Added MEATRO-like mapping as a result

build.py

@@ -1,7 +1,7 @@
 import os, sys
 commit_id = 'e1d8efd8e5469cf865a9db60007a70e3f0cb8778'
 dst_path = "cost_model/maestro"
-maestro_dir = "../maestro"
+maestro_dir = "../qmaestro"
 working_path = os.getcwd()
 dst_path = os.path.join(working_path, dst_path)
 maestro = os.path.join(maestro_dir, "maestro")

data/mapping_cstr/advanced_cstr/costmodel_cstr/maestro_cstr.py

@@ -1,5 +1,8 @@
 import numpy as np
 mapping_cstr = {}
+mapping_cstr["L3"] = {"R":"R",
+                      "S":"S",
+                      }
 mapping_cstr["L2"] = {"R":"R",
                       "S":"S",
                       }

data/model/vgg16.csv

@@ -1,14 +1,14 @@
-K,C,Y,X,R,S,T
-64,3,224,224,3,3,1
-64,64,224,224,3,3,1
-128,64,112,112,3,3,1
-128,128,112,112,3,3,1
-256,128,56,56,3,3,1
-256,256,56,56,3,3,1
-256,256,56,56,3,3,1
-512,256,28,28,3,3,1
-512,512,28,28,3,3,1
-512,512,28,28,3,3,1
-512,512,14,14,3,3,1
-512,512,14,14,3,3,1
-512,512,14,14,3,3,1
+K,C,Y,X,R,S,T,Precision
+64,3,224,224,3,3,1,FP16
+64,64,224,224,3,3,1,FP16
+128,64,112,112,3,3,1,FP16
+128,128,112,112,3,3,1,FP16
+256,128,56,56,3,3,1,FP16
+256,256,56,56,3,3,1,FP16
+256,256,56,56,3,3,1,FP16
+512,256,28,28,3,3,1,FP16
+512,512,28,28,3,3,1,FP16
+512,512,28,28,3,3,1,FP16
+512,512,14,14,3,3,1,FP16
+512,512,14,14,3,3,1,FP16
+512,512,14,14,3,3,1,FP16

extract_dataflow.py

@@ -0,0 +1,61 @@
+import os
+import argparse
+
+def extract_sections(file_name, output_folder, output_file_name=None):
+    # Read the content of the original file
+    with open(file_name, 'r') as f:
+        content = f.read()
+
+    # Initialize sections
+    precision_section = ""
+    dataflow_section = ""
+
+    # Find the Precision section, if it exists
+    precision_start_index = content.find("Precision:")
+    if precision_start_index != -1:
+        precision_end_index = content.find("}", precision_start_index) + 1
+        precision_section = content[precision_start_index:precision_end_index]
+        precision_section += '\n'
+
+    # Find the Dataflow section
+    dataflow_start_index = content.find("Dataflow {")
+    if dataflow_start_index != -1:
+        dataflow_end_index = content.find("}", dataflow_start_index) + 1
+        dataflow_section = content[dataflow_start_index:dataflow_end_index]
+        dataflow_section += '\n'
+
+        # Indent lines in Dataflow section (excluding the first and last lines)
+        dataflow_lines = dataflow_section.split('\n')
+        indented_dataflow_lines = '\n'.join(dataflow_lines[0:1] + ['\t' + line for line in dataflow_lines[1:-1]] + dataflow_lines[-1:])
+        dataflow_section = indented_dataflow_lines
+
+    # Create the output folder if it doesn't exist
+    if not os.path.exists(output_folder):
+        os.makedirs(output_folder)
+
+    # Determine the output file name
+    if output_file_name is None:
+        output_file_name = os.path.basename(file_name)
+    output_file_path = os.path.join(output_folder, output_file_name)
+
+    # Write the modified Precision and Dataflow sections to the new file
+    with open(output_file_path, 'w') as f:
+        if precision_section:
+            f.write(precision_section)
+        if dataflow_section:
+            f.write(dataflow_section)
+
+if __name__ == "__main__":
+    # Create an argument parser
+    parser = argparse.ArgumentParser(description='Extract Precision and Dataflow from a file and save to a new file.')
+
+    # Add the file and output folder arguments
+    parser.add_argument('--file', type=str, required=True, help='Path of the input file')
+    parser.add_argument('--out', type=str, required=True, help='Path of the output folder')
+    parser.add_argument('--outname', type=str, help='Optional name of the output file')
+
+    # Parse the command-line arguments
+    args = parser.parse_args()
+
+    # Extract the Precision and Dataflow parts and save them to the output folder
+    extract_sections(args.file, args.out, args.outname)

