
<routing_table_file>is the name under which the resulting routing table is stored (ininputs/routing_tables/). <routing algorithm>specifies the routing algorithm to be used. We currently support two routing algorithms:splif: Shortest Path Lowest ID firstsptmr: Shortest Path Turn Model Random
generate_traffic.py: Generate a synthetic traffic pattern for a given chip design
python3 generate_traffic.py -df inputs/designs/<design_file> -tf <traffic_file> -tp <traffic_pattern> -par <parameters>- The
<design file>points to all inputs that the traffic generator needs (chiplets, placement). - The
<traffic_file>is the name under which the resulting traffic pattern is stored (in/inputs/traffic_by_chiplet/andinputs/traffic_by_unit/). <traffic_pattern>specifies the traffic pattern to be generated. We currently support four traffic patterns:random_uniform,transpose,permutation,hotspot.<parameters>are specific to the selected traffic pattern.
python3 rapidchiplet.py -df inputs/designs/<design_file> -rf <results_file> [-as] [-ps] [-ls] [-c] [-l] [-t]- The
<design_file>points to all inputs that are required - The
<results_file>specifies the name, under which the results are stored (in/results/). - The optional flags are used to enable the computation of different metrics: area summary (
-as), power summary (-ps), link summary (-ls), manufacturing cost (-c), latency (-l), throughput (-t).
To export a design to BookSim and gather the results, simply run rapidchiplet.py with the -bs flag:
python3 rapidchiplet.py -df inputs/designs/<design_file> -rf <results_file> -bs- The
<design_file>points to all inputs that are required. - The
<results_file>specifies the name, under which the results are stored (in/results/).
Specify parameters and parameter-ranges for your design space exploration in an experiment-file in the ./experiments/ directory. Check out the provided example files to get started.
python3 run_experiment.py -e experiments/<experiment_file>This script generates one results-file for each combination of input parameters. All result-files are stored in ./results/.
Download the traces from the netrace website [5] and store them in ./netrace/traces_in/.
In a first step, export the traces from the netrace format into an intermediate format:
cd netrace
./export_trace traces_in/<trace_name>.tra.bz2 <trace_region_id> <packet_limit> > traces_out/<trace_name>.json
cd ../- Netrace traces contain one or multiple trace regions. Use the
<trace_region_id>argument to specify the region to export. If you want to export the whole trace, omit this argument. - Some Netrace traces are very long. If you only want to export a partial trace region, use the
<packet_limit>argument to pass the maximum number of packets that should be exported.
In a second step, the trace is parsed into the RapidChiplet format:
python3 parse_netrace_trace.py -df inputs/designs/<design_file> -if netrace/traces_out/<trace_name>.json -of <trace_name>.json- The
<design file>points to all inputs that the trace parser needs. - The arguments
-ifand-ofrefer to the input-trace-file (in the intermediate format) and the output-trace-file (in the output format). The output trace file is stored ininputs/traces/.
Visualize a complete design by running
python3 visualizer.py -df inputs/designs/<design_name> [-sci] [-spi]- You can show chiplet-IDs and PHY-IDs by passing the
-sciand-spiflags respectively.
You can also visualize a single chiplet by running
python3 visualizer.py -cf inputs/chiplets/<chiplet_file> -cn <chiplet_name><chiplet_file>is an input file which potentially specifies multiple chiplets and<chiplet_name>is the name of one specific chiplet within this file.
Visualize the results by running:
python3 create_plots.py -rf results/<results-file> -pt <plot_type>- The
<results_file>contains the results you want to visualize. - Currently, only one plot type, namely,
latency_vs_loadis supported, but more will be added soon.
[1] Jiang, N., Becker, D.U., Michelogiannakis, G., Balfour, J., Towles, B., Shaw, D.E., Kim, J. and Dally, W.J., 2013, April. A detailed and flexible cycle-accurate network-on-chip simulator. In 2013 IEEE international symposium on performance analysis of systems and software (ISPASS) (pp. 86-96). IEEE.
[2] https://github.com/booksim/booksim2
[3] Hestness, J., Grot, B. and Keckler, S.W., 2010, December. Netrace: dependency-driven trace-based network-on-chip simulation. In Proceedings of the Third International Workshop on Network on Chip Architectures (pp. 31-36).