adds new branch for some benchmark scripts
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										108
									
								
								benchmarks/dhrystone_run_multiple.py
									
									
									
									
									
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										108
									
								
								benchmarks/dhrystone_run_multiple.py
									
									
									
									
									
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import argparse
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import os
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import shutil
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import subprocess
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import time
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from pathlib import Path
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def run_command(command, cwd=None):
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    """Run a shell command in the specified directory and return its output."""
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    result = subprocess.run(
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        command,
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        shell=True,
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        cwd=cwd,
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        stdout=subprocess.PIPE,
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        stderr=subprocess.PIPE,
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        check=False,
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    )
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    return result.stdout.decode("utf-8"), result.stderr.decode("utf-8")
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def build_test_cases(makefile_dir, iterations):
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    """Run the Makefile with the specified iterations."""
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    make_command = f"make clean && make ITERATIONS={iterations}"
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    stdout, stderr = run_command(make_command, cwd=makefile_dir)
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    if stderr:
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        raise RuntimeError(f"Error during make: {stderr}")
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def main(simulator_path, makefile_dir):
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    # Directory for generated test cases
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    generated_dir = makefile_dir.parent / "workspace"
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    os.makedirs(generated_dir, exist_ok=True)
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    # Define the iterations
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    iterations_list = [10, 20, 30]
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    # 15 value up to 6.000.000 evenly apart on a log scale
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    iterations_list = [
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        1,
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        2,
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        4,
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        8,
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        17,
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        34,
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        69,
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        141,
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        287,
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        582,
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        1182,
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        2401,
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        4878,
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        9910,
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        20133,
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        40914,
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        83103,
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        168830,
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        343042,
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        696712,
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        1414641,
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        2874878,
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        5837995,
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    ]
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    for iteration in iterations_list:
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        try:
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            # Update the Makefile with the current ITERATIONS value
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            build_test_cases(makefile_dir, iteration)
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        except RuntimeError as e:
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            print(f"Error during compilation with ITERATIONS={iteration}: {e}")
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            continue
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        # Run the simulator with the generated test case
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        exe = makefile_dir / "dhrystone.elf"
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        if not exe.is_file():
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            exit(f"{exe} does not exist")
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        verbose_exe = generated_dir / "bin" / f"dhrystone_{iteration}.elf"
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        os.makedirs(verbose_exe.parent, exist_ok=True)
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        shutil.copy(exe, verbose_exe)
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        backends = ["interp", "llvm", "tcc", "asmjit"]
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        for backend in backends:
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            log_file = os.path.join(generated_dir, f"{backend}_{iteration}.log")
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            sim_command = f"{simulator_path} -f {exe} --backend {backend}"
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            start_time = time.time()
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            sim_stdout, sim_stderr = run_command(sim_command)
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            end_time = time.time()
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            elapsed_time = end_time - start_time
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            # Save the output to the logfile
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            with open(log_file, "w", encoding="utf8") as f:
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                f.write(sim_stdout)
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                if sim_stderr:
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                    f.write(f"\nErrors:\n{sim_stderr}")
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            print(
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                f"Ran {backend} in {elapsed_time:.2f} s, Output saved to {backend}_{iteration}.log"
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            )
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if __name__ == "__main__":
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    parser = argparse.ArgumentParser(
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        description="Run simulations with generated test cases."
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    )
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    parser.add_argument("simulator_path", help="Path to the simulator executable.")
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    args = parser.parse_args()
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    dhrystone_path = Path(__file__).parent / "dhrystone"
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    main(args.simulator_path, dhrystone_path)
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										86
									
								
								benchmarks/visualize_runtimes.py
									
									
									
									
									
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										86
									
								
								benchmarks/visualize_runtimes.py
									
									
									
									
									
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							@@ -0,0 +1,86 @@
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import argparse
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import os
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import re
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from pathlib import Path
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import plotly.express as px
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import yaml
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def parse_logs(log_dir):
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    results = []
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    for filename in os.listdir(log_dir):
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        if filename.endswith(".log"):
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            filepath = os.path.join(log_dir, filename)
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            with open(filepath, "r", encoding="utf8") as file:
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                for line in file:
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                    if (
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                        "Executed" in line
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                        and "instructions" in line
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                        and "during" in line
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                        and "resulting in" in line
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                    ):
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                        parts = line.split()
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                        instructions = int(parts[3])
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                        time_idx = parts.index("during") + 1
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                        time = int(parts[time_idx].rstrip("ms"))
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                        mips_idx = parts.index("resulting") + 2
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                        mips = float(parts[mips_idx].rstrip("MIPS"))
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                        backend, iterations, _ = re.split(r"[_.]", filename)
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                        results.append(
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                            {
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                                "backend": backend,
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                                "run_count": int(iterations),
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                                "instructions": instructions,
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                                "time": time,
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                                "mips": mips,
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                            }
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                        )
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    return results
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def write_yaml(results, output_file):
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    with open(output_file, "w", encoding="utf8") as file:
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        yaml.dump(results, file)
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def visualize_mips_over_instructions(yaml_file):
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    # Read data from YAML file
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    with open(yaml_file, "r", encoding="utf8") as file:
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        data = yaml.safe_load(file)
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    # Extract instructions and MIPS values
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    run_count = [entry["run_count"] for entry in data]
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    mips = [entry["mips"] for entry in data]
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    backends = [entry["backend"] for entry in data]
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    # Create scatter plot using Plotly Express
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    fig = px.line(
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        x=run_count,
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        y=mips,
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        color=backends,
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        labels={"x": "Dhrystone Iterations", "y": "MIPS", "color": "Backend"},
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        title="MIPS over Amount of Dhrystone Iterations",
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        log_x=True,
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    )
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    fig.show()
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def main():
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    parser = argparse.ArgumentParser(
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        description="""
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        Parse log files and extract relevant information. Create a 'results.yaml' file and visualize it.
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        Intended to be run after 'dhrystone_run_multiple.py'"""
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    )
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    parser.add_argument("log_dir", help="Path to the directory containing log files.")
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    args = parser.parse_args()
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    result_file = Path(__file__).parent / "results.yaml"
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    if not result_file.is_file():
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        results = parse_logs(args.log_dir)
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        write_yaml(results, result_file)
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    visualize_mips_over_instructions(result_file)
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if __name__ == "__main__":
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    main()
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