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#!/usr/bin/env python3
import os, io, argparse, datetime
#import numpy as np
import sqlalchemy
from sqlalchemy.types import NVARCHAR, Float, Integer
from sqlalchemy import text
import pymysql
import pandas as pd
from sshtunnel import SSHTunnelForwarder
def print_to_string(*args, **kwargs):
output = io.StringIO()
print(*args, file=output, **kwargs)
contents = output.getvalue()
output.close()
return contents
def parse_args():
parser = argparse.ArgumentParser(description='Parse results from tf benchmark runs')
parser.add_argument('filename', type=str, help='Log file to prase or directory containing log files')
args = parser.parse_args()
files = []
if os.path.isdir(args.filename):
all_files = os.listdir(args.filename)
for name in all_files:
if not 'log' in name:
continue
files.append(os.path.join(args.filename, name))
else:
files = [args.filename]
args.files = files
return args
def get_log_params(logfile):
print("logfile=",logfile)
branch_name=' '
node_id=' '
gpu_arch=' '
hip_vers=' '
compute_units=0
environment=' '
rocm_vers=' '
for line in open(logfile):
if 'Branch name' in line:
lst=line.split()
branch_name=lst[2]
if 'On branch' in line:
lst=line.split()
branch_name=lst[2]
if 'Node name' in line:
lst=line.split()
node_id=lst[2]
if 'GPU_arch' in line:
lst=line.split()
gpu_arch=lst[2]
if 'HIP version' in line:
lst=line.split()
hip_vers=lst[2]
if 'Compute Unit' in line:
lst=line.split()
compute_units=lst[2]
if 'Environment type' in line:
lst=line.split()
environment=lst[2]
if 'InstalledDir' in line:
lst=line.split()
rocm_vers=lst[1][lst[1].find('/opt/rocm-')+len('/opt/rocm-'):lst[1].rfind('/llvm/bin')]
return branch_name, node_id, gpu_arch, compute_units, rocm_vers, hip_vers, environment
def parse_logfile(logfile):
glue=''
res=[]
tests=[]
kernels=[]
tflops=[]
dtype=[]
alayout=[]
blayout=[]
M=[]
N=[]
K=[]
StrideA=[]
StrideB=[]
StrideC=[]
if 'perf_gemm' in logfile and 'gemm_bilinear' not in logfile:
for line in open(logfile):
if 'Best Perf' in line:
lst=line.split()
if len(lst)>=37: #the line is complete
tests.append(glue.join(lst[5:30]))
kernels.append(glue.join(lst[37:]))
tflops.append(lst[33])
dtype.append(lst[5])
alayout.append(lst[8])
blayout.append(lst[11])
M.append(lst[14])
N.append(lst[17])
K.append(lst[20])
StrideA.append(lst[23])
StrideB.append(lst[26])
StrideC.append(lst[29])
elif len(lst)<37 and len(lst)>=33: #the tflops are available
tests.append(glue.join(lst[5:30]))
kernels.append("N/A")
tflops.append(lst[33])
dtype.append(lst[5])
alayout.append(lst[8])
blayout.append(lst[11])
M.append(lst[14])
N.append(lst[17])
K.append(lst[20])
StrideA.append(lst[23])
StrideB.append(lst[26])
StrideC.append(lst[29])
print("warning: incomplete line:",lst)
elif len(lst)<33: #even the tflops are not available
print("Error in ckProfiler output!")
