Philipp Claßen Philipp Claßen - 1 month ago 11
C++ Question

Understanding std::hardware_destructive_interference_size and std::hardware_constructive_interference_size

C++17 added

and
std::hardware_constructive_interference_size
. First, I thought it is just a portable way to get the size of a L1 cache line but that is an oversimplification.

Questions:


  • How are these constants related to the L1 cache line size?

  • Is there a good example that demonstrates their use cases?

  • Both are defined
    static constexpr
    . Is that not a problem if you build a binary and execute it on other machines with different cache line sizes? How can it protect against false sharing in that scenario when you are not certain on which machine your code will be running?


Answer

The intent of these constants is indeed to get the cache-line size. The best place to read about the rationale for them is in the proposal itself:

http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2016/p0154r1.html

I'll quote a snippet of the rationale here for ease-of-reading:

[...] the granularity of memory that does not interfere (to the first-order) [is] commonly referred to as the cache-line size.

Uses of cache-line size fall into two broad categories:

  • Avoiding destructive interference (false-sharing) between objects with temporally disjoint runtime access patterns from different threads.
  • Promoting constructive interference (true-sharing) between objects which have temporally local runtime access patterns.

The most sigificant issue with this useful implementation quantity is the questionable portability of the methods used in current practice to determine its value, despite their pervasiveness and popularity as a group. [...]

We aim to contribute a modest invention for this cause, abstractions for this quantity that can be conservatively defined for given purposes by implementations:

  • Destructive interference size: a number that’s suitable as an offset between two objects to likely avoid false-sharing due to different runtime access patterns from different threads.
  • Constructive interference size: a number that’s suitable as a limit on two objects’ combined memory footprint size and base alignment to likely promote true-sharing between them.

In both cases these values are provided on a quality of implementation basis, purely as hints that are likely to improve performance. These are ideal portable values to use with the alignas() keyword, for which there currently exists nearly no standard-supported portable uses.


"How are these constants related to the L1 cache line size?"

In theory, pretty directly.

Assume the compiler knows exactly what architecture you'll be running on - then these would almost certainly give you the L1 cache-line size precisely. (As noted later, this is a big assumption.)

For what it's worth, I would almost always expect these values to be the same. I believe the only reason they are declared separately is for completeness. (That said, maybe a compiler wants to estimate L2 cache-line size instead of L1 cache-line size for constructive interference; I don't know if this would actually be useful, though.)


"Is there a good example that demonstrates their use cases?"

At the bottom of this answer I've attached a long benchmark program that demonstrates false-sharing and true-sharing.

It demonstrates false-sharing by allocating an array of int wrappers: in one case multiple elements fit in the L1 cache-line, and in the other a single element takes up the L1 cache-line. In a tight loop a single, a fixed element is chosen from the array and updated repeatedly.

It demonstrates true-sharing by allocating a single pair of ints in a wrapper: in one case, the two ints within the pair do not fit in L1 cache-line size together, and in the other they do. In a tight loop, each element of the pair is updated repeatedly.

Note that the code for accessing the object under test does not change; the only difference is the layout and alignment of the objects themselves.

I don't have a C++17 compiler (and assume most people currently don't either), so I've replaced the constants in question with my own. You need to update these values to be accurate on your machine. That said, 64 bytes is probably the correct value on typical modern desktop hardware (at the time of writing).

Warning: the test will use all cores on your machines, and allocate ~256MB of memory. Don't forget to compile with optimizations!

On my machine, the output is:

Hardware concurrency: 16
sizeof(naive_int): 4
alignof(naive_int): 4
sizeof(cache_int): 64
alignof(cache_int): 64
sizeof(bad_pair): 72
alignof(bad_pair): 4
sizeof(good_pair): 8
alignof(good_pair): 4
Running naive_int test.
Average time: 0.0873625 seconds, useless result: 3291773
Running cache_int test.
Average time: 0.024724 seconds, useless result: 3286020
Running bad_pair test.
Average time: 0.308667 seconds, useless result: 6396272
Running good_pair test.
Average time: 0.174936 seconds, useless result: 6668457

I get ~3.5x speedup by avoiding false-sharing, and ~1.7x speedup by ensuring true-sharing.


