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OpenRAM
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Added tracking for available data.

This commit is contained in:
Hunter Nichols 2019-02-12 16:28:13 -08:00
parent 9e23e6584a
commit a4bb481612
4 changed files with 87 additions and 19 deletions
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4
compiler/characterizer/model_check.py
View File

@ -229,6 +229,10 @@ class model_check(delay):
"""Gets the number of stages in the delay chain from the control logic"""
return len(self.sram.control_logic_rw.replica_bitline.delay_fanout_list)
def get_num_delay_fanout_list(self):
"""Gets the number of stages in the delay chain from the control logic"""
return self.sram.control_logic_rw.replica_bitline.delay_fanout_list
def get_num_delay_stage_fanout(self):
"""Gets fanout in each stage in the delay chain. Assumes each stage is the same"""
return self.sram.control_logic_rw.replica_bitline.delay_fanout_list[0]

5
compiler/characterizer/stimuli.py
View File

@ -258,14 +258,15 @@ class stimuli():
# UIC is needed for ngspice to converge
self.sf.write(".TRAN {0}p {1}n UIC\n".format(timestep,end_time))
self.sf.write(".TEMP {}\n".format(self.temperature))
if OPTS.spice_name == "ngspice":
# ngspice sometimes has convergence problems if not using gear method
# which is more accurate, but slower than the default trapezoid method
# Do not remove this or it may not converge due to some "pa_00" nodes
# unless you figure out what these are.
self.sf.write(".OPTIONS POST=1 RELTOL={0} PROBE method=gear TEMP={1}\n".format(reltol,self.temperature))
self.sf.write(".OPTIONS POST=1 RELTOL={0} PROBE method=gear\n".format(reltol))
else:
self.sf.write(".OPTIONS POST=1 RUNLVL={0} PROBE TEMP={1}\n".format(runlvl,self.temperature))
self.sf.write(".OPTIONS POST=1 RUNLVL={0} PROBE\n".format(runlvl))
# create plots for all signals
self.sf.write("* probe is used for hspice/xa, while plot is used in ngspice\n")

11
compiler/tests/config_data.py
View File

@ -3,9 +3,14 @@ word_size = 1
num_words = 16
tech_name = "freepdk45"
#process_corners = ["TT", "FF", "SS", "SF", "FS"]
process_corners = ["TT", "FF", "SS"]
#Default corner
process_corners = ["TT"]
supply_voltages = [1.0]
temperatures = [25]
#temperatures = [25]
#Corner options
#process_corners = ["TT", "FF", "SS"]
#supply_voltages = [.9, 1.0, 1.1]
temperatures = [10,25,50]