print("warning: incomplete line=",lst)
#sort results
#sorted_tests = sorted(tests)
res = [x for _,x in sorted(zip(tests,tflops))]
#sorted_kernels = [x for _,x in sorted(zip(tests,kernels))]
test_list=list(range(1,len(tests)+1))
#parse conv_fwd and conv_bwd performance tests:
elif 'conv_fwd' in logfile or 'conv_bwd' in logfile:
for line in open(logfile):
if 'tflops:' in line:
lst=line.split()
res.append(lst[1])
#parse all other performance tests:
elif 'resnet50' in logfile or 'batched_gemm' in logfile or 'grouped_gemm' in logfile or 'gemm_bilinear' in logfile or 'reduction' in logfile:
for line in open(logfile):
if 'Best Perf' in line:
lst=line.split()
res.append(lst[4])
elif 'onnx_gemm' in logfile:
for line in open(logfile):
if 'Best Perf' in line:
lst=line.split()
res.append(lst[33])
elif 'splitK_gemm' in logfile or 'mixed_gemm' in logfile:
for line in open(logfile):
if 'Best Perf' in line:
lst=line.split()
res.append(lst[36])
elif 'perf_fmha' in logfile:
for line in open(logfile):
if 'TFlops' in line:
lst=line.split()
line_dict=dict(zip(lst[1:],lst))
res.append(line_dict['TFlops,'])
elif 'perf_tile_gemm_basic' in logfile or 'perf_tile_gemm_mem_pipeline' in logfile:
for line in open(logfile):
if 'TFlops' in line:
lst=line.split()
line_dict=dict(zip(lst[1:],lst))
res.append(line_dict['TFlops,'])
return res
def get_baseline(table, connection):
query = text('''SELECT * from '''+table+''' WHERE Datetime = (SELECT MAX(Datetime) FROM '''+table+''' where Branch_ID='develop' );''')
return pd.read_sql(query, connection)
def store_new_test_result(table_name, test_results, testlist, branch_name, node_id, gpu_arch, compute_units, rocm_vers, hip_vers, environment, connection):
params=[str(branch_name),str(node_id),str(gpu_arch),compute_units,str(rocm_vers),str(hip_vers),str(environment),str(datetime.datetime.now())]
df=pd.DataFrame(data=[params],columns=['Branch_ID','Node_ID','GPU_arch','Compute Units','ROCM_version','HIP_version','Environment','Datetime'])
df_add=pd.DataFrame(data=[test_results],columns=testlist)
df=pd.concat([df,df_add],axis=1)
#print("new test results dataframe:",df)
df.to_sql(table_name,connection,if_exists='append',index=False)
return 0
def compare_test_to_baseline(baseline,test,testlist):
regression=0
if not baseline.empty:
base=baseline[testlist].to_numpy(dtype='float')
base_list=base[0]
ave_perf=0
for i in range(len(base_list)):
# success criterion:
if base_list[i]>1.01*float(test[i]):
print("test # ",i,"shows regression by {:.3f}%".format(
(float(test[i])-base_list[i])/base_list[i]*100))
regression=1
if base_list[i]>0: ave_perf=ave_perf+float(test[i])/base_list[i]
if regression==0:
print("no regressions found")
ave_perf=ave_perf/len(base_list)
print("average performance relative to baseline:",ave_perf)
else:
print("could not find a baseline")
return regression
'''
def post_test_params(tlist,connection):
sorted_dtypes = [x for _,x in sorted(zip(tests,dtype))]
sorted_alayout = [x for _,x in sorted(zip(tests,alayout))]
sorted_blayout = [x for _,x in sorted(zip(tests,blayout))]
sorted_M = [x for _,x in sorted(zip(tests,M))]
sorted_N = [x for _,x in sorted(zip(tests,N))]
sorted_K = [x for _,x in sorted(zip(tests,K))]
sorted_StrideA = [x for _,x in sorted(zip(tests,StrideA))]
sorted_StrideB = [x for _,x in sorted(zip(tests,StrideB))]
sorted_StrideC = [x for _,x in sorted(zip(tests,StrideC))]
ck_gemm_params=[tlist,sorted_dtypes,sorted_alayout,sorted_blayout,
sorted_M,sorted_N,sorted_K,sorted_StrideA,sorted_StrideB,
sorted_StrideC]
df=pd.DataFrame(np.transpose(ck_gemm_params),columns=['Test_number','Data_type',
'Alayout','BLayout','M','N','K', 'StrideA','StrideB','StrideC'])
print(df)
dtypes = {
'Test_number': Integer(),
'Data_type': NVARCHAR(length=5),
'Alayout': NVARCHAR(length=12),
'Blayout': NVARCHAR(length=12),
'M': Integer(),
'N': Integer(),
'K': Integer(),
'StrideA': Integer(),
'StrideB': Integer(),
'StrideC': Integer()
}
df.to_sql("ck_gemm_test_params",connection,if_exists='replace',index=False, dtype=dtypes)
'''
def main():
args = parse_args()
results=[]
tflops_base=[]
testlist=[]
#parse the test parameters from the logfile
for filename in args.files:
