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//          Copyright Oliver Kowalke 2016.// Distributed under the Boost Software License, Version 1.0.//    (See accompanying file LICENSE_1_0.txt or copy at//          http://www.boost.org/LICENSE_1_0.txt)#ifndef BOOST_FIBERS_SPINLOCK_TTAS_H#define BOOST_FIBERS_SPINLOCK_TTAS_H#include <atomic>#include <chrono>#include <cmath>#include <random>#include <thread>#include <boost/fiber/detail/config.hpp>#include <boost/fiber/detail/cpu_relax.hpp>#include <boost/fiber/detail/spinlock_status.hpp>// based on informations from:// https://software.intel.com/en-us/articles/benefitting-power-and-performance-sleep-loops// https://software.intel.com/en-us/articles/long-duration-spin-wait-loops-on-hyper-threading-technology-enabled-intel-processorsnamespace boost {namespace fibers {namespace detail {class spinlock_ttas {private:    template< typename FBSplk >    friend class spinlock_rtm;    std::atomic< spinlock_status >              state_{ spinlock_status::unlocked };public:    spinlock_ttas() = default;    spinlock_ttas( spinlock_ttas const&) = delete;    spinlock_ttas & operator=( spinlock_ttas const&) = delete;    void lock() noexcept {        static thread_local std::minstd_rand generator{ std::random_device{}() };        std::size_t collisions = 0 ;        for (;;) {            // avoid using multiple pause instructions for a delay of a specific cycle count            // the delay of cpu_relax() (pause on Intel) depends on the processor family            // the cycle count can not guaranteed from one system to the next            // -> check the shared variable 'state_' in between each cpu_relax() to prevent            //    unnecessarily long delays on some systems            std::size_t retries = 0;            // test shared variable 'status_'            // first access to 'state_' -> chache miss            // sucessive acccess to 'state_' -> cache hit            // if 'state_' was released by other fiber            // cached 'state_' is invalidated -> cache miss            while ( spinlock_status::locked == state_.load( std::memory_order_relaxed) ) {#if !defined(BOOST_FIBERS_SPIN_SINGLE_CORE)                if ( BOOST_FIBERS_SPIN_BEFORE_SLEEP0 > retries) {                    ++retries;                    // give CPU a hint that this thread is in a "spin-wait" loop                    // delays the next instruction's execution for a finite period of time (depends on processor family)                    // the CPU is not under demand, parts of the pipeline are no longer being used                    // -> reduces the power consumed by the CPU                    // -> prevent pipeline stalls                    cpu_relax();                } else if ( BOOST_FIBERS_SPIN_BEFORE_YIELD > retries) {                    // std::this_thread::sleep_for( 0us) has a fairly long instruction path length,                    // combined with an expensive ring3 to ring 0 transition costing about 1000 cycles                    // std::this_thread::sleep_for( 0us) lets give up this_thread the remaining part of its time slice                    // if and only if a thread of equal or greater priority is ready to run                    static constexpr std::chrono::microseconds us0{ 0 };                    std::this_thread::sleep_for( us0);                } else {                    // std::this_thread::yield() allows this_thread to give up the remaining part of its time slice,                    // but only to another thread on the same processor                    // instead of constant checking, a thread only checks if no other useful work is pending                    std::this_thread::yield();                }#else                std::this_thread::yield();#endif            }            // test-and-set shared variable 'status_'            // everytime 'status_' is signaled over the bus, even if the test failes            if ( spinlock_status::locked == state_.exchange( spinlock_status::locked, std::memory_order_acquire) ) {                // spinlock now contended                // utilize 'Binary Exponential Backoff' algorithm                // linear_congruential_engine is a random number engine based on Linear congruential generator (LCG)                std::uniform_int_distribution< std::size_t > distribution{                    0, static_cast< std::size_t >( 1) << (std::min)(collisions, static_cast< std::size_t >( BOOST_FIBERS_CONTENTION_WINDOW_THRESHOLD)) };                const std::size_t z = distribution( generator);                ++collisions;                for ( std::size_t i = 0; i < z; ++i) {                    // -> reduces the power consumed by the CPU                    // -> prevent pipeline stalls                    cpu_relax();                }            } else {                // success, thread has acquired the lock                break;            }        }    }    bool try_lock() noexcept {        return spinlock_status::unlocked == state_.exchange( spinlock_status::locked, std::memory_order_acquire);    }    void unlock() noexcept {        state_.store( spinlock_status::unlocked, std::memory_order_release);    }};}}}#endif // BOOST_FIBERS_SPINLOCK_TTAS_H
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