During an undergraduate computer science degree, you’ll generally produce two sorts of code: very well-organized and aesthetically pleasing code which you’ll never touch after the assignment has been submitted, and awkward balls of mud which you’ll never touch after the assignment has been submitted. In industry it is far more common to encounter the latter and without the saving grace of disposability. The C language in particular easily lends itself to the production of dense, incomprehensible code. In this talk, I’m going to unravel two different snippets: the notorious “Duff’s device”, and a rather hairy mechanism for determining how many bits are set in an integer. In doing so, I hope to demonstrate both some techniques for breaking down poorly-understood code and enforce a healthy fear of unnecessarily complicated code even if it’s only a few lines long. Delivered for the Acadia Computer Science Society on 2016-11-25.

1. In the Name of
Performance
Sam Coleman

2. Who am I?

3. Who am I?

4. What is this not?
• Not about overall architecture

5. What is this not?
• Not about rescuing an entire codebase

6. What is this, then?
• Let’s look at something gross
• Let’s understand it
• Let’s never do it unless it needs to be done
• …“Performance”

7. Duff’s Device
• Live coding
• Please excuse the mess

8. Duff’s Device
• Why?
• Don’t do this.
• …unless you have to.
• memcpy available almost everywhere.

9. Bit Counting
• aka “population count”, aka “Hamming Weight”

10. But First, Bit Operations
• Bitwise: &, >>
• Masking: “covering up” bits we don’t care about
h g f e d c b a
& 0 0 1 1 1 1 0 0
0 0 f e d c 0 0

11. Bit Counting
• Live coding

12. Bit Counting
h g f e d c b a
- h g f e d c b
= h (g ^ h) f (e ^ f) d (c ^ d) b (a ^ b)
• The left column retains its original value.
• The right column is “on” only if either d or c were on.
• So across both columns, possible results are “10”, “01”, or “00”.
• …you may recognize these as “2”, “1”, or “0”.

13. Bit Counting
+
h g f e d c b a
h g d c

14. Bit Counting
• Sum of two 2-bit numbers can require 3 bits
• Need to clean (mask) the input so we know which
bits of output are relevant
• Result is clean, 4-bit integers
+
h g f e d c b a
i h g e d c

15. Bit Counting
• Our “4-bit” inputs will only have up to 3 bits in use
(to store “4”) so the sum will take at most 4 bits
• Only need to mask the output to get a clean, 8-bit
result – saves an operation vs. masking both inputs
+
p o n m l k j i h g f e d c b a
p o n m h g f e

16. Bit Counting
- - - - p o n m - - - - l k j i - - - - h g f e - - - - d c b a
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1
- - - - p o n m - - - - l k j i - - - - h g f e - - - - d c b a
- - - - l k j i - - - - h g f e - - - - d c b a
- - - - h g f e - - - - d c b a
- - - - d c b a
… >> 24

17. Bit Counting
• Why?
• Don’t do this.
• …unless you have to.
• __builtin_popcount available almost everywhere.

18. Concluding Remarks
• Old code can be a pain
• Embedded code can be a pain
• Progress can also be pain
• Boyscout rule: leave the campground cleaner than
you found it.
• Caveat: Don’t clean the campground without
understanding it!

19. ?