YDB Import 559

1 files changed, 0 insertions, 318 deletions

diff --git a/contrib/libs/llvm12/include/llvm/Support/Parallel.h b/contrib/libs/llvm12/include/llvm/Support/Parallel.h
deleted file mode 100644
index ac053bb4cce..00000000000
--- a/contrib/libs/llvm12/include/llvm/Support/Parallel.h
+++ /dev/null
@@ -1,318 +0,0 @@
-#pragma once
-
-#ifdef __GNUC__
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wunused-parameter"
-#endif
-
-//===- llvm/Support/Parallel.h - Parallel algorithms ----------------------===//
-//
-// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-//
-//===----------------------------------------------------------------------===//
-
-#ifndef LLVM_SUPPORT_PARALLEL_H
-#define LLVM_SUPPORT_PARALLEL_H
-
-#include "llvm/ADT/STLExtras.h"
-#include "llvm/Config/llvm-config.h"
-#include "llvm/Support/Error.h"
-#include "llvm/Support/MathExtras.h"
-#include "llvm/Support/Threading.h"
-
-#include <algorithm>
-#include <condition_variable>
-#include <functional>
-#include <mutex>
-
-namespace llvm {
-
-namespace parallel {
-
-// Strategy for the default executor used by the parallel routines provided by
-// this file. It defaults to using all hardware threads and should be
-// initialized before the first use of parallel routines.
-extern ThreadPoolStrategy strategy;
-
-namespace detail {
-
-#if LLVM_ENABLE_THREADS
-
-class Latch {
-  uint32_t Count;
-  mutable std::mutex Mutex;
-  mutable std::condition_variable Cond;
-
-public:
-  explicit Latch(uint32_t Count = 0) : Count(Count) {}
-  ~Latch() { sync(); }
-
-  void inc() {
-    std::lock_guard<std::mutex> lock(Mutex);
-    ++Count;
-  }
-
-  void dec() {
-    std::lock_guard<std::mutex> lock(Mutex);
-    if (--Count == 0)
-      Cond.notify_all();
-  }
-
-  void sync() const {
-    std::unique_lock<std::mutex> lock(Mutex);
-    Cond.wait(lock, [&] { return Count == 0; });
-  }
-};
-
-class TaskGroup {
-  Latch L;
-  bool Parallel;
-
-public:
-  TaskGroup();
-  ~TaskGroup();
-
-  void spawn(std::function<void()> f);
-
-  void sync() const { L.sync(); }
-};
-
-const ptrdiff_t MinParallelSize = 1024;
-
-/// Inclusive median.
-template <class RandomAccessIterator, class Comparator>
-RandomAccessIterator medianOf3(RandomAccessIterator Start,
-                               RandomAccessIterator End,
-                               const Comparator &Comp) {
-  RandomAccessIterator Mid = Start + (std::distance(Start, End) / 2);
-  return Comp(*Start, *(End - 1))
-             ? (Comp(*Mid, *(End - 1)) ? (Comp(*Start, *Mid) ? Mid : Start)
-                                       : End - 1)
-             : (Comp(*Mid, *Start) ? (Comp(*(End - 1), *Mid) ? Mid : End - 1)
-                                   : Start);
-}
-
-template <class RandomAccessIterator, class Comparator>
-void parallel_quick_sort(RandomAccessIterator Start, RandomAccessIterator End,
-                         const Comparator &Comp, TaskGroup &TG, size_t Depth) {
-  // Do a sequential sort for small inputs.
-  if (std::distance(Start, End) < detail::MinParallelSize || Depth == 0) {
-    llvm::sort(Start, End, Comp);
-    return;
-  }
-
-  // Partition.
-  auto Pivot = medianOf3(Start, End, Comp);
-  // Move Pivot to End.
-  std::swap(*(End - 1), *Pivot);
-  Pivot = std::partition(Start, End - 1, [&Comp, End](decltype(*Start) V) {
-    return Comp(V, *(End - 1));
-  });
-  // Move Pivot to middle of partition.
-  std::swap(*Pivot, *(End - 1));
-
-  // Recurse.
