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Merge branch 'dev' of https://github.com/AMDResearch/omniperf into kernel_name_mappings

فهرست منبع
This commit is contained in:
JoseSantosAMD
2023-08-08 14:49:59 -05:00
والد 4e51c122d1 c809346b1b
کامیت 76da2a9ed5
56فایلهای تغییر یافته به همراه1345 افزوده شده و 213 حذف شده
دانلود پرونده وصله دانلود فایل تغییرات diff Expand all files Collapse all files
src/utils/perfagg.py
+164 -76
مشاهده پرونده
@@ -95,13 +95,19 @@ def test_df_column_equality(df):
# joins disparate runs less dumbly than rocprof
def join_prof(workload_dir, join_type, log_file, verbose, out=None):
# Set default output directory if not specified
if out == None:
out = workload_dir + "/pmc_perf.csv"
files = glob.glob(workload_dir + "/" + "pmc_perf_*.csv")
df = None
if type(workload_dir) == str:
if out is None:
out = workload_dir + "/pmc_perf.csv"
files = glob.glob(workload_dir + "/" + "pmc_perf_*.csv")
elif type(workload_dir) == list:
files = workload_dir
else:
print("ERROR: Invalid workload_dir")
sys.exit(1)
df = None
for i, file in enumerate(files):
_df = pd.read_csv(file)
_df = pd.read_csv(file) if type(workload_dir) == str else file
if join_type == "kernel":
key = _df.groupby("KernelName").cumcount()
_df["key"] = _df.KernelName + " - " + key.astype(str)
@@ -127,10 +133,15 @@ def join_prof(workload_dir, join_type, log_file, verbose, out=None):
"wgr": [col for col in df.columns if "wgr" in col],
"lds": [col for col in df.columns if "lds" in col],
"scr": [col for col in df.columns if "scr" in col],
"arch_vgpr": [col for col in df.columns if "arch_vgpr" in col],
"accum_vgpr": [col for col in df.columns if "accum_vgpr" in col],
"spgr": [col for col in df.columns if "sgpr" in col],
}
# Check for vgpr counter in ROCm < 5.3
if "vgpr" in df.columns:
duplicate_cols["vgpr"] = [col for col in df.columns if "vgpr" in col]
# Check for vgpr counter in ROCm >= 5.3
else:
duplicate_cols["arch_vgpr"] = [col for col in df.columns if "arch_vgpr" in col]
duplicate_cols["accum_vgpr"] = [col for col in df.columns if "accum_vgpr" in col]
for key, cols in duplicate_cols.items():
_df = df[cols]
if not test_df_column_equality(_df):
@@ -140,10 +151,12 @@ def join_prof(workload_dir, join_type, log_file, verbose, out=None):
)
)
warnings.warn(msg)
log_file.write(msg + "\n")
if log_file:
log_file.write(msg + "\n")
else:
msg = "Successfully joined {} in pmc_perf.csv".format(key)
log_file.write(msg + "\n")
if log_file:
log_file.write(msg + "\n")
if test_df_column_equality(_df) and verbose:
print(msg)
@@ -173,6 +186,8 @@ def join_prof(workload_dir, join_type, log_file, verbose, out=None):
"fbar",
"sig",
"obj",
# rocscope specific merged counters, keep original
"dispatch_",
]
)
]
@@ -183,7 +198,15 @@ def join_prof(workload_dir, join_type, log_file, verbose, out=None):
[
k
for k in df.keys()
if not any(check in k for check in ["DispatchNs", "CompleteNs"])
if not any(
check in k
for check in [
"DispatchNs",
"CompleteNs",
# rocscope specific timestamp
"HostDuration",
]
)
]
]
#   C) sanity check the name and key
@@ -210,12 +233,14 @@ def join_prof(workload_dir, join_type, log_file, verbose, out=None):
df["EndNs"] = endNs
# finally, join the drop key
df = df.drop(columns=["key"])
# and save to file
df.to_csv(out, index=False)
# and delete old file(s)
if not verbose:
for file in files:
os.remove(file)
# save to file and delete old file(s), skip if we're being called outside of Omniperf
if type(workload_dir) == str:
df.to_csv(out, index=False)
if not verbose:
for file in files:
os.remove(file)
else:
return df
def pmc_perf_split(workload_dir):
@@ -250,7 +275,94 @@ def pmc_perf_split(workload_dir):
os.remove(workload_perfmon_dir + "/pmc_perf.txt")
def perfmon_coalesce(pmc_files_list, workload_dir, soc):
def update_pmc_bucket(
counters, save_file, soc, pmc_list=None, stext=None, workload_perfmon_dir=None
):
