def writeCounterData(SOS, frame, adios_group, fd):
global config
global prog_names
global comm_ranks
global value_names
global threads
global counters
# Get the frame-specific counter data...
start = time.time()
sqlValsToColByRank = "select value_name, coalesce(value,0.0), prog_name, comm_rank from viewCombined where value_name like 'TAU_COUNTER:%' and frame = " + str(
frame) + " order by prog_name, comm_rank, value_name;"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for counter query"
values_array = np.zeros(shape=(len(results), 5), dtype=np.float)
index = 0
for r in results:
value_name = str(r[0])
value = float(r[1])
prog_name = str(r[2])
comm_rank = str(r[3])
if prog_name not in prog_names:
attr_name = "program_name " + str(len(prog_names))
prog_names[prog_name] = len(prog_names)
ad.define_attribute(adios_group, attr_name, "", ad.DATATYPE.string,
prog_name, "")
# may not be necessary...
if comm_rank not in comm_ranks:
comm_ranks[comm_rank] = len(comm_ranks)
# tease apart the counter name.
tokens = value_name.split(":", 2)
thread = tokens[1]
counter = tokens[2]
if thread not in threads:
threads[thread] = len(threads)
if counter not in counters:
attr_name = "counter " + str(len(counters))
counters[counter] = len(counters)
ad.define_attribute(adios_group, attr_name, "", ad.DATATYPE.string,
counter, "")
values_array[index][0] = int(prog_names[prog_name])
values_array[index][1] = int(comm_ranks[comm_rank])
values_array[index][2] = int(threads[thread])
values_array[index][3] = counters[counter]
values_array[index][4] = float(value)
index = index + 1
# now that the data is queried and in arrays, write it out to the file
# initialize the ADIOS data
if config["output_adios"]:
# write the adios
ad.write_int(fd, "program_count", len(prog_names))
ad.write_int(fd, "comm_rank_count", len(comm_ranks))
ad.write_int(fd, "thread_count", len(threads))
ad.write_int(fd, "metric_count", len(metrics))
ad.write_int(fd, "counter_count", len(counters))
ad.write_int(fd, "counter_value_count", len(results))
ad.write(fd, "counter_values", values_array)
return
## Writing
print "\n>>> Writing ... (rank = %d)\n" % rank
config = "config_mpi.xml"
if len(sys.argv) > 1:
config = sys.argv[1]
ad.init(config, comm)
fd = ad.open("temperature", "adios_test_mpi.bp", "w", comm)
NX = 10
groupsize = 4 + 4 + 4 + 8 * 1 * NX
t = np.array(range(NX), dtype=np.float64) + rank*NX
ad.set_group_size(fd, groupsize)
ad.write_int(fd, "NX", NX)
ad.write_int(fd, "rank", rank)
ad.write_int(fd, "size", size)
ad.write(fd, "temperature", t)
ad.close(fd)
ad.finalize()
## Reading
if rank == 0:
print "\n>>> Reading ...\n"
f = ad.file("adios_test_mpi.bp", comm=MPI.COMM_SELF)
f.printself()
v = f.var['temperature']
def generateADIOSFile(SOS, cycleFieldName, simCycle, lastX, lastY, lastZ,
stride, mintime, maxtime):
global previous_attr
global cached_results_dim
global cachedName
global config
global last_time
global last_fp_ops
global last_rss
global adios_mode
# Get the frame-specific data...
# because we are querying different servers, the data has the potential to
# arrive out-of-order (prog_name, comm_rank). So after each query, sort
# the results into a dictionary of dictionaries.
prog_names = {}
# do the memory first - HWM
start = time.time()
sqlValsToColByRank = "select coalesce(value,0.0), prog_name, comm_rank from viewCombined where value_name = '" + str(
config["events"]["counters"][0]) + "' and frame = " + str(
simCycle) + ";"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for frame query"
for r in results:
value = float(r[0])
prog_name = str(r[1])
comm_rank = int(r[2])
if prog_name not in prog_names:
prog_names[prog_name] = {}
if comm_rank not in prog_names[prog_name]:
prog_names[prog_name][comm_rank] = []
prog_names[prog_name][comm_rank].append(value)
# do the memory first - RSS
start = time.time()
current_rss = {}
sqlValsToColByRank = "select coalesce(value,0.0), prog_name, comm_rank from viewCombined where value_name = '" + str(
config["events"]["counters"][1]) + "' and frame = " + str(
simCycle) + ";"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for frame query"
index = -1
for r in results:
index = index + 1
value = float(r[0])
# change the mean value to a total value and save it
current_rss[index] = value * simCycle
# convert the running average to the most recent measurement
if index in last_rss:
value = current_rss[index] - last_rss[index]
prog_name = str(r[1])
comm_rank = int(r[2])
if prog_name not in prog_names:
prog_names[prog_name] = {}
if comm_rank not in prog_names[prog_name]:
prog_names[prog_name][comm_rank] = []
prog_names[prog_name][comm_rank].append(value)
last_rss = current_rss
# do the timer PAPI metric next
start = time.time()
