Efficiency of C# on Linux

This week I attended Mads Torgersen’s talk Why you should take another look at C#. Afterward I asked him about the efficiency of C# on Linux. When I last looked into it, it wasn’t good. A few years ago I asked someone on my team to try running some C# software on Linux using Mono. The code worked correctly, but it ran several times slower than on Windows.

Mads said that now with .NET Core, C# code runs about as fast on Linux as Windows. Maybe a few percent slower on Linux. Scott Hanselman joined the conversation and explained that with .NET Core, the same code runs on every platform. The Mono project duplicated the much of the functionality of the .NET framework, but it was an entirely independent implementation and not as efficient.

I had assumed the difference was due to compiler optimizations or lack thereof, but Scott and Mads said that the difference was mostly the code implementation. There are some compiler optimizations that are better on the Windows side, and so C# might run a little faster on Windows, but the performance is essentially the same on both platforms.

I could recommend C# to a client running Linux if there’s a 5% performance penalty, but a 500% performance penalty was a show-stopper. Now I’d consider using C# on a project where I need more performance than Python or R, but wanted to use something easier to work with than C++.

Years ago I developed software with the Microsoft stack, but I moved away from Microsoft tools when I quit doing the kind of software development the tools are geared for. So I don’t write C# much any more. It’s been about a year since I had a project where I needed to write C# code. But I like the C# language. You can tell that a lot of thought has gone into the design, and the tool support is great. Now that the performance is better on Linux I’d consider using it for numerical simulations.

Click to find out more about consulting for numerical computing

Leading digits and quadmath

My previous post looked at a problem that requires repeatedly finding the first digit of kn where k is a single digit but n may be on the order of millions or billions.

The most direct approach would be to first compute kn as a very large integer, then find it’s first digit. That approach is slow, and gets slower as n increases. A faster way is to look at the fractional part of log kn = n log k and see which digit it corresponds to.

If n is not terribly big, this can be done in ordinary precision. But when n is large, multiplying log k by n and taking the fractional part brings less significant digits into significance. So for very large n, you need extra precision. I first did this in Python using SymPy, then switched to C++ for more speed. There I used the quadmath library for gcc. (If n is big enough, even quadruple precision isn’t enough. An advantage to SymPy over quadmath is that the former has arbitrary precision. You could, for example, set the precision to be 10 more than the number of decimal places in n in order to retain 10 significant figures in the fractional part of n log k.)

The quadmath.h header file needs to be wrapped in an extern C declaration. Otherwise gcc will give you misleading error messages.

The 128-bit floating point type __float128 has twice as many bits as a double. The quadmath functions have the same name as their standard math.h counterparts, but with a q added on the end, such as log10q and fmodq below.

Here’s code for computing the leading digit of kn that illustrates using quadmath.

#include <cmath >
extern "C" {
#include <quadmath.h>

__float128 logs[11];

for (int i = 2; i  <= 10; i++)
    logs[i] = log10q(i + 0.0);

int first_digit(int base, long long exponent)
    __float128 t = fmodq(exponent*logs[base], 1.0);
    for (int i = 2; i  <= 10; i++)
        if (t  < logs[i])
            return i-1;

The code always returns because t is less than 1.

Caching the values of log10q saves repeated calls to a relatively expensive function. So does using the search at the bottom rather than computing powq(10, t).

The linear search at the end is more efficient than it may seem. First, it’s only search a list of length 9. Second, because of Benford’s law, the leading digits are searched in order of decreasing frequency, i.e. most inputs will cause first_digit to return early in the search.

When you compile code using quadmath, be sure to add -lquadmath to the compile command.

Related posts

C++ at Facebook

Andrei Alexandrescu said in a panel discussion last week that when he joined Facebook two years ago, maybe 90% of the programmers wrote PHP and 10% C++. Now there are roughly as many C++ programmers as PHP programmers.

