Added mesurement only on middle 2 quartile, default for simd analysis…

… with tags (#2527)

Signed-off-by: Alexandre Eichenberger <[email protected]>

utils/RunONNXModel.py

@@ -155,11 +155,13 @@ def check_non_negative(argname, value):
                     " E.g. --upper-bound=int64:10,float32:0.2,uint8:9."
                     " Supported types are bool, uint8, int8, uint16, int16, uint32, int32,"
                     " uint64, int64, float16, float32, float64")
-parser.add_argument('--warmup',
+parser.add_argument('-w',
+                    '--warmup',
                     type=lambda s: check_non_negative("--warmup", s),
                     default=0,
                     help="The number of warmup inference runs")
-parser.add_argument('--n-iteration',
+parser.add_argument('-n',
+                    '--n-iteration',
                     type=lambda s: check_positive("--n-iteration", s),
                     default=1,
                     help="The number of inference runs excluding warmup")
@@ -495,6 +497,10 @@ def verify_outs(actual_outs, ref_outs):
 def warning(msg):
     print("Warning:", msg)
 
+def data_without_top_bottom_quartile(data, percent):
+    data = np.array(sorted(data))
+    trim = int(percent*data.size/100.0)
+    return data[trim:-trim]
 
 def main():
     if not (args.model or args.load_so):
@@ -646,14 +652,19 @@ def main():
             end = time.perf_counter()
             elapsed = end - start
             perf_results += [elapsed]
-            print("  {} iteration: {} seconds".format(ordinal(i+1), elapsed))
+            print("  {} iteration, {}, seconds".format(ordinal(i+1), elapsed))
 
         # Print statistics info, e.g., min/max/stddev inference time.
         if args.n_iteration > 1 :
-            print("  Statistics (excluding warmup):"
-                  " min {}, max {}, mean {}, stddev {}".format(
+            print("  Statistics 1 (excluding warmup),"
+                  " min, {:.6e}, max, {:.6e}, mean, {:.6e}, stdev, {:.6e}".format(
                 np.min(perf_results), np.max(perf_results),
-                np.mean(perf_results), np.std(perf_results, dtype=np.float64)))
+                np.mean(perf_results),np.std(perf_results, dtype=np.float64)))
+            t_perf_results = data_without_top_bottom_quartile(perf_results, 25)
+            print("  Statistics 2 (no warmup/quart.),"
+                  " min, {:.6e}, max, {:.6e}, mean, {:.6e}, stdev, {:.6e}".format(
+                np.min(t_perf_results), np.max(t_perf_results),
+                np.mean(t_perf_results),np.std(t_perf_results, dtype=np.float64)))
 
 
         # Print the output if required.

utils/analyze-simd.py

@@ -14,6 +14,7 @@
 import re
 import io
 import subprocess
+from pathlib import Path
 
 ################################################################################
 # Usage.
@@ -25,7 +26,7 @@ def print_usage(msg = ""):
     dprint("")
     if msg:
         dprint("ERROR: " + msg + "\n")
-    dprint("analyze-simd [-a <arch>] (-c|-m|-o)+ [-n num] [-f pattern] [-dhlp] file")
+    dprint("analyze-simd [-t <arch>] (-a|-c|-m|-o)+ [-n num] [-f pattern] [-dhlp] file")
     dprint("  Utility to analyze and print SIMD code located in functions")
     dprint("")
     dprint("Pattern:")
@@ -59,7 +60,7 @@ def print_usage(msg = ""):
 print_code = False
 print_listing = False
 print_details = False
-fct_match_str = r'^main_graph$'
+fct_match_str = ""
 op_dict = {}
 aggr_dict = {}
 op_name = {}
@@ -426,13 +427,20 @@ def main(argv):
         # All commands after the file name seems to be added here!!!
         print_usage("Need an single input file as last option: ", args, ".")
     filename = args[0]
+
+    name_stub = Path(filename).stem
+    if not fct_match_str:
+        fct_match_str = r'^main_graph_' + name_stub + '$'
+        print("# search default function: main_graph with default tag \""+fct_match_str+"\"")
+
     match_binary = re.match(r'(.*)\.so$', filename)
     if match_binary:
         asm_filename = match_binary.group(1) + ".s"
         cmd = "objdump -S ./" + filename + " > ./" + asm_filename
         dprint("# generate asm file with: " + cmd)
         ret = subprocess.call(cmd, shell=True)
         filename = asm_filename
+
     scan_basic_blocks(filename)
     buff = scan_for_simd(filename, pattern, num)
     return