# Make sure we sort by prog_name, comm_rank!
sqlValsToColByRank = "select coalesce(value,0.0), prog_name, comm_rank from viewCombined where value_name = '" + str(
config["events"]["timers"][0]) + "' and frame = " + str(simCycle) + ";"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for frame query"
for r in results:
value = float(r[0])
prog_name = str(r[1])
comm_rank = int(r[2])
if prog_name not in prog_names:
prog_names[prog_name] = {}
if comm_rank not in prog_names[prog_name]:
prog_names[prog_name][comm_rank] = []
prog_names[prog_name][comm_rank].append(value)
# do the timer time metric next
start = time.time()
sqlValsToColByRank = "select coalesce(value,0.0), prog_name, comm_rank from viewCombined where value_name = '" + str(
config["events"]["timers"][1]) + "' and frame = " + str(simCycle) + ";"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for frame query"
for r in results:
value = float(r[0])
prog_name = str(r[1])
comm_rank = int(r[2])
if prog_name not in prog_names:
prog_names[prog_name] = {}
if comm_rank not in prog_names[prog_name]:
prog_names[prog_name][comm_rank] = []
prog_names[prog_name][comm_rank].append(value)
# now that the data is queried and sorted, write it out to the file
# initialize the ADIOS data
groupsize = 0
# How many MPI ranks in each program?
for prog_name in prog_names:
groupsize = groupsize + len(prog_names[prog_name])
program_count = len(prog_names)
adios_process_index = np.array(range(groupsize), dtype=np.uint32)
adios_memdata_hwm = np.array(range(groupsize), dtype=np.float64)
adios_memdata_rss = np.array(range(groupsize), dtype=np.float64)
adios_flops1 = np.array(range(groupsize), dtype=np.float64)
adios_flops2 = np.array(range(groupsize), dtype=np.float64)
adios_program = np.array(range(groupsize), dtype=np.uint32)
adios_program_name = np.array(range(program_count), dtype=np.chararray)
adios_mpi_index = np.array(range(groupsize), dtype=np.uint32)
cyclestr = str(simCycle)
cyclestr = cyclestr.rjust(5, '0')
filename = "performance.metrics." + cyclestr + ".txt"
# regular text file
if config["output_text"]:
flops_out = open(config["outputdir"] + "/" + filename, 'w')
flops_out.write(
"Process Index, Memory HWM, Memory RSS, Total FLOPS, Latest FLOPS, Program Name, Program Index, MPI Rank\n"
)
s1 = config["events"]["timer_scaling"][0]
s2 = config["events"]["timer_scaling"][1]
index = -1
prog_index = -1
current_time = {}
current_fp_ops = {}
for prog_name in prog_names:
prog_index = prog_index + 1
adios_program_name[prog_index] = prog_name
for comm_rank in prog_names[prog_name]:
index = index + 1
print prog_name, comm_rank, index, current_fp_ops, prog_names
current_fp_ops[index] = prog_names[prog_name][comm_rank][2] * s1
current_time[index] = prog_names[prog_name][comm_rank][3] * s2
flops_to_date = current_fp_ops[index] / current_time[index]
if len(last_fp_ops) > 0:
tmp = (current_fp_ops[index] - last_fp_ops[index])
tmp2 = (current_time[index] - last_time[index])
if tmp2 > 0.0:
# compute flops from lastest timestep
flops_in_last_timestep = tmp / tmp2
else:
if last_time[index] > 0.0:
# compute flops from previous timestep
flops_in_last_timestep = last_fp_ops[
index] / last_time[index]
else:
