diff --git a/llvm/projects/soc_simulator/src/driver.py b/llvm/projects/soc_simulator/src/driver.py
index aa20a7e7a22743399d5281889542a79c8adb4397..c747f47d998edaef603a4fc4f38fccb9a4207ea6 100644
--- a/llvm/projects/soc_simulator/src/driver.py
+++ b/llvm/projects/soc_simulator/src/driver.py
@@ -1,12 +1,123 @@
 # Python driver -- ported from Perl driver (driver.pl)
 
+from collections import defaultdict
+import os
 import sys
 
-# Read layer info
+def build_nested_default_dict():
+	return defaultdict(build_nested_default_dict)
 
-# Read tensor info
+tensor_layers = defaultdict(build_nested_default_dict)
 
-# Run simulations on promise
+def is_conv(operation_name):
+    return operation_name.startswith("Conv")
+
+def is_nml(operation_name):
+    return operation_name.startswith("NML")
+
+def is_fc(operation_name):
+    return operation_name.startswith("FC")
+
+def parse_tensor_layer_file(layer_filename): 
+    '''
+    Convs: Layer name, N, Cin, H, W, Cout, Kh, Kw, Sh, Sw
+    FCs: Layer name, Rows_A, Cols_A, Rows_B, Cols_B
+    NMLs (No Man Lands):  NML<number> (edited) 
+    '''
+    if not os.path.isfile(layer_filename):
+        print("ERROR: %s was not found." % layer_filename)
+        exit(1)
+
+    layer_file = open(layer_filename, "r")
+    for line in layer_file:
+        layer_data = line.strip().split(',')
+        layer_name = layer_data[0]
+        
+        if is_conv(layer_name):
+            tensor_layers[layer_name]["N"] = layer_data[1]
+            tensor_layers[layer_name]["Cin"] = layer_data[2]
+            tensor_layers[layer_name]["H"] = layer_data[3]
+            tensor_layers[layer_name]["W"] = layer_data[4]
+            tensor_layers[layer_name]["Cout"] = layer_data[5]
+            tensor_layers[layer_name]["Kh"] = layer_data[6] 
+            tensor_layers[layer_name]["Kw"] = layer_data[7]
+            tensor_layers[layer_name]["Sh"] = layer_data[8]
+            tensor_layers[layer_name]["Sw"] = layer_data[9]
+
+        elif is_fc(layer_name):
+            tensor_layers[layer_name]["RA"] = layer_data[1]
+            tensor_layers[layer_name]["CA"] = layer_data[2]
+            tensor_layers[layer_name]["RB"] = layer_data[3]
+            tensor_layers[layer_name]["CB"] = layer_data[4]
+
+		elif not is_nml(layer_name): # TODO should we store data for NMLs?
+			print("ERROR: Invalid layer name %s" % layer_name)
+			exit(1)
+
+    layer_file.close()
+
+# should this be a nested dict of dicts?
+# [layer_name][operation_name][cols]
+tensor_table = defaultdict(build_nested_default_dict)
+
+def parse_tensor_table(table_filename): 
+    if not os.path.isfile(table_filename):
+        print("ERROR: %s was not found." % table_filename)
+        exit(1)
+
+    table_file = open(table_filename, "r")
+
+	line = table_file.readline().strip()
+
+	while line:
+		# Line here MUST be a header or there's a bug 
+		# Get the description of the layer 
+		assert(line.startswith("**"))
+		header_contents = line.split(' ')[1:] 
+		layer_name = header_contents[0]
+		num_ops = int(header_contents[1])
+		col_names = header_contents[2:]
+
+		# Go through all operations in the layer
+		for op_count in range(num_ops):
+			line = table_file.readline().strip()
+			op_data = line.split(' ')
+			op_name = op_data[0]
+
+			# Number of data items (#s) needs to match up with the # of cols 
+			assert(len(op_data) - 1 == len(col_names)) 
+
+			# Go through all data items (each col element) per operation 
+			for i in range(len(col_names)):
+				tensor_table[layer_name][op_name][col_names[i]] = op_data[i + 1]
+
+    	line = table_file.readline().strip()
+
+	table_file.close()
+
+
+def run_simulations():
+    # open configuration file
+    # open results file
+    # read through each line in the configuration file
+        # for each config file line --> parse the comma separated voltage swing levels
+        # recall: each line = a configuration that works
+        # for each level
+            # if promise --> promise runs an entire layer
+                # quantize, no patching and unpatching
+                # run on promise 
+                # output the total time and energy
+            # else
+                # for each sublevel (separated by spaces)
+                # quantize
+                # run
+                # keep track of total time and energy --> update as needed
+                # output the total time and energy
+
+# quantization: we always have smart dma
+# need to search stuff up
+# $layer = a map of elements
+# stores the layer name, then
 
 if __name__ == "__main__":
     if len(sys.argv) != 4):