Have XLA CPU emit TraceMe calls by default in JIT mode (roll forward)

This lets Xprof to enable these `TraceMe`s and produce timelines for XLA CPU.

Rolling forward with bugfix (earlier we would try to create a `void*` type in
LLVM IR, even though LLVM does not allow pointers to void).

PiperOrigin-RevId: 307961400
Change-Id: I0624c32294387a113867c2d80de8cccfd6cd6c21

tensorflow/compiler/aot/tfcompile.bzl

@@ -38,6 +38,7 @@ def tf_library(
         tfcompile_tool = "//tensorflow/compiler/aot:tfcompile",
         include_standard_runtime_deps = True,
         enable_xla_hlo_profiling = False,
+        enable_tracemes = False,
         mlir_components = "None",
         deps = None,
         tags = []):
@@ -89,6 +90,9 @@ def tf_library(
       enable_xla_hlo_profiling: Enable XLA HLO profiling in the generated
         program, and emit metadata that lets us pretty-print the gathered
         profile counters.
+      enable_tracemes: Tell tfcompile to generate calls to
+        TraceMe::Activity{Start|End} around HLO instructions that can be used by
+        Xprof to construct profiler timelines.
       mlir_components: When the value is "None", no components use MLIR. When
         the value is "Bridge", use MLIR to translate GraphDef to HLO.
       deps: a list of deps to include on the build rules for the generated
@@ -190,6 +194,11 @@ def tf_library(
     else:
         profiling_flag = ""
 
+    if enable_tracemes:
+        traceme_flag = "--xla_cpu_enable_xprof_traceme=true"
+    else:
+        traceme_flag = "--xla_cpu_enable_xprof_traceme=false"
+
     mlir_flag = "--mlir_components=" + mlir_components
 
     srcs = [tfcompile_graph, config]
@@ -218,7 +227,7 @@ def tf_library(
             " --out_header=$(@D)/" + header_file +
             " --out_metadata_object=$(@D)/" + metadata_object_file +
             " --out_function_object=$(@D)/" + function_object_file +
-            " " + flags + " " + profiling_flag + " " + mlir_flag
+            " " + flags + " " + profiling_flag + " " + mlir_flag + " " + traceme_flag
         ),
         tools = [tfcompile_tool],
         visibility = visibility,

tensorflow/compiler/xla/debug_options_flags.cc

@@ -63,6 +63,8 @@ DebugOptions DefaultDebugOptionsIgnoringFlags() {
   opts.set_xla_allow_excess_precision(true);
   opts.set_xla_force_host_platform_device_count(1);
   opts.set_xla_gpu_deterministic_reductions(false);
+  opts.set_xla_cpu_enable_xprof_traceme(true);
+
   return opts;
 }
 
@@ -529,7 +531,6 @@ static void AllocateFlags() {
                        flag_values->xla_gpu_algorithm_blacklist_path(),
                        "An AlgorithmBlacklist text proto file as a blacklist "
                        "of convolutions to avoid to use."),
-
       tensorflow::Flag(
           "xla_gpu_deterministic_reductions",
           bool_setter_for(&DebugOptions::set_xla_gpu_deterministic_reductions),
@@ -545,6 +546,12 @@ static void AllocateFlags() {
           bool_setter_for(&DebugOptions::set_xla_tpu_detect_inf),
           flag_values->xla_tpu_detect_inf(),
           "Trigger error on execution on TPU if a INF value is detected"),
+      tensorflow::Flag(
+          "xla_cpu_enable_xprof_traceme",
+          bool_setter_for(&DebugOptions::set_xla_cpu_enable_xprof_traceme),
+          flag_values->xla_cpu_enable_xprof_traceme(),
+          "If true, XLA CPU generates code to call "
+          "TraceMe::Activity{Start|End} around HLO operations."),
   });
   ParseFlagsFromEnvAndDieIfUnknown("XLA_FLAGS", *flag_objects);
 }

tensorflow/compiler/xla/service/cpu/ir_emitter.cc

@@ -182,11 +182,8 @@ StatusOr<llvm::Function*> IrEmitter::EmitComputation(
                     arch_type_ == llvm::Triple::ArchType::x86_64;
   profiling_state_ = ProfilingState(use_rdtscp);
 
-  bool emit_tracing =
+  tracing_state_.set_enabled(
-      hlo_module_config_.hlo_profiling_enabled() &&
+      computation->parent()->config().cpu_traceme_enabled());
-      hlo_module_config_.debug_options().xla_backend_extra_options().count(
-          "xla_hlo_trace");
-  tracing_state_.set_enabled(emit_tracing);
 
   TF_RETURN_IF_ERROR(computation->AcceptOrdered(this, instruction_order));
   llvm::Function* ir_function = compute_function_->function();
@@ -3126,7 +3123,8 @@ void IrEmitter::TracingState::EmitTracingStart(llvm::IRBuilder<>* b,
   }
 
   llvm::Type* int8_ptr_type = b->getInt8Ty()->getPointerTo();
-  llvm::Type* void_ptr_type = b->getVoidTy()->getPointerTo();
+  llvm::Type* void_ptr_type =
+      int8_ptr_type;  // LLVM does not have a void*, we use an int8* instead.
   llvm::FunctionType* fn_type =
       llvm::FunctionType::get(b->getInt64Ty(), {void_ptr_type, int8_ptr_type},
                               /*isVarArg=*/false);
@@ -3156,7 +3154,9 @@ void IrEmitter::TracingState::EmitTracingEnd(llvm::IRBuilder<>* b,
     return;
   }
 
-  llvm::Type* void_ptr_type = b->getVoidTy()->getPointerTo();
+  llvm::Type* void_ptr_type =
+      b->getInt8Ty()->getPointerTo();  // LLVM does not have a void*, we use an
+                                       // int8* instead.
   llvm::FunctionType* fn_type =
       llvm::FunctionType::get(b->getVoidTy(), {void_ptr_type, b->getInt64Ty()},
                               /*isVarArg=*/false);

tensorflow/compiler/xla/service/hlo_module_config.h

@@ -104,6 +104,10 @@ class HloModuleConfig {
     return debug_options_.xla_hlo_profile();
   }
 
+  bool cpu_traceme_enabled() const {
+    return debug_options_.xla_cpu_enable_xprof_traceme();
+  }
+
   // Sets/returns the module seed set during execution.
   void set_seed(uint64 seed) { seed_ = seed; }
   uint64 seed() const { return seed_; }

tensorflow/compiler/xla/xla.proto

@@ -269,7 +269,10 @@ message DebugOptions {
   bool xla_tpu_detect_nan = 135;
   bool xla_tpu_detect_inf = 136;
 
-  // Next id: 137
+  // True if TraceMe annotations are enabled for XLA:CPU.
+  bool xla_cpu_enable_xprof_traceme = 137;
+
+  // Next id: 138
 
   // Extra options to pass to the compilation backend (e.g. LLVM); specific
   // interpretation of these values is left to the backend.