# something weird is happening...
flops_in_last_timestep = 0.0
else:
# compute flops from first timestep
flops_in_last_timestep = flops_to_date
if config["output_text"]:
# write the sorted data to the file
flops_out.write(str(index) + ", ")
flops_out.write(
str(prog_names[prog_name][comm_rank][0]) + ", ")
flops_out.write(
str(prog_names[prog_name][comm_rank][1]) + ", ")
flops_out.write(str(flops_to_date) + ", ")
flops_out.write(str(flops_in_last_timestep) + ", ")
flops_out.write(prog_name + ", ")
flops_out.write(str(prog_index) + ", ")
flops_out.write(str(comm_rank) + "\n")
if config["output_adios"]:
adios_process_index[index] = index
adios_memdata_hwm[index] = prog_names[prog_name][comm_rank][0]
adios_memdata_rss[index] = prog_names[prog_name][comm_rank][1]
adios_flops1[index] = flops_to_date
adios_flops2[index] = flops_in_last_timestep
adios_program[index] = prog_index
adios_mpi_index[index] = comm_rank
if config["output_text"]:
flops_out.close()
stream_file = "performance.metrics.txt"
stream_out = open(config["outputdir"] + "/" + stream_file, 'w')
stream_out.write(filename + "\n")
stream_out.close()
last_time = current_time
last_fp_ops = current_fp_ops
if config["output_adios"]:
# write the adios
fd = ad.open("TAU_metrics", "tau-metrics.bp", adios_mode)
ad.write_int(fd, "process_count", groupsize)
ad.write_int(fd, "program_count", program_count)
ad.write(fd, "process_index", adios_process_index)
ad.write(fd, "memory_HWM", adios_memdata_hwm)
ad.write(fd, "memory_RSS", adios_memdata_rss)
ad.write(fd, "total_FLOPS", adios_flops1)
ad.write(fd, "latest_FLOPS", adios_flops2)
#ad.write(fd, "program_name", adios_program_name)
ad.write(fd, "program_index", adios_program)
ad.write(fd, "MPI_rank", adios_mpi_index)
ad.close(fd)
#fd.close()
# future iterations are appending, not writing
adios_mode = "a"
return filename
def writeTimerData(SOS, frame, adios_group, fd):
global config
global prog_names
global comm_ranks
global value_names
global threads
global groups
global timers
global event_types
global validation
# Get the frame-specific timer data...
start = time.time()
#sqlValsToColByRank = "select prog_name, comm_rank, value, value_name from viewCombined where (value_name like 'TAU_EVENT_ENTRY%' or value_name like 'TAU_EVENT_EXIT%') and frame = " + str(frame) + " order by value;"
#results, col_names = queryAllAggregators(sqlValsToColByRank)
pub_filter = ""
val_filter = "TAU_EVENT"
frame_start = frame
frame_depth = 1
results, col_names = queryAllAggregatorsCache(pub_filter, val_filter,
frame_start, frame_depth)
end = time.time()
print((end - start), "seconds for event query")
timer_values_array = np.zeros(shape=(len(results), 6), dtype=np.uint64)
counter_values_array = np.zeros(shape=(len(results), 6), dtype=np.uint64)
comm_values_array = np.zeros(shape=(len(results), 8), dtype=np.uint64)
timer_index = 0
counter_index = 0
comm_index = 0
prog_name_index = column_map["prog_name"]
comm_rank_index = column_map["comm_rank"]
value_name_index = column_map["val_name"]
value_index = column_map["val"]
frame_index = column_map["frame"]
time_index = column_map["time_pack"]
results = sorted(results, key=itemgetter(value_index))
total_valid = len(results)
for r in results:
prog_name = str(r[prog_name_index])
comm_rank = str(r[comm_rank_index])
value = int(r[value_index])
value_name = str(r[value_name_index])
row_frame = str(r[frame_index])
#print row_frame, prog_name, comm_rank, value_name
if int(row_frame) != frame:
total_valid = total_valid - 1
continue
if prog_name not in validation:
validation[prog_name] = {}
if comm_rank not in validation[prog_name]:
validation[prog_name][comm_rank] = {}
if "TAU_EVENT_ENTRY" in value_name or "TAU_EVENT_EXIT" in value_name:
if prog_name not in prog_names:
attr_name = "program_name " + str(len(prog_names))
prog_names[prog_name] = len(prog_names)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, prog_name, "")
