The C99 <stdint.h> header provides a plethora of type definition for platform-independent safe code: int_fast16_t, for example, provides an integer that plays well with the machine but has at least 16 bits. The int_fastxx_t and int_leastxx_t defines doesn’t guarantee a tight fit, they provide an machine-efficient fit. They find the fastest type of integer for that machine that respects the constraint.

But let’s take the problem the other way around: what about defines that gives you the smallest integer, not for the number of bits (because that’s trivial with intxx_t) but from the maximum value you need to represent?

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Lïtbørd (more than some assembly required)


As you may have noticed, a global pandemics got many of us working from home. While one can argue that you can do accounting from home, it’s a lot more complicated to teach from home. Pretty much everyone is trying to figure that one out. For my part, I decided that zoom and the virtual whiteboard is not very interesting. Like many, I decided to use a lightboard.

So, the problem is, where do you get a lightboard on short notice? Well, you can build one. Let’s see how:

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Evaluating polynomials


Evaluating polynomials is not a thing I do very often. When I do, it’s for interpolation and splines; and traditionally those are done with relatively low degree polynomials—cubic at most. There are a few rather simple tricks you can use to evaluate them efficiently, and we’ll have a look at them.

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Factorial Approximations


n! (and its logarithm) keep showing up in the analysis of algorithm. Unfortunately, it’s very often unwieldy, and we use approximations of n! (or \log n!) to simplify things. Let’s examine a few!

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How many bits?


In this quarantine week, let’s answer a (not that) simple question: how many bits do you need to encode sound and images with a satisfying dynamic range?

Let’s see what hypotheses are useful, and how we can use them to get a good idea on the number of bits needed.

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In one of the classes I teach, we end up writing assembly language programs. And while I explain the (sometimes very relative) benefits of writing assembly language, I use bubble sort as an example where even carefully crafted assembly language doesn’t mean much: it’s a bad algorithm to start with.


Except that it’s not quite true.

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Fast Exponentiation, revisited


Quite a while ago, I presented a fast exponentiation algorithm that uses the binary decomposition of the exponent n to perform O(\log_2 n) products to compute x^n.

While discussing this algorithm in class, a student asked a very interesting question: what’s special about base 2? Couldn’t we use another base? Well, yes, yes we can.

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Last week (at the time of writing, anyway), Ars Technica reported a serious bug in AMD’s implementation of rdrand, an instruction that helps you generate random numbers. Apparently, on (some) Ryzen 3000, 0xfff…ff is “random”.

I recently got an AMD Ryzen 9 3900x, and I wondered if I have the bug as well.

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(Sub)bit-fields (Coding with fractions of bits, Part II)


Last week, we used the 6×7×6 palette as an example of very simple fraction-of-a-bit coding1. However, we can generalize still a bit more to allow single field extraction and modification

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The 6×7×6 palette (Coding with fractions of bits, Part I)


Remember ye olde dayes when we had to be mindful of the so-called “web safe palette“? Once upon a time, screens could display 24-bits colors, but only 256 at a time in some “hi-res” modes. But that’s not what I’m going to tell you about: I’d rather tell you about the encoding of the palette, and about a somewhat better palette. And also about using fractions of bits for more efficient encodings.

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