primecount 0.2.1

///
/// @file  LoadBalancerS2.cpp
/// @brief The LoadBalancerS2 assigns work to the individual threads
///        in the computation of the special leaves in the
///        Lagarias-Miller-Odlyzko, Deleglise-Rivat and Gourdon
///        prime counting algorithms. This load balancer is used
///        by the S2_hard(x, y) and D(x, y) functions.
///
///        Simply parallelizing the computation of the special
///        leaves in the Lagarias-Miller-Odlyzko algorithm by
///        subdividing the sieve interval by the number of threads
///        into equally sized subintervals does not scale because
///        the distribution of the special leaves is highly skewed
///        and most special leaves are in the first few segments
///        whereas later on there are very few special leaves.
///
///        This LoadBalancerS2 gradually increases the number of
///        segments to sieve as long the expected runtime of the
///        sieve distance is smaller than the expected finish time
///        of the algorithm. Near the end the LoadBalancerS2 will
///        gradually decrease the number of segments to sieve in
///        order to prevent that 1 thread will run much longer
///        than all the other threads.
///
/// Copyright (C) 2021 Kim Walisch, <kim.walisch@gmail.com>
///
/// This file is distributed under the BSD License. See the COPYING
/// file in the top level directory.
///

#include <LoadBalancerS2.hpp>
#include <primecount-internal.hpp>
#include <StatusS2.hpp>
#include <Sieve.hpp>
#include <imath.hpp>
#include <int128_t.hpp>
#include <min.hpp>

#include <stdint.h>

namespace primecount {

LoadBalancerS2::LoadBalancerS2(maxint_t x,
                               int64_t sieve_limit,
                               maxint_t sum_approx,
                               int threads,
                               bool is_print) :
  sieve_limit_(sieve_limit),
  sum_approx_(sum_approx),
  time_(get_time()),
  is_print_(is_print),
  status_(x)
{
  // The best performance is usually achieved using
  // a sieve array size that matches your CPU's L1
  // data cache size (per core) or that is slightly
  // larger than your L1 cache size but smaller than
  // your L2 cache size (per core). Also, the
  // segment_size must be >= sqrt(sieve_limit).
  int64_t sieve_bytes = 128 << 10;
  int64_t numbers_per_byte = 30;
  int64_t sqrt_limit = isqrt(sieve_limit);
  max_size_ = max(sieve_bytes * numbers_per_byte, sqrt_limit);

  // When a single thread is used (and printing
  // is disabled) we can set segment_size to
  // its maximum size as load balancing is only
  // useful for multi-threading.
  if (threads == 1 &&
      !is_print)
  {
    segment_size_ = max_size_;
    segments_ = 100;
  }
  else
  {
    // Start with a tiny segment size of x^(1/4) as
    // most special leaves are in the first few
    // segments and as we need to ensure that all
    // threads are assigned an equal amount of work.
    segment_size_ = isqrt(isqrt(x));
    segments_ = 1;
  }

  int64_t min_size = 1 << 9;
  segment_size_ = max(min_size, segment_size_);
  segment_size_ = Sieve::get_segment_size(segment_size_);
}

maxint_t LoadBalancerS2::get_sum() const
{
  return sum_;
}

bool LoadBalancerS2::get_work(ThreadSettings& thread)
{
  LockGuard lockGuard(lock_);
  sum_ += thread.sum;

  if (is_print_)
  {
    uint64_t dist = thread.segments * thread.segment_size;
    uint64_t high = thread.low + dist;
    status_.print(high, sieve_limit_, sum_, sum_approx_);
  }

  update_load_balancing(thread);

  thread.low = low_;
  thread.segments = segments_;
  thread.segment_size = segment_size_;
  thread.sum = 0;
  thread.secs = 0;
  thread.init_secs = 0;

  low_ += segments_ * segment_size_;
  bool is_work = thread.low < sieve_limit_;

  return is_work;
}

void LoadBalancerS2::update_load_balancing(const ThreadSettings& thread)
{
  if (thread.low > max_low_)
  {
    max_low_ = thread.low;
    segments_ = thread.segments;

