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#!/usr/bin/env python3
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"""
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Run a regression test on various srams
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"""
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import unittest
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from testutils import header,openram_test
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import sys,os
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sys.path.append(os.path.join(sys.path[0],".."))
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import globals
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from globals import OPTS
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import debug
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import csv
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from sram import sram
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from sram_config import sram_config
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MODEL_DIR = "model_data/"
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class data_collection(openram_test):
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def runTest(self):
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self.init_data_gen()
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#Run on one size to initialize CSV writing (csv names come from return value). Strange, but it is okay for now.
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sram_data = self.get_sram_data(1,16,1)
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self.initialize_csv_file(sram_data)
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self.add_sram_data_to_csv(sram_data, 1, 16, 1)
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#Run openRAM for several size configurations
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#word_size_list, num_word_list, words_per_row_list = self.get_sram_configs()
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word_size_list, num_word_list, words_per_row_list = [4], [16], [1] #for quick testing.
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for word_size in word_size_list:
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for num_word in num_word_list:
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for words_per_row in words_per_row_list:
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#Unfortunately, init needs to be called everytime
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self.init_data_gen()
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sram_data = self.get_sram_data(word_size, num_word, words_per_row)
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self.add_sram_data_to_csv(sram_data, word_size, num_word, words_per_row)
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self.close_files()
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debug.info(1,"Data Generated")
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globals.end_openram()
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def init_data_gen(self):
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"""Initialization for the data test to run"""
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globals.init_openram("config_20_{0}".format(OPTS.tech_name))
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OPTS.spice_name="hspice" #Much faster than ngspice.
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OPTS.trim_netlist = False
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OPTS.netlist_only = True
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OPTS.analytical_delay = False
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# This is a hack to reload the characterizer __init__ with the spice version
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from importlib import reload
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import characterizer
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reload(characterizer)
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def close_files(self):
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"""Closes all files stored in the file dict"""
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for key,file in self.csv_files.items():
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file.close()
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def get_sram_configs(self):
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"""Generate lists of wordsizes, number of words, and column mux size (words per row) to be tested."""
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min_word_size = 1
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max_word_size = 16
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min_num_words_log2 = 4
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max_num_words_log2 = 8
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word_sizes = [i for i in range(min_word_size,max_word_size+1)]
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num_words = [2**i for i in range(min_num_words_log2,max_num_words_log2+1)]
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words_per_row = [1]
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return word_sizes, num_words, words_per_row
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def add_sram_data_to_csv(self, sram_data, word_size, num_words, words_per_row):
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"""Writes data to its respective CSV file. There is a CSV for each measurement target (wordline, sense amp enable, and models)"""
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sram_specs = [word_size,num_words,words_per_row]
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for data_name, data_values in sram_data.items():
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self.csv_writers[data_name].writerow(sram_specs+sram_data[data_name])
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debug.info(2,"Data Added to CSV file.")
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def initialize_csv_file(self, sram_data):
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"""Opens a CSV file and writer for every data set being written (wl/sae measurements and model values)"""
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#CSV File writing
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header_dict = self.delay_obj.get_all_signal_names()
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self.csv_files = {}
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self.csv_writers = {}
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for data_name, header_list in header_dict.items():
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self.csv_files[data_name] = open('{}data_{}.csv'.format(MODEL_DIR,data_name), 'w')
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fields = ('word_size', 'num_words', 'words_per_row', *header_list)
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self.csv_writers[data_name] = csv.writer(self.csv_files[data_name], lineterminator = '\n')
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self.csv_writers[data_name].writerow(fields)
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def get_sram_data(self, word_size, num_words, words_per_row):
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"""Generates the SRAM based on input configuration and returns the data."""
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from characterizer import model_check
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c = sram_config(word_size=word_size,
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num_words=num_words,
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num_banks=1)
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#minimum 16 rows. Most sizes below 16*16 will try to automatically use less rows unless enforced.
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#if word_size*num_words < 256:
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c.words_per_row=words_per_row #Force no column mux until incorporated into analytical delay.
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debug.info(1, "Getting data for {} bit, {} words SRAM with 1 bank".format(word_size, num_words))
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s = sram(c, name="sram_{}ws_{}words".format(word_size, num_words))
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tempspice = OPTS.openram_temp + "temp.sp"
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s.sp_write(tempspice)
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corner = (OPTS.process_corners[0], OPTS.supply_voltages[0], OPTS.temperatures[0])
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self.delay_obj = model_check(s.s, tempspice, corner)
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import tech
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#Only 1 at a time
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probe_address = "1" * s.s.addr_size
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probe_data = s.s.word_size - 1
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loads = [tech.spice["msflop_in_cap"]*4]
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slews = [tech.spice["rise_time"]*2]
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sram_data = self.delay_obj.analyze(probe_address,probe_data,slews,loads)
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return sram_data
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def remove_lists_from_dict(self, dict):
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"""Check all the values in the dict and replaces the list items with its first value."""
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#This is useful because the tests performed here only generate 1 value but a list
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#with 1 item makes writing it to a csv later harder.
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for key in dict.keys():
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if type(dict[key]) is list:
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if len(dict[key]) > 0:
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dict[key] = dict[key][0]
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else:
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del dict[key]
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# instantiate a copdsay of the class to actually run the test
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if __name__ == "__main__":
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(OPTS, args) = globals.parse_args()
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del sys.argv[1:]
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header(__file__, OPTS.tech_name)
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unittest.main()
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Hunter Nichols