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Added support for Navi ATT

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Change-Id: If65afd850b1a63fdda6382133c6269c8d17bfb4d


[ROCm/rocprofiler commit: a6a61c5f51]
This commit is contained in:
Giovanni LB
2023-05-02 05:17:47 -03:00
committed by Giovanni Baraldi
parent 1d95e00954
commit 0d25fd5727
2 changed files with 140 additions and 72 deletions
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projects/rocprofiler/plugin/att/att.py
+38 -29
View File
@@ -117,22 +117,20 @@ class Wave(ctypes.Structure):
('timeline_string', ctypes.c_char_p),
('instructions_string', ctypes.c_char_p)]
# Flags :
# IS_NAVI = 0x1
class ReturnInfo(ctypes.Structure):
_fields_ = [('num_waves', ctypes.c_uint64),
('wavedata', POINTER(Wave)),
('num_events', ctypes.c_uint64),
('perfevents', POINTER(PerfEvent)),
('occupancy', POINTER(ctypes.c_uint64)),
('num_occupancy', ctypes.c_uint64)]
('num_occupancy', ctypes.c_uint64),
('flags', ctypes.c_uint64)]
rocprofv2_att_lib = os.getenv('ROCPROFV2_ATT_LIB_PATH')
try: # For build dir
path_to_parser = os.path.abspath(rocprofv2_att_lib)
SO = CDLL(path_to_parser)
except: # For installed dir
path_to_parser = os.path.abspath('/usr/lib/hsa-amd-aqlprofile/librocprofv2_att.so')
SO = CDLL(path_to_parser)
path_to_parser = os.path.abspath(rocprofv2_att_lib)
SO = CDLL(path_to_parser)
SO.AnalyseBinary.restype = ReturnInfo
SO.AnalyseBinary.argtypes = [ctypes.c_char_p, ctypes.c_int, ctypes.c_bool]
@@ -182,18 +180,11 @@ def getWaves(filename, target_cu, verbose):
events = [deepcopy(info.perfevents[k]) for k in range(info.num_events)]
occupancy = [int(info.occupancy[k]) for k in range(int(info.num_occupancy))]
'''occupancy = np.asarray([f for f in occupancy if (f&0xFF) == 3])
print(occupancy.size, occupancy.dtype)
token_time = occupancy >> 16
value = (occupancy >> 8) & 0xFF
plt.plot(token_time, value); plt.show()
quit()'''
for wave in waves:
wave.timeline = deepcopy(wave.timeline_string.decode("utf-8"))
wave.instructions = deepcopy(wave.instructions_string.decode("utf-8"))
return waves, events, occupancy
return waves, events, occupancy, 'navi' if (info.flags & 0x1) else 'vega'
def persist(trace_file, SIMD):
@@ -328,9 +319,6 @@ def draw_wave_metrics(selections, normalize):
delta_step = 8
quad_delta_time = max(delta_step,int(0.5+np.min([get_delta_time(events) for events in EVENTS])))
maxtime = np.max([np.max([e.time for e in events]) for events in EVENTS])/quad_delta_time+1
event_timeline = np.zeros((16, maxtime), dtype=np.int32)
print('Delta:', quad_delta_time)
print('Max_cycles:', maxtime)
if maxtime*delta_step >= COUNTERS_MAX_CAPTURES:
delta_step = 1
@@ -468,7 +456,8 @@ if __name__ == "__main__":
for line in lines:
if 'PERFCOUNTER=' in line:
EVENT_NAMES += [clean(line).split('SQ_')[1].lower()]
if len(EVENT_NAMES) == 0:
EVENT_NAMES = ['SPI', 'Vdata', 'Sdata', 'LDS']
if args.target_cu is None:
args.target_cu = 1
@@ -515,13 +504,14 @@ if __name__ == "__main__":
DBFILES = []
global TIMELINES
global EVENTS
TIMELINES = [np.zeros(int(1E4),dtype=np.int32) for k in range(5)]
TIMELINES = [np.zeros(int(1E4),dtype=np.int16) for k in range(5)]
EVENTS = []
OCCUPANCY = []
analysed_filenames = []
SIMD_list = []
for name in filenames:
SIMD, perfevents, occupancy = getWaves(name, args.target_cu, False)
SIMD, perfevents, occupancy, gfxv = getWaves(name, args.target_cu, False)
if len(SIMD) == 0:
print("Error parsing ", name)
continue
@@ -529,17 +519,36 @@ if __name__ == "__main__":
EVENTS.append(perfevents)
DBFILES.append( persist(name, SIMD) )
OCCUPANCY.append( occupancy )
for wave in SIMD:
SIMD_list.append( SIMD )
min_event_time = 2**62
for df in DBFILES:
if len(df['begin_time']) > 0:
min_event_time = min(min_event_time, np.min(df['begin_time']))
for perf in EVENTS:
for p in perf:
min_event_time = min(min_event_time, p.time)
for occ in OCCUPANCY:
min_event_time = min(min_event_time, np.min(np.array(occ)>>16))
print("Min time:", min_event_time)
for perf in EVENTS:
for p in perf:
p.time -= min_event_time
OCCUPANCY = [[max(min(int((u>>16)-min_event_time)<<16,2**42),0) | (u&0xFFFFF) for u in occ] for occ in OCCUPANCY]
for df in DBFILES:
for T in range(len(df['timeline'])):
timeline = df['timeline'][T]
time_acc = 0
tuples1 = wave.timeline.split('(')
tuples1 = timeline.split('(')
tuples2 = [t.split(')')[0].split(',') for t in tuples1 if t != '']
tuples3 = [(int(t[0]),int(t[1])) for t in tuples2]
tuples3 = [(0,df['begin_time'][T]-min_event_time)]+[(int(t[0]),int(t[1])) for t in tuples2]
for state in tuples3:
if state[1] > 1E7:
if state[1] > 50E6:
print('Warning: Time limit reached for ',state[0], state[1])
break
if time_acc+state[1] > TIMELINES[state[0]].size:
TIMELINES[state[0]] = np.hstack([
TIMELINES[state[0]],
@@ -549,7 +558,7 @@ if __name__ == "__main__":
time_acc += state[1]
if args.genasm and len(args.genasm) > 0:
flight_count = view_trace(args, code, jumps, DBFILES, analysed_filenames, True, None, OCCUPANCY, args.dumpfiles)
flight_count = view_trace(args, code, jumps, DBFILES, analysed_filenames, True, None, OCCUPANCY, args.dumpfiles, min_event_time, gfxv)
with open(args.assembly_code, 'r') as file:
lines = file.readlines()
@@ -561,4 +570,4 @@ if __name__ == "__main__":
for k in keys:
file.write(assembly_code[k]+'\n')
else:
view_trace(args, code, jumps, DBFILES, analysed_filenames, False, GeneratePIC, OCCUPANCY, args.dumpfiles)
view_trace(args, code, jumps, DBFILES, analysed_filenames, False, GeneratePIC, OCCUPANCY, args.dumpfiles, min_event_time, gfxv)