Many of the very simple algorithms are done by a good compiler, more complex ones generally are not. It is pretty easy to turn these into clean, generalized functions using templates in C++ and std::numeric_limits. I have a substantial library of generalized algorithms constructed from bit-twiddling primitives that does not use any macros.
The value of these examples is that if you understand the underlying mechanisms behind them you can use those building blocks to construct even more complex (and extremely fast) algorithms than demonstrated at the link. Complex, high-level algorithms can be implemented using these bit hacks once you wrap your head around what they are actually doing. The caveat is that the code will be opaque for programmers that are not fluent in bit-hacking.
For most applications you won't see much performance benefit because these are micro-optimizations. If you have a small kernel that is being executed a hundred thousand or million times per second then algorithms constructed this way can be a substantial performance optimization (easily integer factor speedup, I frequently see 10x for components).
Algorithms built on bit-twiddling primitives tend to have two properties that make them particularly efficient on modern processors. First, they make very good use of superscalar CPUs, putting the parallel ALUs to work. Second, they often take branching algorithms (e.g. small tight loops, ?: operator, if statements) and convert them into branchless algorithms. If you are doing performance and latency sensitive code, this method of building algorithms is worth learning. For everyone else, it is a neat bit of computer science arcana that really delves into the nature of integers.
Comments
Many of the very simple algorithms are done by a good compiler, more complex ones generally are not. It is pretty easy to turn these into clean, generalized functions using templates in C++ and std::numeric_limits. I have a substantial library of generalized algorithms constructed from bit-twiddling primitives that does not use any macros.
The value of these examples is that if you understand the underlying mechanisms behind them you can use those building blocks to construct even more complex (and extremely fast) algorithms than demonstrated at the link. Complex, high-level algorithms can be implemented using these bit hacks once you wrap your head around what they are actually doing. The caveat is that the code will be opaque for programmers that are not fluent in bit-hacking.
For most applications you won't see much performance benefit because these are micro-optimizations. If you have a small kernel that is being executed a hundred thousand or million times per second then algorithms constructed this way can be a substantial performance optimization (easily integer factor speedup, I frequently see 10x for components).
Algorithms built on bit-twiddling primitives tend to have two properties that make them particularly efficient on modern processors. First, they make very good use of superscalar CPUs, putting the parallel ALUs to work. Second, they often take branching algorithms (e.g. small tight loops, ?: operator, if statements) and convert them into branchless algorithms. If you are doing performance and latency sensitive code, this method of building algorithms is worth learning. For everyone else, it is a neat bit of computer science arcana that really delves into the nature of integers.