Using std::async for easy parallel computations

C++0x, the next major revision of C++, includes a number of new language and library facilities that I am greatly looking forward to, including a standard thread interface. Initially the agenda for C++0x had included facilities built on threads, such as a thread pool, but as part of the so-called 'Kona compromise' (named after the location of the committee meeting where the compromise was made) all but the most basic facilities were deferred for a later revision.

However there were many requests for a simple facility for creating an asynchronous function call, and a function for this, named std::async, was voted in at the last meeting. std::async is a rather blunt tool; it spawns a new thread (though wording is included which would allow an implementation to spawn threads in a fixed-size thread pool to eliminate thread creation overhead and reduce hardware oversubscription) and returns a "future" representing the return value of the function. A future is a placeholder for a value which can be passed around the program, and if and when the value is actually needed, it can be retrieved from the future; the get operation may block if the value has not yet been computed. In C++0x the future/promise system is primarily intended for use with threads, but there doesn't seem to be any reason a system for distributed RPC (ala E's Pluribus protocol) could not provide an interface using the same classes.

An operation which felt like easy low-hanging fruit for parallel invocation is RSA's decrypt/sign operation. Mathematically, when one signs a message using RSA, the message representation (usually a hash function output plus some specialized padding) is converted to an integer, and then raised to the power of d, the RSA private key, modulo another number. Both of these numbers are relatively large, typically 300 to 600 digits long. A well known trick, which takes advantage of the underlying structure of the numbers, allows one to instead compute two modular exponentiations, both using numbers about half the size of d, and combine them using the Chinese Remainder Theorem (thus this optimization is often called RSA-CRT). The two computations are both still quite intensive, and since they are independent it seemed reasonable to try computing them in parallel. Running one of the two exponentiations in a different thread showed an immediate doubling in speed for RSA signing on a multicore! Other mathematically intensive algorithms that offer some amount of parallel computation, including DSA and ElGamal, also showed nice improvements.

As std::async is not included in GCC 4.5, I wrote a simple clone of it. This version does not offer thread pooling or the option of telling the runtime to run the function on the same thread; it is mostly a 'proof of concept' version I'm using until GCC includes the real deal in libstdc++. Here is the code:

#include <future>
#include <thread>

template<typename F>
auto std_async(F f) -> std::unique_future<decltype(f())>
   typedef decltype(f()) result_type;
   std::packaged_task<result_type ()> task(std::move(f));
   std::unique_future<result_type> future = task.get_future();
   std::thread thread(std::move(task));
   return future;

The highly curious auto return type of std_async uses C++0x's new function declaration syntax; ordinarily there is no reason to use it but here we want to specify that the function returns a unique_future paramaterized by whatever it is that f returns. Since f can't be referred to until it has been mentioned as the name of an argument, the return value has to come after the parameter list.

Unlike the version of std::async that was finally voted in, std_async assumes its argument takes no arguments (one of the original proposals for std::async used a similar interface). This would be highly inconvenient except for the assistance of C++0x's lambdas, which allow us to pack everything together. For instance here is the code for RSA signing, which packages up one half of the computation in a 0-ary lambda function:

auto future_j1 = std_async([&]() { return powermod_d1_p(i); });
   BigInt j2 = powermod_d2_q(i);
   BigInt j1 = future_j1.get();
   // Now combine j1 and j2 using CRT

Using C++0x's std::bind instead of a lambda here should work as well, but I ran into problem with that in the 4.5 snapshot I'm using; the current implementation follows the TR1 style of requiring result_type typedefs which will not be necessary in C++0x thanks to decltype. Since the actual std::async can take an arbitrary number of arguments, the declaration of future_j1 will eventually change to simply:

auto future_j1 = std::async(powermod_d1_p, i);

The implementation of std_async may strike you as excessively C++0x-ish, for instance by using decltype instead of TR1's result_of metaprogramming function. Part of this is due to current limitations of GCC and/or libstdc++; the version of result_of in 4.5's libstdc++ does not understand lambda functions (C++0x's result_of is guaranteed to get this right, because it itself uses decltype, but apparently libstdc++ hasn't changed to use this yet).

Overall I'm pretty happy with C++0x as an evolution of C++98 for systems programming tasks. Though I am certainly interested to see how Thompson and Pike's Go works out; now that BitC is more or less dead after the departure of its designers to Microsoft, Go seems to be the only game in town in terms of new systems programming languages that might provide a compelling alternative to C++.