One reason Facebook is shifting more work to C++ is to reduce operating costs such as power consumption per user.

Andrei’s remarks are about 24 minutes into this video.

C++ Renaissance

Dynamic language developers who are concerned about performance end up writing pieces of their applications in C++. So if you’re going to write C++ anyway, why not write your entire application in C++?

Library writers develop in C++ so that their users won’t have to. That makes a lot of sense. But if you’re developing your own application, not a library, maybe it would be better to write everything in C++ instead of wrapping C++ in something else.

A few years ago an immediate objection would be that C++ is hard to use. But with the advent of C++ 11, that’s not as true as it once was. C++ has gained many of the conveniences traditionally associated with other languages. (Update: for more on this theme, see Not Your Father’s C++.)

Dynamic languages are designed for programmer productivity[1] at the expense of efficiency. If you can afford that trade-off, and quite often you can, then don’t worry about C++. But if you’re using a dynamic language and C++, maybe it would be easier to just stick to C++. Of course the decision depends on many factors — how much of the application needs to be efficient, the size and skill of your team, etc. — but I suspect more projects will decide to do everything in C++ because of its new features.

* * *

[1] “Productivity” implicitly assumes productivity at a certain set of tasks. If your tasks fall into the set of things a language was designed to support, great. But a “productivity” language may not improve your productivity if you don’t meet the language’s intended profile.

More C++ posts

a < b < c

In Python, and in some other languages, the expression a < b < c is equivalent to a < b and b < c. For example, the following code outputs “not increasing.”

a, b, c = 3, 1, 2
if a < b < c:
    print "increasing"
    print "not increasing"

Now consider the analogous C code.

int a = 3, b = 1, c = 2;
if (a < b < c)
    printf( "increasingn" );
    printf("not increasingn");

This outputs “increasing”!

If you don’t know C, you’d expect the output to be “not increasing.” If you do know C, you might expect the code not to compile.

Here’s what’s going on. The code first asks whether a < b. This evaluates to 0 because a < b is false. Then it asks whether 0 < c, which is true.

If the code above were part of a C++ program, it would still compile and still produce the same result. However, the compiler would generate a warning for implicitly casting Boolean result to an integer.

Using C# like a scripting language

Clift Norris wrote a clever little batch file csrun.bat several years ago. I thought I’d posted it here, but apparently not. If you have a C# program in foo.cs, you can type csrun foo.cs to compile and run the program.

The batch file doesn’t do much at all, but it might change how you think about a C# program. The C# code is still compiled, but since the compilation step is hidden, it feels more like an interpreted language.

When someone says they like interpreted languages, maybe what they really mean is that they enjoy running code quickly without the overhead of starting up an IDE, compiling the code, navigating to the directory containing the compiled executable, etc. This has nothing to do with whether a language is compiled or interpreted.

@echo off
REM : Compile and run a C# source file.
REM : The C# compiler (csc.exe) must be in your PATH.
REM : The command line argument is expected to be something like foo.cs

if "%1"=="" goto USAGE

csc.exe /nologo /out:%1.exe  %1

%1.exe	%2  %3  %4  %5
goto EXIT

echo You must specify an argument representing the C# file you want to run.


This batch file does not set references; you’d need to modify it if you want to reference an assembly.

Update: CsharpRepl is a REPL (read-evaluate-print-loop) that lets you write C# at the command line as you would most scripting languages. CsharpRepl is part of Mono and works cross-platform. Thanks to MikeG in the comments.

Related post: Visual Studio 2010 is a pig

What most C++ programmers do

“Nobody knows what most C++ programmers do.” — Bjarne Stroustrup

The quote above came up in a discussion of C++ by Scott Meyers, Andrei Alexandrescu, and Herb Sutter. They argue that C++ is used in so many diverse applications that if someone starts a sentence with “Most C++ programmers …” he probably doesn’t know what he’s talking about.