# may not be necessary...
if comm_rank not in comm_ranks:
comm_ranks[comm_rank] = len(comm_ranks)
# tease apart the event name
tokens = value_name.split(":", 2)
event_type = tokens[0].replace("TAU_EVENT_", "")
if event_type not in event_types:
attr_name = "event_type " + str(len(event_types))
event_types[event_type] = len(event_types)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, event_type, "")
thread = int(tokens[1])
if thread not in validation[prog_name][comm_rank]:
validation[prog_name][comm_rank][thread] = []
timer = tokens[2]
if thread not in threads:
threads[thread] = len(threads)
if timer not in timers:
attr_name = "timer " + str(len(timers))
timers[timer] = len(timers)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, timer, "")
if "MPI_Send" in value_name:
print(value_name, thread)
if "MPI_Recv" in value_name:
print(value_name, thread)
timer_values_array[timer_index][0] = int(prog_names[prog_name])
timer_values_array[timer_index][1] = int(comm_ranks[comm_rank])
timer_values_array[timer_index][2] = int(thread)
timer_values_array[timer_index][3] = int(event_types[event_type])
timer_values_array[timer_index][4] = int(timers[timer])
timer_values_array[timer_index][5] = int(value)
timer_index = timer_index + 1
if "TAU_EVENT_ENTRY" in value_name:
validation[prog_name][comm_rank][thread].append(timer)
else:
if len(validation[prog_name][comm_rank][thread]) == 0:
print("VALIDATION ERROR! empty stack", prog_name,
comm_rank, thread, timer)
#sys.exit()
else:
current_timer = validation[prog_name][comm_rank][
thread].pop()
if current_timer != timer:
print("VALIDATION ERROR!", value,
prog_names[prog_name], comm_rank, thread,
timers[timer], "!= current: ",
timers[current_timer])
elif "TAU_EVENT_COUNTER" in value_name:
# convert the timestamp from seconds to usec
timestamp = float(r[time_index]) * 1000000
if prog_name not in prog_names:
attr_name = "program_name " + str(len(prog_names))
prog_names[prog_name] = len(prog_names)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, prog_name, "")
# may not be necessary...
if comm_rank not in comm_ranks:
comm_ranks[comm_rank] = len(comm_ranks)
# tease apart the event name
tokens = value_name.split(":", 2)
thread = tokens[1]
counter = tokens[2]
if thread not in threads:
threads[thread] = len(threads)
if counter not in counters:
attr_name = "counter " + str(len(counters))
counters[counter] = len(counters)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, counter, "")
counter_values_array[counter_index][0] = int(prog_names[prog_name])
counter_values_array[counter_index][1] = int(comm_ranks[comm_rank])
counter_values_array[counter_index][2] = int(thread)
counter_values_array[counter_index][3] = int(counters[counter])
counter_values_array[counter_index][4] = int(value)
counter_values_array[counter_index][5] = int(timestamp)
counter_index = counter_index + 1
elif "TAU_EVENT_SEND" in value_name or "TAU_EVENT_RECV" in value_name:
if prog_name not in prog_names:
attr_name = "program_name " + str(len(prog_names))
prog_names[prog_name] = len(prog_names)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, prog_name, "")
# may not be necessary...
if comm_rank not in comm_ranks:
comm_ranks[comm_rank] = len(comm_ranks)
# tease apart the event name
tokens = value_name.split(":", 2)
event_type = tokens[0].replace("TAU_EVENT_", "")
if event_type not in event_types:
attr_name = "event_type " + str(len(event_types))
event_types[event_type] = len(event_types)
ad.define_attribute(adios_group, attr_name, "",
ad.DATATYPE.string, event_type, "")
tokens = value_name.split(":", 4)
thread = tokens[1]
tag = tokens[2]
partner = tokens[3]
num_bytes = tokens[4]
if thread not in threads:
threads[thread] = len(threads)
comm_values_array[comm_index][0] = int(prog_names[prog_name])
comm_values_array[comm_index][1] = int(comm_ranks[comm_rank])
