_N_HIST = 2
bp = BranchPredictorTournament(sat_cnt_bits=_SAT_CNT_BITS, bht_addr_bits=_BHT_ADDR_BITS, n_hist=_N_HIST)
# loop over all trace lines
for address, taken in tr.read():
# predict branch
prediction = bp.predict(address)
# check if prediction was correct
correct = prediction == taken
# update internal predictor state
bp.update(address, correct)
# parameter grid search
if args.gridsearch:
# instantiate evaluator
ev = Evaluator(branch_predictor=BranchPredictorTournament, num_processes=4)
# add all evaluation corners
for trace in ["short_mobile_1", "long_mobile_1", "short_server_1", "long_server_1"]:
for sat_bits in [1, 2, 3, 4, 5]:
for addr_bits in [3, 6, 9, 12, 15]:
ev.submit(trace, sat_bits, addr_bits)
# wait for all tasks to finish
ev.finalize()
# write result to file
ev.write_result("gridsearch_bp_tournament.csv")
# print result
ev.print_result()
tr = TraceReader("../traces/dummy.trace")
# instantiate branch predictor
bp = BranchPredictorAlwaysTaken()
# loop over all trace lines
for address, taken in tr.read():
# predict branch
prediction = bp.predict(address)
# check if prediction was correct
correct = prediction == taken
# update internal predictor state
bp.update(address, correct)
# parameter grid search
if args.gridsearch:
# instantiate evaluator
ev = Evaluator(branch_predictor=BranchPredictorAlwaysTaken, num_processes=4)
# add all evaluation corners
for trace in ["short_mobile_1", "long_mobile_1", "short_server_1", "long_server_1"]:
ev.submit(trace)
# wait for all tasks to finish
ev.finalize()
# write result to file
ev.write_result("gridsearch_bp_always_taken.csv")
# print result
ev.print_result()
n_hist=_N_HIST)
# loop over all trace lines
for address, taken in tr.read():
# predict branch
prediction = bp.predict(address)
# check if prediction was correct
correct = prediction == taken
# update internal predictor state
bp.update(address, correct)
# parameter grid search
if args.gridsearch:
# instantiate evaluator
ev = Evaluator(branch_predictor=BranchPredictorGselect,
num_processes=4)
# add all evaluation corners
for trace in [
"short_mobile_1", "long_mobile_1", "short_server_1",
"long_server_1"
]:
for sat_bits in [1, 2, 3, 4, 5]:
for addr_bits in [3, 6, 9, 12, 15]:
for n_hist in [3, 6]:
ev.submit(trace, sat_bits, addr_bits, n_hist)
# wait for all tasks to finish
ev.finalize()
# write result to file
ev.write_result("gridsearch_bp_gselect.csv")
n_hist=_N_HIST)
# loop over all trace lines
for address, taken in tr.read():
# predict branch
prediction = bp.predict(address)
# check if prediction was correct
correct = prediction == taken
# update internal predictor state
bp.update(address, correct)
# parameter grid search
if args.gridsearch:
# instantiate evaluator
ev = Evaluator(branch_predictor=BranchPredictorTwoLevelLocal,
num_processes=4)
# add all evaluation corners
for trace in [
"short_mobile_1", "long_mobile_1", "short_server_1",
"long_server_1"
]:
for sat_bits in [1, 2, 3, 4, 5]:
for addr_bits in [3, 6, 9, 12, 15]:
ev.submit(trace, sat_bits, addr_bits)
# wait for all tasks to finish
ev.finalize()
# write result to file
ev.write_result("gridsearch_bp_two_level_local.csv")
# print result
n_hist=_N_HIST)
# loop over all trace lines
for address, taken in tr.read():
# predict branch
prediction = bp.predict(address)
# check if prediction was correct
correct = prediction == taken
# update internal predictor state
bp.update(address, correct)
# parameter grid search
if args.gridsearch:
# instantiate evaluator
ev = Evaluator(branch_predictor=BranchPredictorPerceptron,
num_processes=4)
# add all evaluation corners
for trace in [
"short_mobile_1", "long_mobile_1", "short_server_1",
"long_server_1"
]:
for sat_bits in [1, 2, 3, 4, 5]:
for addr_bits in [3, 6, 9, 12, 15]:
ev.submit(trace, sat_bits, addr_bits)
# wait for all tasks to finish
ev.finalize()
# write result to file
ev.write_result("gridsearch_bp_perceptron.csv")
# print result