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PHiPAC

 

By analyzing the microarchitectures of a range of machines, such as workstations and microprocessor-based SMP and MPP nodes, and the output of their ANSI C compilers, we derived a set of guidelines that help us attain high performance across a range of machine and compiler combinations [BAD tex2html_wrap_inline1913 96].

From our analysis of various ANSI C compilers, we determined we could usually rely on reasonable register allocation, instruction selection, and instruction scheduling. More sophisticated compiler optimizations, however, including pointer alias disambiguation, register and cache blocking, loop unrolling, and software pipelining, were either not performed or not very effective at producing the highest quality code.

Although it would be possible to use another target language, we chose ANSI C because it provides a low-level, yet portable, interface to machine resources, and compilers are widely available. One problem with our use of C is that we must explicitly work around pointer aliasing as described below. In practice, this has not limited our ability to extract near-peak performance.

We emphasize that for both microarchitectures and compilers we are determining a lowest common denominator. Some microarchitectures or compilers will have superior characteristics in certain attributes, but, if we code assuming these exist, performance will suffer on systems where they do not. Conversely, coding for the lowest common denominator should not adversely affect performance on more capable platforms.

For example, some machines can fold a pointer update into a load instruction while others require a separate add. Coding for the lowest common denominator dictates replacing pointer updates with base plus constant offset addressing where possible. In addition, while some production compilers have sophisticated loop unrolling and software pipelining algorithms, many do not. Our search strategy (Section 4) empirically evaluates several levels of explicit loop unrolling and depths of software pipelining. While a naive compiler might benefit from code with explicit loop unrolling or software pipelining, a more sophisticated compiler might perform better without either.




next up previous
Next: PHiPAC Coding Guidelines Up: Optimizing Matrix Multiply using Previous: Introduction

Richard Vuduc
Tue Nov 18 15:58:12 PST 1997