separate build test

EnzymeAD · Jan 25, 2025 · fb4b24f · fb4b24f
1 parent a33e314
commit fb4b24f
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Showing 10 changed files with 335 additions and 67 deletions.
diff --git a/WORKSPACE b/WORKSPACE
@@ -28,9 +28,9 @@ http_archive(
 load("@jax//third_party/xla:workspace.bzl", "XLA_COMMIT", "XLA_SHA256")
 http_archive(
     name = "xla",
-    sha256 = XLA_SHA256,
+    # sha256 = XLA_SHA256,
     strip_prefix = "xla-" + XLA_COMMIT,
-    urls = ["https://github.com/wsmoses/xla/archive/{commit}.tar.gz".format(commit = XLA_COMMIT)],
+    urls = ["https://github.com/smjleo/xla/archive/{commit}.tar.gz".format(commit = XLA_COMMIT)],
     patch_cmds = XLA_PATCHES,
 )
 

diff --git a/src/enzyme_ad/jax/AnalyticalCostModel.cpp b/src/enzyme_ad/jax/AnalyticalCostModel.cpp
@@ -0,0 +1,110 @@
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/BuiltinTypes.h"
+#include "mlir/IR/MLIRContext.h"
+#include "mlir/IR/Operation.h"
+#include "mlir/IR/OperationSupport.h"
+#include "mlir/IR/Types.h"
+#include "mlir/IR/Value.h"
+#include "mlir/IR/Verifier.h"
+#include "mlir/Pass/Pass.h"
+#include "mlir/Pass/PassManager.h"
+
+#include "xla/mlir_hlo/mhlo/transforms/passes.h"
+#include "xla/service/backend.h"
+#include "xla/service/gpu/gpu_latency_hiding_scheduler.h"
+#include "xla/service/gpu/model/gpu_hlo_cost_analysis.h"
+#include "xla/service/gpu/model/gpu_performance_model.h"
+#include "xla/service/platform_util.h"
+#include "xla/stream_executor/cuda/cuda_platform_id.h"
+#include "xla/stream_executor/device_description.h"
+#include "xla/stream_executor/platform.h"
+#include "xla/stream_executor/platform_manager.h"
+#include "xla/translate/mhlo_to_hlo/mlir_hlo_to_hlo.h"
+
+#include <iostream>
+#include <memory>
+#include <stdexcept>
+#include <string>
+
+#include "AnalyticalCostModel.h"
+#include "RunXlaGpuPasses.h"
+
+using namespace mlir;
+
+uint64_t AnalyticalCostModel::getAnalyticalCost(ModuleOp &wrapperModule) {
+  std::unique_ptr<xla::HloModule> preOpt =
+      wrapperModuleToHloModule(wrapperModule);
+
+  // Run XLA passes (layout, fusion, simplification) to ensure what is being
+  // measured is what will be run
+  auto hloModule = runXlaGpuPasses(std::move(preOpt));
+
+  auto deviceDescription = getDeviceDescription();
+
+  xla::HloCostAnalysis::ShapeSizeFunction shapeSizeFunction =
+      [](const xla::Shape &shape) {
+        return xla::gpu::GetSizeOfShape(shape, 4);
+      };
+  xla::gpu::GpuHloCostAnalysis costAnalysis(
+      xla::gpu::GpuHloCostAnalysis::Options{shapeSizeFunction, {}, {}, true},
+      *deviceDescription);
+
+  assert(hloModule->computation_count() == 1);
+
+  uint64_t cost = -1;
+
+  for (auto c : hloModule->computations()) {
+    c->Accept(&costAnalysis);
+    // The op we are measuring should always be the return value, which is
+    // at the root.