"Both are defined static constexpr. Is that not a problem if you build a binary and execute it on other machines with different cache line sizes? How can it protect against false sharing in that scenario when you are not certain on which machine your code will be running?"

This will indeed be a problem. These constants are not guaranteed to map to any cache-line size on the target machine in particular, but are intended to be the best approximation the compiler can muster up.

This is noted in the proposal, and in the appendix they give an example of how some libraries try to detect cache-line size at compile time based on various environmental hints and macros. You are guaranteed that this value is at least alignof(max_align_t), which is an obvious lower bound.

In other words, this value should be used as your fallback case; you are free to define a precise value if you know it, e.g.:

constexpr std::size_t cache_line_size() {
#ifdef KNOWN_L1_CACHE_LINE_SIZE
  return KNOWN_L1_CACHE_LINE_SIZE;
#else
  return std::hardware_destructive_interference_size;
#endif
}

During compilation, if you want to assume a cache-line size just define KNOWN_L1_CACHE_LINE_SIZE.

Hope this helps!

Benchmark program:

#include <chrono>
#include <condition_variable>
#include <cstddef>
#include <functional>
#include <future>
#include <iostream>
#include <random>
#include <thread>
#include <vector>

// !!! YOU MUST UPDATE THIS TO BE ACCURATE !!!
constexpr std::size_t hardware_destructive_interference_size = 64;

// !!! YOU MUST UPDATE THIS TO BE ACCURATE !!!
constexpr std::size_t hardware_constructive_interference_size = 64;

constexpr unsigned kTimingTrialsToComputeAverage = 100;
constexpr unsigned kInnerLoopTrials = 1000000;

typedef unsigned useless_result_t;
typedef double elapsed_secs_t;

//////// CODE TO BE SAMPLED:

// wraps an int, default alignment allows false-sharing
struct naive_int {
    int value;
};
static_assert(alignof(naive_int) < hardware_destructive_interference_size, "");

// wraps an int, cache alignment prevents false-sharing
struct cache_int {
    alignas(hardware_destructive_interference_size) int value;
};
static_assert(alignof(cache_int) == hardware_destructive_interference_size, "");

// wraps a pair of int, purposefully pushes them too far apart for true-sharing
struct bad_pair {
    int first;
    char padding[hardware_constructive_interference_size];
    int second;
};
static_assert(sizeof(bad_pair) > hardware_constructive_interference_size, "");

// wraps a pair of int, ensures they fit nicely together for true-sharing
struct good_pair {
    int first;
    int second;
};
static_assert(sizeof(good_pair) <= hardware_constructive_interference_size, "");

// accesses a specific array element many times
template <typename T, typename Latch>
useless_result_t sample_array_threadfunc(
    Latch& latch,
    unsigned thread_index,
    T& vec) {
    // prepare for computation
    std::random_device rd;
    std::mt19937 mt{ rd() };
    std::uniform_int_distribution<int> dist{ 0, 4096 };

    auto& element = vec[vec.size() / 2 + thread_index];

    latch.count_down_and_wait();

    // compute
    for (unsigned trial = 0; trial != kInnerLoopTrials; ++trial) {
        element.value = dist(mt);
    }

    return static_cast<useless_result_t>(element.value);
}

// accesses a pair's elements many times
template <typename T, typename Latch>
useless_result_t sample_pair_threadfunc(
    Latch& latch,
    unsigned thread_index,
    T& pair) {
    // prepare for computation
    std::random_device rd;
    std::mt19937 mt{ rd() };
    std::uniform_int_distribution<int> dist{ 0, 4096 };

    latch.count_down_and_wait();

    // compute
    for (unsigned trial = 0; trial != kInnerLoopTrials; ++trial) {
        pair.first = dist(mt);
        pair.second = dist(mt);
    }

    return static_cast<useless_result_t>(pair.first) +
        static_cast<useless_result_t>(pair.second);
}

//////// UTILITIES:

// utility: allow threads to wait until everyone is ready
class threadlatch {
public:
    explicit threadlatch(const std::size_t count) :
        count_{ count }
    {}

    void count_down_and_wait() {
        std::unique_lock<std::mutex> lock{ mutex_ };
        if (--count_ == 0) {
            cv_.notify_all();
        }
        else {
            cv_.wait(lock, [&] { return count_ == 0; });
        }
    }

private:
    std::mutex mutex_;
    std::condition_variable cv_;
    std::size_t count_;
};