branch_name, node_id, gpu_arch, compute_units, rocm_vers, hip_vers, environment = get_log_params(filename)
print("Branch name:",branch_name)
print("Node name:",node_id)
print("GPU_arch:",gpu_arch)
print("Compute units:",compute_units)
print("ROCM_version:",rocm_vers)
print("HIP_version:",hip_vers)
print("Environment:",environment)
#parse results, get the Tflops value for "Best Perf" kernels
results=parse_logfile(filename)
print("Number of tests:",len(results))
sql_hostname = '127.0.0.1'
sql_username = os.environ["dbuser"]
sql_password = os.environ["dbpassword"]
sql_main_database = os.environ["ck_perf_db"]
sql_port = 3306
ssh_host = os.environ["dbsship"]
ssh_user = os.environ["dbsshuser"]
ssh_port = int(os.environ["dbsshport"])
ssh_pass = os.environ["dbsshpassword"]
with SSHTunnelForwarder(
(ssh_host, ssh_port),
ssh_username=ssh_user,
ssh_password=ssh_pass,
remote_bind_address=(sql_hostname, sql_port)) as tunnel:
sqlEngine = sqlalchemy.create_engine('mysql+pymysql://{0}:{1}@{2}:{3}/{4}'.
format(sql_username, sql_password, sql_hostname, tunnel.local_bind_port, sql_main_database))
conn = sqlEngine.connect()
#save gemm performance tests:
if 'perf_gemm' in filename and 'gemm_bilinear' not in filename:
#write the ck_gemm_test_params table only needed once the test set changes
#post_test_params(test_list,conn)
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_gemm_tflops"
if 'batched_gemm' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_batched_gemm_tflops"
if 'grouped_gemm' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_grouped_gemm_tflops"
if 'perf_conv_fwd' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_conv_fwd_tflops"
if 'perf_conv_bwd_data' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_conv_bwd_data_tflops"
if 'grouped_conv_fwd' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_grouped_conv_fwd_tflops"
if 'grouped_conv_bwd_data' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_grouped_conv_bwd_data_tflops"
if 'grouped_conv_bwd_weight' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_grouped_conv_bwd_weight_tflops"
if 'gemm_bilinear' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_gemm_bilinear_tflops"
if 'reduction' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_reduction_GBps"
if 'resnet50_N4' in filename:
for i in range(1,50):
testlist.append("Layer%i"%i)
table_name="ck_resnet50_N4_tflops"
if 'resnet50_N256' in filename:
for i in range(1,50):
testlist.append("Layer%i"%i)
table_name="ck_resnet50_N256_tflops"
if 'onnx_gemm' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_onnx_gemm_tflops"
if 'splitK_gemm' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_splitK_gemm_tflops"
if 'mixed_gemm' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_mixed_gemm_tflops"
if 'fmha_fwd' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_fmha_fwd_tflops"
if 'fmha_bwd' in filename:
for i in range(1,len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_fmha_bwd_tflops"
if 'gemm_basic_fp16' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_basic_fp16_tflops"
if 'gemm_mem_pipeline_fp16' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_mem_pipeline_fp16_tflops"
if 'gemm_basic_bf16' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_basic_bf16_tflops"
if 'gemm_mem_pipeline_bf16' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_mem_pipeline_bf16_tflops"
if 'gemm_basic_fp8' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_basic_fp8_tflops"
if 'gemm_mem_pipeline_fp8' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_mem_pipeline_fp8_tflops"
if 'gemm_basic_bf8' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_basic_bf8_tflops"
if 'gemm_mem_pipeline_bf8' in filename:
for i in range(1, len(results)+1):
testlist.append("Test%i"%i)
table_name="ck_tile_gemm_mem_pipeline_bf8_tflops"
tflops_base = get_baseline(table_name,conn)
store_new_test_result(table_name, results, testlist, branch_name, node_id, gpu_arch, compute_units, rocm_vers, hip_vers, environment, sqlEngine)
conn.close()
#compare the results to the baseline if baseline exists
regression=0
regression=compare_test_to_baseline(tflops_base,results,testlist)
return regression
if __name__ == '__main__':
main()