from_maestro_to_gamma.py

@@ -0,0 +1,49 @@
+import csv
+import re
+import argparse
+
+def parse_m_file(file_path):
+    layers = []
+    with open('../qmaestro/data/model/' + file_path, 'r') as file:
+        with open('../qmaestro/data/model/' + file_path, 'r') as file:
+            content = file.read()
+            layers_type = re.findall(r'Type: (\w+)', content, re.DOTALL)
+            dimension_matches = re.findall(r'Dimensions \{.*?\}', content, re.DOTALL)
+
+            for i, dimensions in enumerate(dimension_matches):
+                dim_values = re.findall(r'\b\w: \d+', dimensions)
+                dim_dict = {d.split(': ')[0]: int(d.split(': ')[1]) for d in dim_values}
+                if layers_type[i] == 'DSCONV':
+                    dim_dict['T'] = 2
+                else:
+                    dim_dict['T'] = 1
+                layers.append(dim_dict)
+    return layers
+
+def write_csv(layers, precision, output_file):
+    with open('./data/model/'+ output_file, mode='w', newline='') as file:
+        writer = csv.writer(file)
+        writer.writerow(["K", "C", "Y", "X", "R", "S", "T", "Precision"])
+        for layer in layers:
+            t_value = 2 if layer.get('Type') == 'DSCONV' else 1
+            writer.writerow([
+                layer.get('K', 0),
+                layer.get('C', 0),
+                layer.get('Y', 0),
+                layer.get('X', 0),
+                layer.get('R', 0),
+                layer.get('S', 0),
+                layer.get('T', 0),
+                precision
+            ])
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description='Parse a .m file and generate a CSV.')
+    parser.add_argument('input_file', type=str, help='Path to the input .m file')
+    parser.add_argument('precision', type=str, help='Precision value for the CSV')
+    parser.add_argument('output_file', type=str, help='Path to the output CSV file')
+    args = parser.parse_args()
+
+    layers = parse_m_file(args.input_file)
+    write_csv(layers, args.precision, args.output_file)

run_digamma.sh

@@ -0,0 +1,12 @@
+cd ./src/GAMMA
+
+
+python main.py --num_pe -1 --area_budget 0.2 --pe_limit 200 --model vgg16 --outdir outdir_digamma
+
+cd ../../
+
+
+
+
+
+

run_gamma.sh

@@ -1,6 +1,6 @@
 cd ./src/GAMMA
 python main.py --fitness1 latency --fitness2 power --num_pe 168 --l1_size 512 --l2_size 108000 --NocBW 81920000 --epochs 10 \
-              --model vgg16 --singlelayer 1
+              --model vgg16 --num_layer 13 #--singlelayer 1 
 cd ../../
 