# Verify inputs.
# If save_file is True, we're being called internally, from perfmon_coalesce
# Else we're being called externally, from rocomni
detected_external_call = False
if save_file and (stext is None or workload_perfmon_dir is None):
raise ValueError(
"stext and workload_perfmon_dir must be specified if save_file is True"
)
if pmc_list is None:
detected_external_call = True
pmc_list = dict(
[
("SQ", []),
("GRBM", []),
("TCP", []),
("TA", []),
("TD", []),
("TCC", []),
("SPI", []),
("CPC", []),
("CPF", []),
("GDS", []),
("TCC2", {}), # per-channel TCC perfmon
]
)
for ch in range(perfmon_config[soc]["TCC_channels"]):
pmc_list["TCC2"][str(ch)] = []
if "SQ_ACCUM_PREV_HIRES" in counters and not detected_external_call:
# save all level counters separately
nindex = counters.index("SQ_ACCUM_PREV_HIRES")
level_counter = counters[nindex - 1]
if save_file:
# Save to level counter file, file name = level counter name
fd = open(workload_perfmon_dir + "/" + level_counter + ".txt", "w")
fd.write(stext + "\n\n")
fd.write("gpu:\n")
fd.write("range:\n")
fd.write("kernel:\n")
fd.close()
return pmc_list
# save normal pmc counters in matching buckets
for counter in counters:
IP_block = counter.split(sep="_")[0].upper()
# SQC and SQ belong to the IP block, coalesce them
if IP_block == "SQC":
IP_block = "SQ"
if IP_block != "TCC":
# Insert unique pmc counters into its bucket
if counter not in pmc_list[IP_block]:
pmc_list[IP_block].append(counter)
else:
# TCC counters processing
m = re.match(r"[\s\S]+\[(\d+)\]", counter)
if m is None:
# Aggregated TCC counters
if counter not in pmc_list[IP_block]:
pmc_list[IP_block].append(counter)
else:
# TCC channel ID
ch = m.group(1)
# fake IP block for per channel TCC
if str(ch) in pmc_list["TCC2"]:
# append unique counter into the channel
if counter not in pmc_list["TCC2"][str(ch)]:
pmc_list["TCC2"][str(ch)].append(counter)
else:
# initial counter in this channel
pmc_list["TCC2"][str(ch)] = [counter]
if detected_external_call:
# sort the per channel counter, so that same counter in all channels can be aligned
for ch in range(perfmon_config[soc]["TCC_channels"]):
pmc_list["TCC2"][str(ch)].sort()
return pmc_list
def perfmon_coalesce(pmc_files_list, soc, workload_dir):
workload_perfmon_dir = workload_dir + "/perfmon"
# match pattern for pmc counters
@@ -290,54 +402,20 @@ def perfmon_coalesce(pmc_files_list, workload_dir, soc):
# we have found all the counters, store them in buckets
counters = m.group(1).split()
if "SQ_ACCUM_PREV_HIRES" in counters:
# save all level counters separately
nindex = counters.index("SQ_ACCUM_PREV_HIRES")
level_counter = counters[nindex - 1]
# Utilitze helper function once a list of counters has be extracted
save_file = True
pmc_list = update_pmc_bucket(
counters, save_file, soc, pmc_list, stext, workload_perfmon_dir
)
# Save to level counter file, file name = level counter name
fd = open(workload_perfmon_dir + "/" + level_counter + ".txt", "w")
fd.write(stext + "\n\n")
fd.write("gpu:\n")
fd.write("range:\n")
fd.write("kernel:\n")
fd.close()
continue
# save normal pmc counters in matching buckets
for counter in counters:
IP_block = counter.split(sep="_")[0].upper()
# SQC and SQ belong to the IP block, coalesce them
if IP_block == "SQC":
IP_block = "SQ"
if IP_block != "TCC":
# Insert unique pmc counters into its bucket
if counter not in pmc_list[IP_block]:
pmc_list[IP_block].append(counter)
else:
# TCC counters processing
m = re.match(r"[\s\S]+\[(\d+)\]", counter)
if m is None:
# Aggregated TCC counters
if counter not in pmc_list[IP_block]:
pmc_list[IP_block].append(counter)
else:
# TCC channel ID
ch = m.group(1)
# fake IP block for per channel TCC
if str(ch) in pmc_list["TCC2"]:
# append unique counter into the channel
if counter not in pmc_list["TCC2"][str(ch)]:
pmc_list["TCC2"][str(ch)].append(counter)
else:
# initial counter in this channel
pmc_list["TCC2"][str(ch)] = [counter]
# add a timestamp file
fd = open(workload_perfmon_dir + "/timestamps.txt", "w")
fd.write("pmc:\n\n")
fd.write("gpu:\n")
fd.write("range:\n")
fd.write("kernel:\n")
fd.close()
# sort the per channel counter, so that same counter in all channels can be aligned
for ch in range(perfmon_config[soc]["TCC_channels"]):
@@ -346,9 +424,7 @@ def perfmon_coalesce(pmc_files_list, workload_dir, soc):
return pmc_list
def perfmon_emit(pmc_list, workload_dir, soc):
workload_perfmon_dir = workload_dir + "/perfmon"
def perfmon_emit(pmc_list, soc, workload_dir=None):
# Calculate the minimum number of iteration to save the pmc counters
# non-TCC counters
pmc_cnt = [
@@ -370,7 +446,11 @@ def perfmon_emit(pmc_list, workload_dir, soc):
niter = max(math.ceil(max(pmc_cnt)), math.ceil(tcc_cnt) + math.ceil(max(tcc2_cnt)))
# Emit PMC counters into pmc config file
fd = open(workload_perfmon_dir + "/pmc_perf.txt", "w")
if workload_dir:
workload_perfmon_dir = workload_dir + "/perfmon"
fd = open(workload_perfmon_dir + "/pmc_perf.txt", "w")
else:
batches = []
tcc2_index = 0
for iter in range(niter):
@@ -400,12 +480,20 @@ def perfmon_emit(pmc_list, workload_dir, soc):
# TCC aggregated counters
line = line + " " + " ".join(tcc_counters)
fd.write(line + "\n")
if workload_dir:
fd.write(line + "\n")
else:
b = line.split()
b.remove("pmc:")
batches.append(b)
fd.write("\ngpu:\n")
fd.write("range:\n")
fd.write("kernel:\n")
fd.close()
if workload_dir:
fd.write("\ngpu:\n")
fd.write("range:\n")
fd.write("kernel:\n")
fd.close()
else:
return batches
def perfmon_filter(workload_dir, perfmon_dir, args):
@@ -445,8 +533,8 @@ def perfmon_filter(workload_dir, perfmon_dir, args):
pmc_files_list = ref_pmc_files_list
# Coalesce and writeback workload specific perfmon
pmc_list = perfmon_coalesce(pmc_files_list, workload_dir, soc)
perfmon_emit(pmc_list, workload_dir, soc)
pmc_list = perfmon_coalesce(pmc_files_list, soc, workload_dir)
perfmon_emit(pmc_list, soc, workload_dir)
def pmc_filter(workload_dir, perfmon_dir, soc):
@@ -463,5 +551,5 @@ def pmc_filter(workload_dir, perfmon_dir, soc):
pmc_files_list = ref_pmc_files_list
# Coalesce and writeback workload specific perfmon
pmc_list = perfmon_coalesce(pmc_files_list, workload_dir, soc)
perfmon_emit(pmc_list, workload_dir, soc)
pmc_list = perfmon_coalesce(pmc_files_list, soc, workload_dir)
perfmon_emit(pmc_list, soc, workload_dir)