#!/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()