alt Hacker NewsC is also famously bad at floating point optimization.
Fortran has historcally led this realm (see the Numerical Recipes book).
Julia is a newer option, and I understand that both are commonly used in Python objects.
"Read the older 2nd ed. book in Fortran online for free."
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mianos • today at 5:19 AM
There is not a lot of floating point in an operating system.
The issue with floating point and aliasing preventing vectorisation was from the late 1980s when early C compilers lacked sophisticated alias analysis and standards were loose. is not a really a thing anymore. C can go as fast, specially compiled with strict aliasing. Maybe more work in compilation.
There are several reasons why Fortran historically has been faster. Many of these are because Fortran is less strict about what the compiler can do so allows optimizations that wouldn't be allowed in C. Such as:
- Procedure arguments are not allowed to alias. Similar to restrict pointers in C99+. This is often critical to allow loops to be vectorized, but the onus is on the programmer to ensure no aliasing or else you get UB.
- Unspecified evaluation order for expressions. E.g. C requires that "a+b+c+d" be evaluated as "((a+b)+c)+d)" and with floating point it can't do it another way due to rounding. Fortran can do e.g. "(a+b) + (c+d)" where each subterm can be computed in parallel, but again at the cost of slightly different results due to rounding behavior for floats.
- Old school Fortran lacked pointers which led programmers to program algorithms using arrays rather than fancier data structures, which cpu's love.
In principle there's nothing preventing a competent C or C++ programmer can reach Fortran level performance. In practice, might be difficult.
Of course, nowadays performance is much about designing for cache hierarchies (see e.g. "Data Oriented Design") where Fortran doesn't have a built-in advantage.