 

run_gamma_map_cstr.sh

@@ -0,0 +1,10 @@
+cd ./src/GAMMA
+python main.py --mapping_cstr dla_map --fitness1 latency --fitness2 power --num_pe 168 --l1_size 512 --l2_size 108000 --NocBW 81920000 --epochs 10 \
+              --model vgg16 --outdir outdir_map
+cd ../../
+
+
+
+
+
+

script/avg_exec_time.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+cd ..
+# Number of executions
+num_executions=10
+total_execution_time_ns=0
+
+for ((i=1; i<=$num_executions; i++)); do
+
+    start_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    ./run_gamma.sh
+
+    end_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    elapsed_time_ms=$((end_time - start_time))
+
+    total_execution_time_ms=$((total_execution_time_ms + elapsed_time_ms))
+done
+
+
+average_execution_time_ms=$((total_execution_time_ms / num_executions))
+
+# Display the total execution time in nanoseconds
+echo "Gamma -> Avg Execution Time: $average_execution_time_ms ms"  >> "output.txt"

script/avg_exec_time_digamma.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+cd ..
+# Number of executions
+num_executions=10
+total_execution_time_ns=0
+
+for ((i=1; i<=$num_executions; i++)); do
+
+    start_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    ./run_digamma.sh
+
+    end_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    elapsed_time_ms=$((end_time - start_time))
+
+    total_execution_time_ms=$((total_execution_time_ms + elapsed_time_ms))
+done
+
+
+average_execution_time_ms=$((total_execution_time_ms / num_executions))
+
+# Display the total execution time in nanoseconds
+echo "DiGamma -> Avg Execution Time: $average_execution_time_ms ms" >> "output.txt"

script/avg_exec_time_map_cstr.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+cd ..
+# Number of executions
+num_executions=10
+total_execution_time_ns=0
+
+for ((i=1; i<=$num_executions; i++)); do
+
+    start_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    ./run_gamma_map_cstr.sh
+
+    end_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    elapsed_time_ms=$((end_time - start_time))
+
+    total_execution_time_ms=$((total_execution_time_ms + elapsed_time_ms))
+done
+
+
+average_execution_time_ms=$((total_execution_time_ms / num_executions))
+
+# Display the total execution time in nanoseconds
+echo "Map Cstr -> Avg Execution Time: $average_execution_time_ms ms" >> "output.txt"

script/avg_exec_time_with_hwconfig.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+cd ..
+# Number of executions
+num_executions=10
+total_execution_time_ns=0
+
+for ((i=1; i<=$num_executions; i++)); do
+
+    start_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+     ./run_gamma_with_hwconfig.sh
+
+    end_time=$(perl -MTime::HiRes -e 'printf("%.0f\n",Time::HiRes::time()*1000)')
+
+    elapsed_time_ms=$((end_time - start_time))
+
+    total_execution_time_ms=$((total_execution_time_ms + elapsed_time_ms))
+done
+
+
+average_execution_time_ms=$((total_execution_time_ms / num_executions))
+
+# Display the total execution time in nanoseconds
+echo "Av Execution Time: $average_execution_time_ms ms"

script/delete_file.sh

@@ -0,0 +1,12 @@
+folder_path="$HOME/Desktop/Tesi/gamma/src/GAMMA"
+
+# Navigate to the folder
+cd "$folder_path" || exit
+
+# Delete .csv files
+find . -type f -name "*.csv" -delete
+
+# Delete .m files
+find . -type f -name "*.m" -delete
+
+echo "Deletion complete for .csv and .m files in $folder_path"

script/run_all.sh

@@ -0,0 +1,3 @@
+./avg_exec_time.sh 
+./avg_exec_time_map_cstr.sh
+./avg_exec_time_digamma.sh 

script/run_digamma.sh

@@ -0,0 +1,12 @@
+cd ./src/GAMMA
+
+
+python main.py --num_pe -1 --area_budget 0.2 --pe_limit 200 --model vgg16 --outdir outdir_digamma
+
+cd ../../
+
+
+
+
+
+

script/run_gamma_map_cstr.sh

@@ -0,0 +1,10 @@
+cd ./src/GAMMA
+python main.py --mapping_cstr dla_map --fitness1 latency --fitness2 power --num_pe 168 --l1_size 512 --l2_size 108000 --NocBW 81920000 --epochs 10 \
+              --model vgg16 --outdir outdir_map
+cd ../../
+
+
+
+
+
+