def find_same_level_regions(region):
# Load graph
graph = load_graph()
if not graph:
logger.error("Can't trace multiple regions: Region call graph not available.\n\
Run cere profile.\n\
Tracing region {0}".format(region))
return
# Find region node id
region_node = get_region_id(region, graph)
#Find roots
roots = [n for n,d in graph.in_degree().items() if d==0]
#Compute for every nodes, the max distance from himself to each root
max_path_len = {}
for root in roots:
for n, d in graph.nodes(data=True):
if n not in max_path_len: max_path_len[n]=0
#Get every paths from the current root to the node
paths = list(nx.all_simple_paths(graph, root, n))
#Keep the max length path
for path in paths:
if len(path)-1 > max_path_len[n]:
max_path_len[n] = len(path)-1
#Keep region which have the same depth than the requested region
for n, p in max_path_len.iteritems():
if p == max_path_len[region_node]:
yield graph.node[n]['_name']
def compute_coverage(self):
#There is two ways of computing coverage
#1) If we have gperftool results:
from common.graph_utils import load_graph
import networkx as nx
graph = load_graph()
if graph:
logger.info("Computing coverage using google perf tool")
for n, d in graph.nodes(data=True):
if d['_name'] == self.region:
self.coverage = float(d['_self_coverage'])
return
#2) Compute the coverage manually
elif os.path.isfile("{0}/app_cycles.csv".format(
var.CERE_PROFILE_PATH)):
logger.info("Computing coverage using rdtsc tool")
with open("{0}/app_cycles.csv".format(
var.CERE_PROFILE_PATH)) as app:
reader = csv.DictReader(app)
for row in reader:
app_cycles = float(row["CPU_CLK_UNHALTED_CORE"])
self.coverage = (self.invivo_cycles / app_cycles) * 100
else:
self.coverage = "NA"
logger.warning(
"Cannot compute coverage for region {0}. Try to run cere profile"
.format(self.region))
def find_same_level_regions(region):
# Load graph
graph = load_graph()
if not graph:
logger.error(
"Can't trace multiple regions: Region call graph not available.\n\
Run cere profile.\n\
Tracing region {0}".format(region))
return
# Find region node id
region_node = get_region_id(region, graph)
#Find roots
roots = [n for n, d in graph.in_degree().items() if d == 0]
#Compute for every nodes, the max distance from himself to each root
max_path_len = {}
for root in roots:
for n, d in graph.nodes(data=True):
if n not in max_path_len: max_path_len[n] = 0
#Get every paths from the current root to the node
paths = list(nx.all_simple_paths(graph, root, n))
#Keep the max length path
for path in paths:
if len(path) - 1 > max_path_len[n]:
max_path_len[n] = len(path) - 1
#Keep region which have the same depth than the requested region
for n, p in max_path_len.iteritems():
if p == max_path_len[region_node]:
yield graph.node[n]['_name']
def compute_coverage(self):
#There is two ways of computing coverage
#1) If we have gperftool results:
from common.graph_utils import load_graph
import networkx as nx
graph = load_graph()
if graph:
logger.info("Computing coverage using google perf tool")
for n, d in graph.nodes(data=True):
if d['_name'] == self.region:
self.coverage = float(d['_self_coverage'])
return
#2) Compute the coverage manually
elif os.path.isfile("{0}/app_cycles.csv".format(var.CERE_PROFILE_PATH)):
logger.info("Computing coverage using rdtsc tool")
with open("{0}/app_cycles.csv".format(var.CERE_PROFILE_PATH)) as app:
reader = csv.DictReader(app)
for row in reader:
app_cycles = float(row["CPU_CLK_UNHALTED_CORE"])
self.coverage = (self.invivo_cycles/app_cycles)*100
else:
self.coverage = "NA"
logger.warning("Cannot compute coverage for region {0}. Try to run cere profile".format(self.region))
