lld/test/MachO/bp-section-orderer-stress.s

   1 # REQUIRES: aarch64
   2
   3 # Generate a large test case and check that the output is deterministic.
   4
   5 # RUN: %python %s %t.s %t.proftext
   6
   7 # RUN: llvm-mc -filetype=obj -triple=arm64-apple-darwin %t.s -o %t.o
   8 # RUN: llvm-profdata merge %t.proftext -o %t.profdata
   9
  10 # RUN: %no-fatal-warnings-lld -arch arm64 -lSystem -e _main --icf=all -o - %t.o --irpgo-profile-sort=%t.profdata --compression-sort-startup-functions --compression-sort=both | llvm-nm --numeric-sort --format=just-symbols - > %t.order1.txt
  11 # RUN: %no-fatal-warnings-lld -arch arm64 -lSystem -e _main --icf=all -o - %t.o --irpgo-profile-sort=%t.profdata --compression-sort-startup-functions --compression-sort=both | llvm-nm --numeric-sort --format=just-symbols - > %t.order2.txt
  12 # RUN: diff %t.order1.txt %t.order2.txt
  13
  14 # RUN: %lld -arch arm64 -lSystem -e _main --icf=all -o - %t.o --irpgo-profile=%t.profdata --bp-startup-sort=function --bp-compression-sort-startup-functions --bp-compression-sort=both | llvm-nm --numeric-sort --format=just-symbols - > %t.order1.txt
  15 # RUN: %lld -arch arm64 -lSystem -e _main --icf=all -o - %t.o --irpgo-profile=%t.profdata --bp-startup-sort=function --bp-compression-sort-startup-functions --bp-compression-sort=both | llvm-nm --numeric-sort --format=just-symbols - > %t.order2.txt
  16 # RUN: diff %t.order1.txt %t.order2.txt
  17 import random
  18 import sys
  19
  20 assembly_filepath = sys.argv[1]
  21 proftext_filepath = sys.argv[2]
  22
  23 random.seed(1234)
  24 num_functions = 1000
  25 num_data = 100
  26 num_traces = 10
  27
  28 function_names = [f"f{n}" for n in range(num_functions)]
  29 data_names = [f"d{n}" for n in range(num_data)]
  30 profiled_functions = function_names[: int(num_functions / 2)]
  31
  32 function_contents = [
  33     f"""
  34 {name}:
  35   add w0, w0, #{i % 4096}
  36   add w1, w1, #{i % 10}
  37   add w2, w0, #{i % 20}
  38   adrp x3, {name}@PAGE
  39   ret
  40 """
  41     for i, name in enumerate(function_names)
  42 ]
  43
  44 data_contents = [
  45       f"""
  46 {name}:
  47   .ascii "s{i % 2}-{i % 3}-{i % 5}"
  48   .xword {name}
  49 """
  50     for i, name in enumerate(data_names)
  51 ]
  52
  53 trace_contents = [
  54     f"""
  55 # Weight
  56 1
  57 {", ".join(random.sample(profiled_functions, len(profiled_functions)))}
  58 """
  59     for i in range(num_traces)
  60 ]
  61
  62 profile_contents = [
  63     f"""
  64 {name}
  65 # Func Hash:
  66 {i}
  67 # Num Counters:
  68 1
  69 # Counter Values:
  70 1
  71 """
  72     for i, name in enumerate(profiled_functions)
  73 ]
  74
  75 with open(assembly_filepath, "w") as f:
  76     f.write(
  77         f"""
  78 .text
  79 .globl _main
  80
  81 _main:
  82   ret
  83
  84 {"".join(function_contents)}
  85
  86 .data
  87 {"".join(data_contents)}
  88
  89 .subsections_via_symbols
  90 """
  91     )
  92
  93 with open(proftext_filepath, "w") as f:
  94     f.write(
  95         f"""
  96 :ir
  97 :temporal_prof_traces
  98
  99 # Num Traces
 100 {num_traces}
 101 # Trace Stream Size:
 102 {num_traces}
 103
 104 {"".join(trace_contents)}
 105
 106 {"".join(profile_contents)}
 107 """
 108     )