comm_values_array[comm_index][2] = int(thread)
comm_values_array[comm_index][3] = int(event_types[event_type])
comm_values_array[comm_index][4] = int(tag)
comm_values_array[comm_index][5] = int(partner)
comm_values_array[comm_index][6] = int(num_bytes)
comm_values_array[comm_index][7] = int(value)
comm_index = comm_index + 1
else:
print("ERROR! unknown event:", prog_name, comm_rank, value_name)
# now that the data is queried and in arrays, write it out to the file
# initialize the ADIOS data
if config["output_adios"] and (timer_index > 0 or counter_index > 0
or comm_index > 0):
#if config["output_adios"]:
# write the adios
ad.write_int(fd, "program_count", len(prog_names))
ad.write_int(fd, "comm_rank_count", len(comm_ranks))
ad.write_int(fd, "thread_count", len(threads))
ad.write_int(fd, "timer_count", len(timers))
ad.write_int(fd, "event_type_count", len(event_types))
ad.write_int(fd, "timer_event_count", timer_index)
ad.write_int(fd, "counter_count", len(counters))
ad.write_int(fd, "counter_event_count", counter_index)
ad.write_int(fd, "comm_count", comm_index)
np.resize(timer_values_array, (timer_index, 6))
np.resize(counter_values_array, (counter_index, 6))
np.resize(comm_values_array, (comm_index, 8))
ad.write(fd, "event_timestamps", timer_values_array)
ad.write(fd, "counter_values", counter_values_array)
ad.write(fd, "comm_timestamps", comm_values_array)
return total_valid
## Writing
print "\n>>> Writing ... (rank = %d)\n" % rank
config = "config_mpi.xml"
if len(sys.argv) > 1:
config = sys.argv[1]
ad.init(config, comm)
fd = ad.open("temperature", "adios_test_mpi.bp", "w", comm)
NX = 10
groupsize = 4 + 4 + 4 + 8 * 1 * NX
t = np.array(range(NX), dtype=np.float64) + rank*NX
ad.set_group_size(fd, groupsize)
ad.write_int(fd, "NX", NX)
ad.write_int(fd, "rank", rank)
ad.write_int(fd, "size", size)
ad.write(fd, "temperature", t)
ad.close(fd)
ad.finalize()
## Reading
if rank == 0:
print "\n>>> Reading ...\n"
f = ad.file("adios_test_mpi.bp", comm=MPI.COMM_SELF)
f.printself()
v = f.vars['temperature']
ad.allocate_buffer(ad.BUFFER_ALLOC_WHEN.NOW, 10)
ad.init_noxml(MPI.COMM_WORLD)
g = ad.declare_group("temperature", "", 1)
ad.define_var(g, "NX", "", ad.DATATYPE.integer, "", "", "")
ad.define_var(g, "size", "", ad.DATATYPE.integer, "", "", "")
ad.define_var(g, "temperature", "", ad.DATATYPE.double, "size,NX", "size,NX",
"0,0")
msg = str(datetime.datetime.now())
ad.define_attribute(g, "datetime", "", ad.DATATYPE.string, msg, "")
print ">>> Method:", method, init
ad.select_method(g, method, init, "")
## Writing
for i in range(5):
print ">>> step:", i
fd = ad.open("temperature", "temp.bp", "a")
NX = 10
size = 2
groupsize = 4 + 4 + 8 * size * NX
t = np.array(range(NX * size), dtype=np.float64) + 100 * i
tt = t.reshape((size, NX))
ad.set_group_size(fd, groupsize)
ad.write_int(fd, "NX", NX)
ad.write_int(fd, "size", size)
ad.write(fd, "temperature", tt)
ad.close(fd)
ad.finalize()
print ">>> Done."
def writeCommData(SOS, frame, adios_group, fd):
global config
global prog_names
global comm_ranks
global value_names
global threads
global groups
global timers
global event_types
# Get the frame-specific timer data...
start = time.time()
sqlValsToColByRank = "select prog_name, comm_rank, value, value_name from viewCombined where (value_name like 'TAU_EVENT_SEND%' or value_name like 'TAU_EVENT_RECV%') and frame = " + str(
frame) + " order by value;"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for communication query"
values_array = np.zeros(shape=(len(results), 8), dtype=np.uint64)
index = 0
for r in results:
prog_name = str(r[0])
comm_rank = str(r[1])
value = long(r[2])
value_name = str(r[3])
if prog_name not in prog_names:
attr_name = "program_name " + str(len(prog_names))
prog_names[prog_name] = len(prog_names)
ad.define_attribute(adios_group, attr_name, "", ad.DATATYPE.string,
prog_name, "")
