def main():
parser = argparse.ArgumentParser(
description="Report the weight of a microbenchmark"
)
parser.add_argument("functions_txt")
parser.add_argument("performance_csv")
parser.add_argument("cluster_json")
parser.add_argument("function_name")
parser.add_argument("invocation", type=int)
args = parser.parse_args()
cluster_info = ClusteringInformation.from_file(args.cluster_json)
invocations = load_invocations_from_file(args.performance_csv)
weight = None
with open(args.functions_txt) as file:
lines = file.readlines()[1:]
for line in lines:
_, name, _, _, weight, _, _ = line.split("\t")
weight = float(weight[:-1]) / 100
if name == args.function_name:
break
function = Function(cluster_info, invocations, weight)
print(function.get_weight_of_invocation(args.invocation))
def summary(args):
cluster = ClusteringInformation.from_file(args.cluster_file)
print("Cluster information parsed.")
print("Epsilon parameter: ", cluster.get_epsilon())
print("Invocation count: %d (in %d sets)" %
(cluster.get_invocation_count(), cluster.get_invocation_set_count()))
print("Cluster count: ", cluster.get_cluster_count())
print("Noise invocations: %d (in %d sets)" %
(cluster.get_noise_invocation_count(),
cluster.get_noise_invocation_set_count()))
def invocation(args):
cluster_info = ClusteringInformation.from_file(args.cluster_file)
result = cluster_info.get_cluster_id_for_invocation(args.invocation_id)
if result == None:
print("Invocation %d doesn't exist" % args.invocation_id)
elif result == -1:
print("Invocatoin %d is a noise point" % args.invocation_id)
else:
print("Invocation %d belongs to cluster %d" %
(args.invocation_id, result))
def representative(args):
cluster_info = ClusteringInformation.from_file(args.cluster_file)
if args.noise:
for invocation in cluster_info.get_random_noise_invocations():
print(invocation)
elif args.cluster != None:
print(cluster_info.get_random_invocation_in_cluster(args.cluster))
else:
for index in range(cluster_info.get_cluster_count()):
print(cluster_info.get_random_invocation_in_cluster(index))
for invocation in cluster_info.get_random_noise_invocations():
print(invocation)
def load_function_data(results_path, benchmark):
with open(os.path.join(results_path, "functions.txt")) as file:
lines = file.readlines()[1:]
for line in lines:
_, name, _, _, weight, _, _ = line.split("\t")
weight = float(weight[:-1]) / 100
cluster_info = ClusteringInformation.from_file(
os.path.join(results_path, name + "_cluster.json"))
invocations = load_invocations_from_file(
os.path.join(results_path, name, "benchmark.csv"))
function = Function(cluster_info, invocations, weight)
benchmark.add_function(name, function)
def representative(args):
cluster_info = ClusteringInformation.from_file(args.cluster_file)
if args.noise:
try:
for invocation in cluster_info.get_noise_invocations(
ignore=args.ignore):
print(invocation)
except TypeError:
return
elif args.cluster != None:
print(
cluster_info.get_invocation_in_cluster(args.cluster,
ignore=args.ignore))
else:
for index in range(cluster_info.get_cluster_count()):
print(
cluster_info.get_invocation_in_cluster(index,
ignore=args.ignore))
for invocation in cluster_info.get_noise_invocations(
ignore=args.ignore):
print(invocation)
def summary(args):
cluster = ClusteringInformation.from_file(args.cluster_file)
chop_print("Cluster information parsed.")
if args.cluster is None:
print("Epsilon parameter: %s" % cluster.get_epsilon())
print("Invocation count: %d (in %d sets)" % (
cluster.get_invocation_count(),
cluster.get_invocation_set_count(),
))
print("Cluster count: %d" % cluster.get_cluster_count())
print("Noise invocations: %d (in %d sets)" % (
cluster.get_noise_invocation_count(),
cluster.get_noise_invocation_set_count(),
))
print("Instruction coverage: %.2f %%" %
cluster.get_instruction_coverage())
print("Invocation coverage: %.2f %%" %
cluster.get_invocation_coverage())
return
if not (0 <= args.cluster < cluster.get_cluster_count()):
chop_print("ERROR: Wrong cluster. Valid cluster range [0,%d)" %
cluster.get_cluster_count())
exit(1)
print("Cluster id: %d" % args.cluster)
print("Invocation count: %d " %
cluster.get_invocation_count(cluster=args.cluster))
print("Instruction coverage: %.2f %%" %
cluster.get_instruction_coverage(cluster=args.cluster))
print("Invocation coverage: %.2f %%" %
cluster.get_invocation_coverage(cluster=args.cluster))
print("Instructions: %d" %
cluster.get_extra_cluster_metric(args.cluster, "instructions"))
print("Cycles: %d" %
cluster.get_extra_cluster_metric(args.cluster, "cycles"))
print("IPC: %.2f " % cluster.get_extra_cluster_metric(args.cluster, "ipc"))
def noise(args):
cluster_info = ClusteringInformation.from_file(args.cluster_file)