+    auto op = c->root_instruction();
+
+    auto runtime = xla::gpu::GpuPerformanceModel::EstimateRunTimeForInstruction(
+        op, *deviceDescription, &costAnalysis,
+        xla::gpu::GpuPerformanceModelOptions::ForModule(op->GetModule()));
+    if (cost != -1) {
+      throw std::invalid_argument("found two computations");
+    }
+    cost = absl::ToInt64Nanoseconds(runtime.exec_time);
+  }
+
+  return cost;
+}
+
+/**
+ * Create XLA internal HloModule for the analytical cost model
+ */
+std::unique_ptr<xla::HloModule>
+AnalyticalCostModel::wrapperModuleToHloModule(ModuleOp &wrapperModule) {
+  auto context = wrapperModule.getContext();
+  PassManager pm(context);
+  pm.addPass(mlir::mhlo::createStablehloLegalizeToHloPass());
+  pm.run(wrapperModule);
+
+  MlirToHloConversionOptions options;
+  options.propagate_layouts = true;
+  options.return_tuple = false;
+
+  auto hloModule = ConvertMlirHloToHloModule(wrapperModule, options);
+  if (!hloModule.ok()) {
+    llvm::errs() << "Couldn't create hloModule: "
+                 << hloModule.status().message();
+    return nullptr;
+  } else {
+    return std::move(hloModule.value());
+  }
+}
+
+stream_executor::Platform *AnalyticalCostModel::getXlaPlatform() {
+  return xla::PlatformUtil::GetPlatform("cuda").value();
+}
+
+/**
+ * Get DeviceDescription for current device.
+ */
+std::unique_ptr<stream_executor::DeviceDescription>
+AnalyticalCostModel::getDeviceDescription() {
+  // assume ordinal 0
+  return std::move(getXlaPlatform()->DescriptionForDevice(0).value());
+}
diff --git a/src/enzyme_ad/jax/AnalyticalCostModel.h b/src/enzyme_ad/jax/AnalyticalCostModel.h
@@ -0,0 +1,46 @@
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/BuiltinTypes.h"
+#include "mlir/IR/MLIRContext.h"
+#include "mlir/IR/Operation.h"
+#include "mlir/IR/OperationSupport.h"
+#include "mlir/IR/Types.h"
+#include "mlir/IR/Value.h"
+#include "mlir/IR/Verifier.h"
+
+#include "xla/mlir_hlo/mhlo/transforms/passes.h"
+#include "xla/service/backend.h"
+#include "xla/service/gpu/gpu_latency_hiding_scheduler.h"
+#include "xla/service/gpu/model/gpu_hlo_cost_analysis.h"
+#include "xla/service/gpu/model/gpu_performance_model.h"
+#include "xla/service/platform_util.h"
+#include "xla/stream_executor/cuda/cuda_platform_id.h"
+#include "xla/stream_executor/device_description.h"
+#include "xla/stream_executor/platform.h"
+#include "xla/stream_executor/platform_manager.h"
+#include "xla/translate/mhlo_to_hlo/mlir_hlo_to_hlo.h"
+
+#include <iostream>
+#include <memory>
+#include <stdexcept>
+#include <string>
+
+class AnalyticalCostModel {
+public:
+  static uint64_t getAnalyticalCost(mlir::ModuleOp &wrapperModule);
+
+private:
+  /**
+   * Create XLA internal HloModule for the analytical cost model
+   */
+  static std::unique_ptr<xla::HloModule>
+  wrapperModuleToHloModule(mlir::ModuleOp &wrapperModule);
+
+  static stream_executor::Platform *getXlaPlatform();
+
+  /**
+   * Get DeviceDescription for current device.
+   */
+  static std::unique_ptr<stream_executor::DeviceDescription>
+  getDeviceDescription();
+};
diff --git a/src/enzyme_ad/jax/AnalyticalCostModelStub.cpp b/src/enzyme_ad/jax/AnalyticalCostModelStub.cpp
@@ -0,0 +1,46 @@
+#include "AnalyticalCostModel.h"
+
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/BuiltinTypes.h"
+#include "mlir/IR/MLIRContext.h"
+#include "mlir/IR/Operation.h"
+#include "mlir/IR/OperationSupport.h"
+#include "mlir/IR/Types.h"
+#include "mlir/IR/Value.h"
+#include "mlir/IR/Verifier.h"
+
+#include "xla/mlir_hlo/mhlo/transforms/passes.h"
+#include "xla/service/backend.h"
+#include "xla/service/gpu/gpu_latency_hiding_scheduler.h"
