def _block0():
# omp for
for i in omp.prange(8):
time.sleep(random.randrange(3))
print str(omp.get_thread_num()) + ' thread\n',
omp.barrier()
print "done"
def _block0():
print str(omp.get_thread_num()) + ' a\n',
time.sleep(random.randrange(3))
print str(omp.get_thread_num()) + ' b\n',
time.sleep(random.randrange(3))
# omp barrier
omp.barrier()
print str(omp.get_thread_num()) + ' c\n',
def _block3():
# omp for
for i in omp.prange(num_step):
x = (i + 0.5) * step
# omp critical
omp.set_internal_lock(2)
_dict4['ans'] += 4.0 / (1.0 + x * x)
omp.unset_internal_lock(2)
omp.barrier()
def _block0():
# omp for reduction(+:ans)
OMP_REDUCTION_VAR_0 = omp.reduction_init('+')
for i in omp.prange(num_step):
x = (i + 0.5) * step
OMP_REDUCTION_VAR_0 += 4.0 / (1.0 + x * x)
omp.set_internal_lock(0)
_dict1['ans'] = omp.reduction('+', _dict1['ans'], OMP_REDUCTION_VAR_0)
omp.unset_internal_lock(0)
omp.barrier()
def _block0():
# omp for
for n in omp.prange(_dict2['N'] * _dict2['N']):
i = n / _dict2['N']
j = n % _dict2['N']
tmp = 0
for k in range(_dict2['N']):
tmp = tmp + _dict2['a'][i * _dict2['N'] +
k] * _dict2['b'][k * _dict2['N'] + j]
_dict2['res'][n] = tmp
omp.barrier()
def _block0():
if omp.get_thread_num() == 0:
print 'num_threads =', omp.get_num_threads()
#omp for reduction(+:s)
OMP_REDUCTION_VAR_0_0 = omp.reduction_init('+')
for i in omp.prange(_dict1['n']):
OMP_REDUCTION_VAR_0_0 += i
omp.set_internal_lock(0)
_dict1['s'] = omp.reduction('+', _dict1['s'], OMP_REDUCTION_VAR_0_0)
omp.unset_internal_lock(0)
omp.barrier()
def _block0():
# omp sections
for OMP_SECTIONS_ID in omp.prange(2):
# omp section
if OMP_SECTIONS_ID == 0:
print 'section 0 from ' + str(omp.get_thread_num()) + '\n',
# omp section end
# omp section
if OMP_SECTIONS_ID == 1:
print 'section 1 from ' + str(omp.get_thread_num()) + '\n',
# omp section end
# omp sections end
omp.barrier()
def calc_pi_for():
ans = 0
lock = omp.init_lock()
tmp_ans = omp.reduction_init('+')
#omp parallel num_threads(8) private(i,x)
for i in omp.prange(num_step):
x = (i+0.5)*step
ans += 4.0/(1.0 + x*x)
omp.set_internal_lock(0)
tmp_ans = omp.reduction('+', tmp_ans, ans)
omp.unset_internal_lock(0)
omp.barrier()
ans = tmp_ans
#omp parallel end
print ans * step