Related post: The dark matter of programmers

A couple Python-like features in C++11

The new C++ standard includes a couple Python-like features that I ran across recently. There are other Python-like features in the new standard, but here I’ll discuss range-based for-loops and raw strings.
In Python you loop over lists rather than incrementing a loop counter variable. For example,

    for p in [2, 3, 5, 7, 11]:
        print p

Range-based for loops now let you do something similar in C++11:

    int primes[5] = {2, 3, 5, 7, 11};
    for (int &p : primes)
        cout << p << "n";

Also, Python has raw strings. If you preface a quoted string with R, the contents of the string is interpreted literally. For example,

    print "Hello\nworld"

will produce



    print R"Hello\nworld"

will produce


because the \n is no longer interpreted as a newline character but instead printed literally as two characters.

Raw strings in C++11 use R as well, but they also require a delimiter inside the quotation marks. For example,

    cout << R"(Hello\nworld)";

The C++ raw string syntax is a little harder to read than the Python counterpart since it requires parentheses. The advantage, however, is that such strings can contain double quotes since a double quote alone does not terminate the string. For example,

    cout << R"(Hello "world")";

would print

    Hello "world"

In Python this is unnecessary since single and double quotes are interchangeable; if you wanted double quotes inside your string, you’d use single quotes on the outside.

Note that raw strings in C++ require a capital R unlike Python that allows r or R.

The C++ features mentioned here are supported gcc 4.6.0. The MinGW version of gcc for Windows is available here. To use C++11 features in gcc, you must add the parameter -std=c++0x to the g++ command line. For example,

    g++ -std=c++0x hello.cpp

Visual Studio 2010 supports many of the new C++ features, but not the ones discussed here.

Related links:

Maybe C++ hasn’t jumped the shark after all

A couple years ago I wrote a blog post Has C++ jumped the shark? I wondered how many people would care about the new C++ standard by the time it came out. I doubted that it would matter much to me personally.

… if something is hard to do in C++, I just don’t use C++. I don’t see a new version of C++ changing my decisions about what language to use for various tasks.

The new standard is out now, and I find it more interesting that I thought I would have. I’d still rather not use C++ for tasks that are easier in another language I know, but sometimes I don’t have that option.

When I heard about plans to add lambdas and closures to C++ I commented here that “it seems odd to add these features to C++.”  Now I think lambdas (anonymous functions) and closures may be the most important new features for my use.

One of my favorite features in Python is the ability to define functions on the fly. If I’m writing a function and need to create a new function to pass as an argument, then I can define that function on the spot. By contrast, C++ has not let you define a function inside a function. Now you can.

(You still cannot define a named function inside a C++ function. However, you can create anonymous functions inside another function. If you save that anonymous function to a variable, then you’ve effectively created a named function.)

Here are a couple examples of how it can be very convenient to define little functions on the fly. First, optimization software typically provides methods for minimizing functions. If you want to maximize a f(x), you define a new function g(x) = -f(x) and minimize g. Second, root-finding software typically solves equations of the form f(x) = 0. If you want to solve f(x) = c, you create a new function g(x) = f(x) – c and find where g is zero. In both cases, the function g is so trivial that there’s no need to give it a name. And more importantly, you’d rather define this auxiliary function right where you need it than interrupt your context by defining it outside.

Anonymous functions can also have associated data obtained from the context where they’re defined. That’s called a closure because it encloses some context with the function. This is very often necessary in mathematical software development. For example, say you have a function of two variables f(x, y) and you want to integrate f with respect to x, holding y constant. You might then think of f as a function of one variable with one constant, but the compiler sees it as a function of two variables and will not let you pass it to an integration routine expecting a function of one variable. One way to solve this problem is to use function objects. This isn’t difficult, but it requires a lot of ceremony compared to using closures.

For specifics of how to use lambdas and closures in C++, see Ajay Vijayvargiya’s article Explicating the new C++ standard (C++0x), and its implementation in VC10.

More C++ posts