// utility: runs a given function in N threads
std::tuple<useless_result_t, elapsed_secs_t> run_threads(
    const std::function<useless_result_t(threadlatch&, unsigned)>& func,
    const unsigned num_threads) {
    threadlatch latch{ num_threads + 1 };

    std::vector<std::future<unsigned>> futures;
    std::vector<std::thread> threads;
    for (unsigned thread_index = 0; thread_index != num_threads; ++thread_index) {
        std::packaged_task<unsigned()> task{
            std::bind(func, std::ref(latch), thread_index)
        };

        futures.push_back(task.get_future());
        threads.push_back(std::thread(std::move(task)));
    }

    const auto starttime = std::chrono::high_resolution_clock::now();

    latch.count_down_and_wait();
    for (auto& thread : threads) {
        thread.join();
    }

    const auto endtime = std::chrono::high_resolution_clock::now();
    const auto elapsed = std::chrono::duration_cast<
        std::chrono::duration<double>>(
            endtime - starttime
            ).count();

    unsigned result = 0;
    for (auto& future : futures) {
        result += future.get();
    }

    return std::make_tuple(result, elapsed);
}

// utility: sample the time it takes to run func on N threads
void run_tests(
    const std::function<useless_result_t(threadlatch&, unsigned)>& func,
    const unsigned num_threads) {
    useless_result_t final_result = 0;
    double avgtime = 0.0;
    for (unsigned trial = 0; trial != kTimingTrialsToComputeAverage; ++trial) {
        const auto result_and_elapsed = run_threads(func, num_threads);
        const auto result = std::get<useless_result_t>(result_and_elapsed);
        const auto elapsed = std::get<elapsed_secs_t>(result_and_elapsed);

        final_result += result;
        avgtime = (avgtime * trial + elapsed) / (trial + 1);
    }

    std::cout
        << "Average time: " << avgtime
        << " seconds, useless result: " << final_result
        << std::endl;
}

int main() {
    const auto cores = std::thread::hardware_concurrency();
    std::cout << "Hardware concurrency: " << cores << std::endl;

    std::cout << "sizeof(naive_int): " << sizeof(naive_int) << std::endl;
    std::cout << "alignof(naive_int): " << alignof(naive_int) << std::endl;
    std::cout << "sizeof(cache_int): " << sizeof(cache_int) << std::endl;
    std::cout << "alignof(cache_int): " << alignof(cache_int) << std::endl;
    std::cout << "sizeof(bad_pair): " << sizeof(bad_pair) << std::endl;
    std::cout << "alignof(bad_pair): " << alignof(bad_pair) << std::endl;
    std::cout << "sizeof(good_pair): " << sizeof(good_pair) << std::endl;
    std::cout << "alignof(good_pair): " << alignof(good_pair) << std::endl;

    {
        std::cout << "Running naive_int test." << std::endl;

        std::vector<naive_int> vec;
        vec.resize((1u << 28) / sizeof(naive_int));  // allocate 256 mibibytes

        run_tests([&](threadlatch& latch, unsigned thread_index) {
            return sample_array_threadfunc(latch, thread_index, vec);
        }, cores);
    }
    {
        std::cout << "Running cache_int test." << std::endl;

        std::vector<cache_int> vec;
        vec.resize((1u << 28) / sizeof(cache_int));  // allocate 256 mibibytes

        run_tests([&](threadlatch& latch, unsigned thread_index) {
            return sample_array_threadfunc(latch, thread_index, vec);
        }, cores);
    }
    {
        std::cout << "Running bad_pair test." << std::endl;

        bad_pair p;

        run_tests([&](threadlatch& latch, unsigned thread_index) {
            return sample_pair_threadfunc(latch, thread_index, p);
        }, cores);
    }
    {
        std::cout << "Running good_pair test." << std::endl;

        good_pair p;

        run_tests([&](threadlatch& latch, unsigned thread_index) {
            return sample_pair_threadfunc(latch, thread_index, p);
        }, cores);
    }
}