86
compiler/tests/delay_data_collection.py
View File

@ -16,6 +16,7 @@ from sram import sram
from sram_config import sram_config
MODEL_DIR = "model_data/"
DATASET_CSV_NAME = MODEL_DIR+'datasets.csv'
class data_collection(openram_test):
@ -24,11 +25,56 @@ class data_collection(openram_test):
#Uncomment this for model evaluation
# ratio_data = self.calculate_delay_ratios_of_srams()
# self.display_data(ratio_data)
self.setup_files()
self.run_delay_chain_analysis()
globals.end_openram()
def setup_files(self):
"""Checks existence of files used for data collection"""
if not os.path.isdir(MODEL_DIR):
os.mkdir(MODEL_DIR)
#File requires names from the delay measurement object.
#Initialization is delayed until one configuration simulation has occurred.
self.dataset_initialized=False
def init_dataset_csv(self, file_fields):
"""Creates csv which holds files names of all available datasets."""
debug.info(2,'Initializing dataset file and dataframe.')
self.file_fields = file_fields
self.file_fields.sort()
fields = ['word_size', 'num_words', 'words_per_row', 'dc_config']
self.dataset_fields = fields+self.file_fields
if not os.path.exists(DATASET_CSV_NAME):
debug.info(2,'No dataset file found. Creating dataset file.')
dataset_csv = open(DATASET_CSV_NAME, 'w')
csv_writer = csv.writer(dataset_csv, lineterminator = '\n')
csv_writer.writerow(self.dataset_fields)
dataset_csv.close()
self.dataset_initialized=True
self.datasets_df = pd.read_csv(DATASET_CSV_NAME, encoding='utf-8')
def add_dataset(self, word_size, num_words, words_per_row):
"""Added filenames to DATASET_CSV_NAME"""
cur_len = len(self.datasets_df)
#list converted to str as lists as saved as str in the csv file.
#e.g. list=[2,2] -> csv entry = '[2,2]'
fanout_str = str(self.delay_obj.get_num_delay_fanout_list())
file_names = [self.file_name_dict[fname] for fname in self.file_fields]
new_df_row = [word_size, num_words, words_per_row,fanout_str]+file_names
df_bool = (self.datasets_df['word_size'] == word_size) & (self.datasets_df['num_words'] == num_words) & (self.datasets_df['words_per_row'] == words_per_row) & (self.datasets_df['dc_config'] == fanout_str)
if len(self.datasets_df.loc[df_bool]) == 0:
self.datasets_df = self.datasets_df.append(pd.Series(new_df_row, self.dataset_fields), ignore_index=True)
else:
self.datasets_df.loc[df_bool] = [new_df_row]
def run_delay_chain_analysis(self):
"""Generates sram with different delay chain configs over different corners and
analyzes delay average and variation."""
@ -84,7 +130,7 @@ class data_collection(openram_test):
plt.show()
def plot_two_data_sets(self, x_labels, y1_values, y2_values):
"""Plots two data sets on the same x-axis."""
"""Plots two data sets on the same x-axis. Uses hardcoded axis names."""
data_range = [i for i in range(len(x_labels))]
fig, ax1 = plt.subplots()
@ -123,8 +169,9 @@ class data_collection(openram_test):
def get_csv_data(self):
"""Hardcoded Hack to get the measurement data from the csv into lists. """
wl_files_name = [file_name for file_name in self.file_names if "wl_measures" in file_name][0]
sae_files_name = [file_name for file_name in self.file_names if "sae_measures" in file_name][0]
file_list = self.file_name_dict.values()
wl_files_name = [file_name for file_name in file_list if "wl_measures" in file_name][0]
sae_files_name = [file_name for file_name in file_list if "sae_measures" in file_name][0]
wl_dataframe = pd.read_csv(wl_files_name,encoding='utf-8')
sae_dataframe = pd.read_csv(sae_files_name,encoding='utf-8')
return wl_dataframe,sae_dataframe
@ -144,10 +191,11 @@ class data_collection(openram_test):
meas_delay_ratios = {}
ratio_error = {}
#The full file name contains unrelated portions, separate them into the four that are needed
wl_meas_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in self.file_names if "wl_measures" in file_name][0]
sae_meas_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in self.file_names if "sae_measures" in file_name][0]
wl_model_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in self.file_names if "wl_model" in file_name][0]
sae_model_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in self.file_names if "sae_model" in file_name][0]
file_list = self.file_name_dict.values()
wl_meas_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in file_list if "wl_measures" in file_name][0]
sae_meas_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in file_list if "sae_measures" in file_name][0]
wl_model_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in file_list if "wl_model" in file_name][0]
sae_model_df = [pd.read_csv(file_name,encoding='utf-8') for file_name in file_list if "sae_model" in file_name][0]
#Assume each csv has the same corners (and the same row order), use one of the dfs for corners
proc_pos, volt_pos, temp_pos = wl_meas_df.columns.get_loc('process'), wl_meas_df.columns.get_loc('voltage'), wl_meas_df.columns.get_loc('temp')
@ -238,7 +286,12 @@ class data_collection(openram_test):
for corner in corner_gen:
sram_data = self.get_sram_data(corner)
self.add_sram_data_to_csv(sram_data, word_size, num_words, words_per_row, dc_resized, corner)
#Save file names generated by this run
if not self.dataset_initialized:
self.init_dataset_csv(list(sram_data))
self.add_dataset(word_size, num_words, words_per_row)
self.close_files()
debug.info(1,"Data Generated")
@ -266,8 +319,12 @@ class data_collection(openram_test):
def close_files(self):
"""Closes all files stored in the file dict"""
#Close the files holding data
for key,file in self.csv_files.items():
file.close()
#Write dataframe to the dataset csv
self.datasets_df.to_csv(DATASET_CSV_NAME, index=False)
def corner_combination_generator(self):
processes = OPTS.process_corners
@ -311,19 +368,20 @@ class data_collection(openram_test):
header_dict = self.delay_obj.get_all_signal_names()
self.csv_files = {}
self.csv_writers = {}
self.file_names = []
self.file_name_dict = {}
delay_fanout_list = self.delay_obj.get_num_delay_fanout_list()
fanout_str = '_'.join(str(fanout) for fanout in delay_fanout_list)
delay_stages = self.delay_obj.get_num_delay_stages()
delay_stage_fanout = self.delay_obj.get_num_delay_stage_fanout()
for data_name, header_list in header_dict.items():
file_name = '{}data_{}b_{}word_{}way_dc{}x{}_{}.csv'.format(MODEL_DIR,
file_name = '{}data_{}b_{}word_{}way_dc{}_{}.csv'.format(MODEL_DIR,
word_size,
num_words,
words_per_row,
delay_stages,
delay_stage_fanout,
fanout_str,
data_name)
self.file_names.append(file_name)
self.file_name_dict[data_name] = file_name
self.csv_files[data_name] = open(file_name, 'w')
self.config_fields = ['word_size', 'num_words', 'words_per_row', 'dc_resized', 'process', 'voltage', 'temp']
self.other_data_fields = ['sum']