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| Describe MorphoOptimizationProjectConsistentSerialAlgorithms here. |
Parent: MorphoOptimizationProject There are many reasons why source code compiled for and running on different platforms might not get the same result, even when single threaded. 1. Floating point - compiler might chose a different binary pattern for a decimal number (unlikely), order of evaluation (likely), precision (using double for some intermediate results), implementation of functions such as asin or sqrt. 1. Sorting algorithms - most sorting algorithms are not stable - items with equal keys may be sorted into either order. 1. Random number generators - these are obviously unstable. ''Platform'' here refers to a combination of hardware, compiler version, compiler switches, libraries, and operating systems. For our purposes we are mostly concerned with only changing the number of threads, which is discussed elsewhere [where?]. However we have seen differences between Linux and OSX caused by these kinds of issues, and we also see them when trying to replace one algorithm with a supposedly equivalent one. === Floating point operations === Most h/w these days uses IEEE floating, so that is not usually the problem. Most numbers have an closest binary representation, and compilers are good at using it. Order of evaluation is a big problem. This can change depending on compiler switches. Summing large numbers of floating point and switching between multiply-by-inverse and divide are both suspect. |
Parent: MorphoOptimizationProject
There are many reasons why source code compiled for and running on different platforms might not get the same result, even when single threaded.
- Floating point - compiler might chose a different binary pattern for a decimal number (unlikely), order of evaluation (likely), precision (using double for some intermediate results), implementation of functions such as asin or sqrt.
- Sorting algorithms - most sorting algorithms are not stable - items with equal keys may be sorted into either order.
- Random number generators - these are obviously unstable.
Platform here refers to a combination of hardware, compiler version, compiler switches, libraries, and operating systems.
For our purposes we are mostly concerned with only changing the number of threads, which is discussed elsewhere [where?].
However we have seen differences between Linux and OSX caused by these kinds of issues, and we also see them when trying to replace one algorithm with a supposedly equivalent one.
Floating point operations
Most h/w these days uses IEEE floating, so that is not usually the problem.
Most numbers have an closest binary representation, and compilers are good at using it.
Order of evaluation is a big problem. This can change depending on compiler switches. Summing large numbers of floating point and switching between multiply-by-inverse and divide are both suspect.