    // We only start increasing the segment_size and segments
    // per thread once the first special leaves have been
    // found. Near the start there is a very large number of
    // leaves and we don't want a single thread to compute
    // them all by himself (which would cause scaling issues).
    if (sum_ == 0)
      return;

    // Slowly increase the segment size until it reaches
    // sqrt(sieve_limit). Most special leaves are located
    // around y, hence we need to be careful to not assign too
    // much work to a single thread in this region.
    if (segment_size_ < max_size_)
      update_segment_size();
    else
      update_number_of_segments(thread);
  }
}

/// Slowly increase segment_size until it reaches sqrt(sieve_limit)
void LoadBalancerS2::update_segment_size()
{
  segment_size_ += segment_size_ / 16;
  segment_size_ = min(segment_size_, max_size_);
  segment_size_ = Sieve::get_segment_size(segment_size_);
}

/// Increase or decrease the number of segments per thread
/// based on the remaining runtime.
///
void LoadBalancerS2::update_number_of_segments(const ThreadSettings& thread)
{
  // Near the end it is important that threads run only for
  // a short amount of time in order to ensure that all
  // threads finish nearly at the same time. Since the
  // remaining time is just a rough estimation we want to be
  // very conservative so we divide the remaining time by 3.
  double rem_secs = remaining_secs() / 3;

  // If the previous thread runtime is larger than the
  // estimated remaining time the factor that we calculate
  // below will be < 1 and we will reduce the number of
  // segments per thread. Otherwise if the factor > 1 we
  // will increase the number of segments per thread.
  double min_secs = 0.001;
  double divider = max(min_secs, thread.secs);
  double factor = rem_secs / divider;

  // For small and medium computations the thread runtime
  // should be about 5000x the thread initialization time.
  // However for very large computations we want to further
  // reduce the thread runtimes in order to increase the
  // backup frequency. If the thread runtime is > 6 hours
  // we reduce the thread runtime to about 50x the thread
  // initialization time.
  double init_secs = max(min_secs, thread.init_secs);
  double init_factor = in_between(50, (3600 * 6) / init_secs, 5000);

  // Reduce the thread runtime if it is much larger than
  // its initialization time. This increases the number of
  // backups without deteriorating performance as we make
  // sure that the thread runtime is still much larger than
  // the thread initialization time.
  if (thread.secs > min_secs &&
      thread.secs > thread.init_secs * init_factor)
  {
    double old = factor;
    double next_runtime = thread.init_secs * init_factor;
    factor = next_runtime / thread.secs;
    factor = min(factor, old);
  }

  // Near the end when the remaining time goes close to 0
  // the load balancer tends to reduce the number of
  // segments per thread also close to 0 which is very bad
  // for performance. The condition below fixes this issue
  // and ensures that the thread runtime is always at
  // least 20x the thread initialization time.
  if (thread.secs > 0 &&
      thread.secs * factor < thread.init_secs * 20)
  {
    double next_runtime = thread.init_secs * 20;
    double current_runtime = thread.secs;
    factor = next_runtime / current_runtime;
  }

  // Since the distribution of the special leaves is highly
  // skewed (at the beginning) we want to increase the
  // number of segments per thread very slowly. Because if
  // the previously sieved interval contained no special
  // leaves but the next interval contains many special
  // leaves then sieving the next interval might take orders
  // of magnitude more time even if the interval size is
  // identical.
  factor = in_between(0.5, factor, 2.0);
  double next_runtime = thread.secs * factor;

  if (next_runtime < min_secs)
    segments_ *= 2;
  else
  {
    double new_segments = std::round(segments_ * factor);
    segments_ = (int64_t) new_segments;
    segments_ = max(segments_, 1);
  }
}

/// Remaining seconds till finished
double LoadBalancerS2::remaining_secs() const
{
  double percent = status_.getPercent(low_, sieve_limit_, sum_, sum_approx_);
  percent = in_between(10, percent, 100);
  double total_secs = get_time() - time_;
  double secs = total_secs * (100 / percent) - total_secs;
  return secs;
}

} // namespace