-  TG.spawn([=, &Comp, &TG] {
-    parallel_quick_sort(Start, Pivot, Comp, TG, Depth - 1);
-  });
-  parallel_quick_sort(Pivot + 1, End, Comp, TG, Depth - 1);
-}
-
-template <class RandomAccessIterator, class Comparator>
-void parallel_sort(RandomAccessIterator Start, RandomAccessIterator End,
-                   const Comparator &Comp) {
-  TaskGroup TG;
-  parallel_quick_sort(Start, End, Comp, TG,
-                      llvm::Log2_64(std::distance(Start, End)) + 1);
-}
-
-// TaskGroup has a relatively high overhead, so we want to reduce
-// the number of spawn() calls. We'll create up to 1024 tasks here.
-// (Note that 1024 is an arbitrary number. This code probably needs
-// improving to take the number of available cores into account.)
-enum { MaxTasksPerGroup = 1024 };
-
-template <class IterTy, class FuncTy>
-void parallel_for_each(IterTy Begin, IterTy End, FuncTy Fn) {
-  // Limit the number of tasks to MaxTasksPerGroup to limit job scheduling
-  // overhead on large inputs.
-  ptrdiff_t TaskSize = std::distance(Begin, End) / MaxTasksPerGroup;
-  if (TaskSize == 0)
-    TaskSize = 1;
-
-  TaskGroup TG;
-  while (TaskSize < std::distance(Begin, End)) {
-    TG.spawn([=, &Fn] { std::for_each(Begin, Begin + TaskSize, Fn); });
-    Begin += TaskSize;
-  }
-  std::for_each(Begin, End, Fn);
-}
-
-template <class IndexTy, class FuncTy>
-void parallel_for_each_n(IndexTy Begin, IndexTy End, FuncTy Fn) {
-  // Limit the number of tasks to MaxTasksPerGroup to limit job scheduling
-  // overhead on large inputs.
-  ptrdiff_t TaskSize = (End - Begin) / MaxTasksPerGroup;
-  if (TaskSize == 0)
-    TaskSize = 1;
-
-  TaskGroup TG;
-  IndexTy I = Begin;
-  for (; I + TaskSize < End; I += TaskSize) {
-    TG.spawn([=, &Fn] {
-      for (IndexTy J = I, E = I + TaskSize; J != E; ++J)
-        Fn(J);
-    });
-  }
-  for (IndexTy J = I; J < End; ++J)
-    Fn(J);
-}
-
-template <class IterTy, class ResultTy, class ReduceFuncTy,
-          class TransformFuncTy>
-ResultTy parallel_transform_reduce(IterTy Begin, IterTy End, ResultTy Init,
-                                   ReduceFuncTy Reduce,
-                                   TransformFuncTy Transform) {
-  // Limit the number of tasks to MaxTasksPerGroup to limit job scheduling
-  // overhead on large inputs.
-  size_t NumInputs = std::distance(Begin, End);
-  if (NumInputs == 0)
-    return std::move(Init);
-  size_t NumTasks = std::min(static_cast<size_t>(MaxTasksPerGroup), NumInputs);
-  std::vector<ResultTy> Results(NumTasks, Init);
-  {
-    // Each task processes either TaskSize or TaskSize+1 inputs. Any inputs
-    // remaining after dividing them equally amongst tasks are distributed as
-    // one extra input over the first tasks.
-    TaskGroup TG;
-    size_t TaskSize = NumInputs / NumTasks;
-    size_t RemainingInputs = NumInputs % NumTasks;
-    IterTy TBegin = Begin;
-    for (size_t TaskId = 0; TaskId < NumTasks; ++TaskId) {
-      IterTy TEnd = TBegin + TaskSize + (TaskId < RemainingInputs ? 1 : 0);
-      TG.spawn([=, &Transform, &Reduce, &Results] {
-        // Reduce the result of transformation eagerly within each task.
-        ResultTy R = Init;
-        for (IterTy It = TBegin; It != TEnd; ++It)
-          R = Reduce(R, Transform(*It));
-        Results[TaskId] = R;
-      });
-      TBegin = TEnd;
-    }
-    assert(TBegin == End);
-  }
-
-  // Do a final reduction. There are at most 1024 tasks, so this only adds
-  // constant single-threaded overhead for large inputs. Hopefully most
-  // reductions are cheaper than the transformation.
