The Shape of Code

What will be the big issues in compiler writing in the next decade? Compilers sit between languages and hardware, with the hardware side usually providing the economic incentive.

Before we set off to follow the money, what about the side that developers prefer to talk about. The last decade has not seen any convergence to a very small number of commonly used languages, if anything there seems to have been a divergence with more languages in widespread use. I will not attempt to predict whether there will be a new (in the sense of previously limited to a few research projects) concept that is widely integrated and used in many languages (i.e., the integrating of object-oriented features into languages in the 90s).

Where is hardware going?

• Moore’s law stops being followed. Moore’s law is an economic one that has a number of technical consequences (e.g., less power consumed and until recently increasing clock rates). Will the x86 architecture evolution dramatically slow down once processor manufacturers are no longer able to cram more transistors onto the same amount of chip real estate? Perhaps processor designers will start looking to compiler writers to suggest functionality that could be made use of by compilers to generate more optimal code. To date, my experience of processor designers is that they look to Moore’s law to get a ‘free’ performance boost.

  There are a number of things a compiler code tell the processor, such as when a read or write to a cache line is the last one that will occur for a long time (enabling that line to be moved to the top of the reuse list).

• Not plugged into the mains. When I made a living writing optimizers, the only two optimizations choices were code size and performance. There are a surprising number of functional areas in which a compiler, given processor support, can potentially generate code that consumes less power. More on this issue in a later post.
• More than one processor. Figuring out how to distribute a program across multiple, loosely coupled, processors remains a difficult research topic. If anybody ever comes up with a solution to this problem, it might make more commercial sense for them to keep it secret, selling a compiling service rather than selling compilers.
• Application Specific Instruction-set Processors. Most processors in embedded systems only ever run a single program. The idea of each program being executed on a processor optimized to its requirements sounds seductive. At the moment the economics are such that it is cheaper to take an existing, very low cost, processor and shoe-horn the application onto it. If the economics change, the compiler used for each processor is likely to be automatically generated.

Enough of the hardware, this site is supposed to be about code:

• New implementation techniques. These include GLR parsing and genetic algorithms to improve the generated code quality. The general availability of development machines containing more than 4G of memory will make it worthwhile for compiler writers to implement more whole program optimizations (which are currently being hemmed in by storage limits)
• gcc will continue its rise to world domination. The main force at work here is not the quality of gcc, but the disappearance of the competition. Compiler writing is not a big bucks business, and compiler companies are regularly bought up by much larger hardware outfits looking to gain some edge. A few years go by, plans change, the compiler group are not making enough profit to warrant the time being spent on them by upper management, and they are closed down. One less compiler vendor and a bunch of developers are forced to migrate to another compiler, which may or may not be gcc.
• Figuring out what the developer meant to write based on what they actually wrote, and some mental model of software developers, is my own research interest. This is somewhat leading edge stuff, in other words, nothing major has been achieved so far. Knowledge of developer intent looks like it will open the door to whole classes of new optimization techniques.