# may not be necessary...
if comm_rank not in comm_ranks:
comm_ranks[comm_rank] = len(comm_ranks)
# tease apart the event name
tokens = value_name.split(":", 2)
event_type = tokens[0].replace("TAU_EVENT_", "")
if event_type not in event_types:
attr_name = "event_type " + str(len(event_types))
event_types[event_type] = len(event_types)
ad.define_attribute(adios_group, attr_name, "", ad.DATATYPE.string,
event_type, "")
tokens = value_name.split(":", 4)
thread = tokens[1]
tag = tokens[2]
partner = tokens[3]
num_bytes = tokens[4]
if thread not in threads:
threads[thread] = len(threads)
values_array[index][0] = long(prog_names[prog_name])
values_array[index][1] = long(comm_ranks[comm_rank])
values_array[index][2] = long(threads[thread])
values_array[index][3] = long(event_types[event_type])
values_array[index][4] = long(tag)
values_array[index][5] = long(partner)
values_array[index][6] = long(num_bytes)
values_array[index][7] = long(value)
index = index + 1
# now that the data is queried and in arrays, write it out to the file
# initialize the ADIOS data
if config["output_adios"]:
# write the adios
ad.write_int(fd, "program_count", len(prog_names))
ad.write_int(fd, "comm_rank_count", len(comm_ranks))
ad.write_int(fd, "thread_count", len(threads))
ad.write_int(fd, "comm_count", len(results))
if len(results) > 0:
ad.write(fd, "comm_timestamps", values_array)
return
def writeCounterData(SOS, frame, adios_group, fd):
global config
global prog_names
global comm_ranks
global value_names
global threads
global counters
# Get the frame-specific counter data...
start = time.time()
sqlValsToColByRank = "select prog_name, comm_rank, value, value_name, time_pack from viewCombined where (value_name like 'TAU_EVENT_COUNTER%') and frame = " + str(
frame) + " order by time_pack;"
results, col_names = queryAllAggregators(sqlValsToColByRank)
end = time.time()
print(end - start), "seconds for event query"
values_array = np.zeros(shape=(len(results), 6), dtype=np.uint64)
index = 0
for r in results:
prog_name = str(r[0])
comm_rank = str(r[1])
value = long(r[2])
value_name = str(r[3])
# convert the timestamp from seconds to usec
timestamp = float(r[4]) * 1000000
if prog_name not in prog_names:
attr_name = "program_name " + str(len(prog_names))
prog_names[prog_name] = len(prog_names)
ad.define_attribute(adios_group, attr_name, "", ad.DATATYPE.string,
prog_name, "")
# may not be necessary...
if comm_rank not in comm_ranks:
comm_ranks[comm_rank] = len(comm_ranks)
# tease apart the event name
tokens = value_name.split(":", 2)
thread = tokens[1]
counter = tokens[2]
if thread not in threads:
threads[thread] = len(threads)
if counter not in counters:
attr_name = "counter " + str(len(counters))
counters[counter] = len(counters)
ad.define_attribute(adios_group, attr_name, "", ad.DATATYPE.string,
counter, "")
values_array[index][0] = long(prog_names[prog_name])
values_array[index][1] = long(comm_ranks[comm_rank])
values_array[index][2] = long(threads[thread])
values_array[index][3] = long(counters[counter])
values_array[index][4] = long(value)
values_array[index][5] = long(timestamp)
index = index + 1
# now that the data is queried and in arrays, write it out to the file
# initialize the ADIOS data
if config["output_adios"]:
# write the adios
# these get written when the comm data is written
# ad.write_int(fd, "program_count", len(prog_names))
# ad.write_int(fd, "comm_rank_count", len(comm_ranks))
# ad.write_int(fd, "thread_count", len(threads))
ad.write_int(fd, "counter_count", len(counters))
ad.write_int(fd, "counter_event_count", len(results))
if len(results) > 0:
ad.write(fd, "counter_values", values_array)
return
## Init
ad.allocate_buffer (ad.BUFFER_ALLOC_WHEN.NOW, 10);
ad.init_noxml(MPI.COMM_WORLD)
g = ad.declare_group("temperature", "", 1)
ad.define_var(g, "NX", "", ad.DATATYPE.integer, "", "", "")
ad.define_var(g, "size", "", ad.DATATYPE.integer, "", "", "")
ad.define_var(g, "temperature", "", ad.DATATYPE.double, "size,NX", "size,NX", "0,0")
msg = str(datetime.datetime.now())
ad.define_attribute(g, "datetime", "", ad.DATATYPE.string, msg, "")
print ">>> Method:", method, init
ad.select_method(g, method, init, "")
## Writing
for i in range(5):
print ">>> step:", i
fd = ad.open("temperature", "temp.bp", "a")
NX = 10
size = 2
groupsize = 4 + 4 + 8 * size * NX
t = np.array(range(NX*size), dtype=np.float64) + 100*i
tt = t.reshape((size, NX))
ad.set_group_size(fd, groupsize)
ad.write_int(fd, "NX", NX)
ad.write_int(fd, "size", size)
ad.write(fd, "temperature", tt)
ad.close(fd)
ad.finalize()
print ">>> Done."