-  ResultTy FinalResult = std::move(Results.front());
-  for (ResultTy &PartialResult :
-       makeMutableArrayRef(Results.data() + 1, Results.size() - 1))
-    FinalResult = Reduce(FinalResult, std::move(PartialResult));
-  return std::move(FinalResult);
-}
-
-#endif
-
-} // namespace detail
-} // namespace parallel
-
-template <class RandomAccessIterator,
-          class Comparator = std::less<
-              typename std::iterator_traits<RandomAccessIterator>::value_type>>
-void parallelSort(RandomAccessIterator Start, RandomAccessIterator End,
-                  const Comparator &Comp = Comparator()) {
-#if LLVM_ENABLE_THREADS
-  if (parallel::strategy.ThreadsRequested != 1) {
-    parallel::detail::parallel_sort(Start, End, Comp);
-    return;
-  }
-#endif
-  llvm::sort(Start, End, Comp);
-}
-
-template <class IterTy, class FuncTy>
-void parallelForEach(IterTy Begin, IterTy End, FuncTy Fn) {
-#if LLVM_ENABLE_THREADS
-  if (parallel::strategy.ThreadsRequested != 1) {
-    parallel::detail::parallel_for_each(Begin, End, Fn);
-    return;
-  }
-#endif
-  std::for_each(Begin, End, Fn);
-}
-
-template <class FuncTy>
-void parallelForEachN(size_t Begin, size_t End, FuncTy Fn) {
-#if LLVM_ENABLE_THREADS
-  if (parallel::strategy.ThreadsRequested != 1) {
-    parallel::detail::parallel_for_each_n(Begin, End, Fn);
-    return;
-  }
-#endif
-  for (size_t I = Begin; I != End; ++I)
-    Fn(I);
-}
-
-template <class IterTy, class ResultTy, class ReduceFuncTy,
-          class TransformFuncTy>
-ResultTy parallelTransformReduce(IterTy Begin, IterTy End, ResultTy Init,
-                                 ReduceFuncTy Reduce,
-                                 TransformFuncTy Transform) {
-#if LLVM_ENABLE_THREADS
-  if (parallel::strategy.ThreadsRequested != 1) {
-    return parallel::detail::parallel_transform_reduce(Begin, End, Init, Reduce,
-                                                       Transform);
-  }
-#endif
-  for (IterTy I = Begin; I != End; ++I)
-    Init = Reduce(std::move(Init), Transform(*I));
-  return std::move(Init);
-}
-
-// Range wrappers.
-template <class RangeTy,
-          class Comparator = std::less<decltype(*std::begin(RangeTy()))>>
-void parallelSort(RangeTy &&R, const Comparator &Comp = Comparator()) {
-  parallelSort(std::begin(R), std::end(R), Comp);
-}
-
-template <class RangeTy, class FuncTy>
-void parallelForEach(RangeTy &&R, FuncTy Fn) {
-  parallelForEach(std::begin(R), std::end(R), Fn);
-}
-
-template <class RangeTy, class ResultTy, class ReduceFuncTy,
-          class TransformFuncTy>
-ResultTy parallelTransformReduce(RangeTy &&R, ResultTy Init,
-                                 ReduceFuncTy Reduce,
-                                 TransformFuncTy Transform) {
-  return parallelTransformReduce(std::begin(R), std::end(R), Init, Reduce,
-                                 Transform);
-}
-
-// Parallel for-each, but with error handling.
-template <class RangeTy, class FuncTy>
-Error parallelForEachError(RangeTy &&R, FuncTy Fn) {
-  // The transform_reduce algorithm requires that the initial value be copyable.
-  // Error objects are uncopyable. We only need to copy initial success values,
-  // so work around this mismatch via the C API. The C API represents success
-  // values with a null pointer. The joinErrors discards null values and joins
-  // multiple errors into an ErrorList.
-  return unwrap(parallelTransformReduce(
-      std::begin(R), std::end(R), wrap(Error::success()),
-      [](LLVMErrorRef Lhs, LLVMErrorRef Rhs) {
-        return wrap(joinErrors(unwrap(Lhs), unwrap(Rhs)));
-      },
-      [&Fn](auto &&V) { return wrap(Fn(V)); }));
-}
-
-} // namespace llvm
-
-#endif // LLVM_SUPPORT_PARALLEL_H
-
-#ifdef __GNUC__
-#pragma GCC diagnostic pop
-#endif