+#include "xla/service/gpu/model/gpu_hlo_cost_analysis.h"
+#include "xla/service/gpu/model/gpu_performance_model.h"
+#include "xla/service/platform_util.h"
+#include "xla/stream_executor/cuda/cuda_platform_id.h"
+#include "xla/stream_executor/device_description.h"
+#include "xla/stream_executor/platform.h"
+#include "xla/stream_executor/platform_manager.h"
+#include "xla/translate/mhlo_to_hlo/mlir_hlo_to_hlo.h"
+
+#include <iostream>
+#include <memory>
+#include <stdexcept>
+#include <string>
+
+uint64_t AnalyticalCostModel::getAnalyticalCost(mlir::ModuleOp &wrapperModule) {
+  throw std::runtime_error("stub");
+}
+
+std::unique_ptr<xla::HloModule>
+AnalyticalCostModel::wrapperModuleToHloModule(mlir::ModuleOp &wrapperModule) {
+  throw std::runtime_error("stub");
+}
+
+stream_executor::Platform *AnalyticalCostModel::getXlaPlatform() {
+  throw std::runtime_error("stub");
+}
+
+std::unique_ptr<stream_executor::DeviceDescription>
+AnalyticalCostModel::getDeviceDescription() {
+  throw std::runtime_error("stub");
+}
diff --git a/src/enzyme_ad/jax/BUILD b/src/enzyme_ad/jax/BUILD
@@ -225,6 +225,76 @@ gentbl_cc_library(
     tblgen = "//:enzymexlamlir-tblgen",
 )
 
+cc_library(
+    name = "RunXlaGpuPassesHdr",
+    hdrs = ["RunXlaGpuPasses.h"],
+    deps = [
+    "@xla//xla/hlo/ir:hlo",
+    ],
+    alwayslink = True,
+    linkstatic = True,
+)
+
+cc_library(
+    name = "RunXlaGpuPassesStub",
+    srcs = ["RunXlaGpuPassesStub.cpp"],
+    deps = [":RunXlaGpuPassesHdr"],
+    alwayslink = True,
+    linkstatic = True,
+)
+
+cc_library(
+    name = "RunXlaGpuPasses",
+    srcs = ["RunXlaGpuPasses.cpp"],
+    deps = [
+       ":RunXlaGpuPassesHdr",
+
+        "@xla//xla/stream_executor:stream_executor_impl",
+        "@xla//xla/translate/stablehlo_to_hlo:translate",
+        "@xla//xla/translate/mhlo_to_hlo:mlir_hlo_to_hlo",
+
+        "@xla//xla/service:backend",
+        "@xla//xla/service/gpu/model:gpu_performance_model",
+        "@xla//xla/service/gpu/model:hlo_op_profile_proto_cc_impl",
+        "@xla//xla/service/gpu/model:gpu_hlo_cost_analysis",
+        "@xla//xla/service/gpu:gpu_latency_hiding_scheduler",
+        "@xla//xla/service/gpu:nvptx_compiler",
+        "@xla//xla/stream_executor:device_description",
+    ]
+)
+
+
+cc_library(
+    name = "AnalyticalCostModel",
+    srcs = ["AnalyticalCostModel.cpp"],
+    hdrs = ["AnalyticalCostModel.h"],
+    deps = [
+        "@llvm-project//mlir:IR",
+        "@llvm-project//mlir:Pass",
+        "@llvm-project//mlir:Support",
+
+        "@stablehlo//:reference_ops",
+        "@stablehlo//:stablehlo_ops",
+        "@stablehlo//:stablehlo_passes",
+        "@xla//xla/mlir_hlo",
+
+        "@xla//xla/stream_executor:stream_executor_impl",
+        "@xla//xla/translate/stablehlo_to_hlo:translate",
+        "@xla//xla/translate/mhlo_to_hlo:mlir_hlo_to_hlo",
+
+        "@xla//xla/service:backend",
+        "@xla//xla/service/gpu/model:gpu_performance_model",
+        "@xla//xla/service/gpu/model:hlo_op_profile_proto_cc_impl",
+        "@xla//xla/service/gpu/model:gpu_hlo_cost_analysis",
+        "@xla//xla/service/gpu:gpu_latency_hiding_scheduler",
+        "@xla//xla/stream_executor:device_description",
+    ] + select({
+    "@bazel_tools//src/conditions:darwin": [":RunXlaGpuPassesStub"],
+    "//conditions:default": [":RunXlaGpuPasses"]}),
+    alwayslink = True,
+    linkstatic = True,
+)
+
 cc_library(
     name = "XLADerivatives",
     srcs = glob(
@@ -246,6 +316,7 @@ cc_library(
         "-Werror=unused-result",
     ],
     deps = [
+        ":AnalyticalCostModel",
         ":EnzymeXLAPassesIncGen",
         ":EnzyeHLOPatternsIncGen",
         ":mhlo-derivatives",