Greetings.

This week, some more content from Implementing QuantLib. I’ll look at some classes for linear algebra.

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And now, arrays and matrices.

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### Linear algebra

I don’t have a lot to write about the current implementation of the Array and Matrix classes, shown in the following listing.

Their interface is what you would expect: constructors and assignment operators, element access (the Array class provides the a[i] syntax; the Matrix class provides both m[i][j] and m(i,j), because we aim to please), a bunch of arithmetic operators, all working element by element as usual (it always bothered me that a*b returns the element-wise product and not the dot product, but I seem to be alone among programmers), and a few utilities. There are no methods for resizing, or for other operations suited for containers, because this classes are not meant to be used as such; they’re mathematical utilities. Storage is provided by a simple scoped_ptr, managing the lifetime of the underlying memory.

In the case of Array, we also provide a few functions such as Abs, Log and their like; being good citizens, we’re not overloading the corresponding functions in namespace std because that’s forbidden by the standard. More complex functionality (such as matricial square root, or various decompositions) can be found in separate modules.

In short, a more or less straightforward implementation of arrays and matrices. The one thing which is not obvious is the presence of the Disposable class template, which I’ll describe in more detail in a further section of this appendix; for the time being, let me just say that it’s a pre-C++11 attempt at move semantics.

The idea was to try and reduce the abstraction penalty. Operator overloading is very convenient—after all, c = a+b is much easier to read than understand than add(a,b,c)—but doesn’t come for free: declaring addition as

means that the operator must create and return a new Array instance, that is, must allocate and possibly copy its memory. When the number of operations increases, so does the overhead.

In the first versions of the library, we tried to mitigate the problem by using expression templates. The idea (that I will only describe very roughly, so I suggest you read Veldhuizen, 2000 [1] for details) is that operators don’t return an array, but some kind of parse tree holding references to the terms of the expression; so, for instance, 2*a+b won’t actually perform any calculation but only create a small structure with the relevant information. It is only when assigned that the expression is unfolded; and at that point, the compiler would examine the whole thing and generate a single loop that both calculates the result and copies it into the array being assigned.

The technique is still relevant today (possibly even more so, given the progress in compiler technology) but we abandoned it after a few years. It was difficult to read and maintain (compare the current declaration of operator+ with

for a taste of what the code was like) and not all compilers were able to process it, forcing us to maintain both expression templates and the simpler implementation; therefore, when the C++ community started talking of move semantics and some ideas for implementations began to appear, we took the hint and switched to Disposable.

As I said, compilers progressed a lot during these years; nowadays, I’m guessing that all of them would support an expression-template implementation, and the technique itself has probably improved. However, if I were to write the code today (or if I started to change things) the question might be whether to write classes such as Array or Matrix at all. At the very least, I’d consider implementing them in terms of std::valarray, which is supposed to provide facilities for just such a task; but in the end, I’d probably go for some existing library such as uBLAS, which is available in Boost, is written by actual experts in numerical code, and that we already use in some parts of the library for specialized calculations.

#### Bibliography

[1] T. Veldhuizen, Techniques for Scientific C++. Indiana University Computer Science Technical Report TR542, 2000.